ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2017

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Pharmacy 240

Biopharmaceutical investigations ofdoxorubicin formulations used inliver cancer treatment

Studies in healthy pigs and liver cancerpatients, combined with pharmacokinetic andbiopharmaceutical modelling

ILSE R DUBBELBOER

ISSN 1651-6192ISBN 978-91-513-0124-2urn:nbn:se:uu:diva-330953

Dissertation presented at Uppsala University to be publicly examined in B41, BMC,Husargatan 3, Uppsala, Friday, 8 December 2017 at 09:15 for the degree of Doctor ofPhilosophy (Faculty of Pharmacy). The examination will be conducted in English. Facultyexaminer: Professor Hartmut Derendorf (College of Pharmacy, University of Florida).

AbstractDubbelboer, I. R. 2017. Biopharmaceutical investigations of doxorubicin formulations usedin liver cancer treatment. Studies in healthy pigs and liver cancer patients, combined withpharmacokinetic and biopharmaceutical modelling. Digital Comprehensive Summaries ofUppsala Dissertations from the Faculty of Pharmacy 240. 70 pp. Uppsala: Acta UniversitatisUpsaliensis. ISBN 978-91-513-0124-2.

There are currently two types of drug formulation in clinical use in the locoregional treatmentof intermediate hepatocellular carcinoma (HCC). In the emulsion LIPDOX, the cytostatic agentdoxorubicin (DOX) is dissolved in the aqueous phase, which is emulsified with the oily contrastagent Lipiodol® (LIP). In the microparticular system DEBDOX, DOX is loaded into the drug-eluting entity DC Bead™.

The overall aim of the thesis was to improve pharmaceutical understanding of the LIPDOXand DEBDOX formulations, in order to facilitate the future development of novel drug deliverysystems. In vivo release of DOX from the formulations and the disposition of DOX and itsactive metabolite doxorubicinol (DOXol) were assessed in an advanced multisampling-siteacute healthy pig model and in patients with HCC. The release of DOX and disposition ofDOX and DOXol where further analysed using physiologically based pharmacokinetic (PBPK)and biopharmaceutical (PBBP) modelling. The combination of in vivo investigations and insilico modelling could provide unique insight into the mechanisms behind drug release anddisposition.

The in vivo release of DOX from LIPDOX is not extended and controlled, as it is fromDEBDOX. With both formulations, DOX is released as a burst during the early phase ofadministration. The in vivo release of DOX from LIPDOX was faster than from DEBDOX inboth pigs and patients. The release from DEBDOX was slow and possibly incomplete. The invivo release of DOX from LIPDOX and DEBDOX could be described by using the PBBP modelin combination with in vitro release profiles.

The disposition of DOX and DOXol was modelled using a semi-PBPK model containingintracellular binding sites. The contrast agent Lipiodol® did not affect the hepatobiliarydisposition of DOX in the pig model. The control substance used in this study, cyclosporine A,inhibited the biliary excretion of DOX and DOXol but did not alter metabolism in healthy pigs.The disposition of DOX is similar in healthy pigs and humans, which was shown by the ease oftranslation of the semi-PBPK pig model to the human PBBP model.

Keywords: drug delivery system, in vivo release, PBPK modelling, hepatocellular carcinoma,doxorubicin, transarterial chemoembolization, drug disposition

Ilse R Dubbelboer, Department of Pharmacy, Box 580, Uppsala University, SE-75123Uppsala, Sweden.

© Ilse R Dubbelboer 2017

ISSN 1651-6192ISBN 978-91-513-0124-2urn:nbn:se:uu:diva-330953 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330953)

“Wat zou het leven zijn als we niet wat durfden aanpakken?” “What would life be if we had no courage to attempt anything?”

- Vincent van Gogh

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Dubbelboer, I.R.*, Lilienberg, E.*, Hedeland M., Bondesson, U.,

Piquette-Miller, M., Sjögren, E., Lennernäs, H. (2014) The effects of Lipiodol and Cyclosporine A on the Hepatobilliary Disposition of DOX in Pigs. Molecular Pharmaceutics, 11(4):1301–1313

II Lilienberg, E., Dubbelboer, I.R., Karalli, A., Axelsson, R., Brismar, T.B., Ebeling Barbier,C., Norén, A., Duraj, F., Hedeland, M., Bondesson, U., Sjögren, E., Stål, P., Nyman, R., Lennernäs, H. (2016) In vivo Drug Delivery Performance of Lipiodol-Based Emulsion or Drug-Eluting Beads in Patients with Hepatocellular Carcinoma. Molecular Pharmaceutics, 14(2): 448–458

III Dubbelboer, I.R., Lilienberg, E., Sjögren, E., Lennernäs, H. (2017) A Model-Based Approach To Assessing the Importance of Intracellular Binding Sites in DOX Disposition. Molecular Pharmaceutics, 14(3):686–698

IV Dubbelboer, I.R., Sjögren, E., Lennernäs, H. Porcine and human in

vivo predictions for doxorubicin-containing formulations used in locoregional HCC treatment. In manuscript

Reprints were made with permission from the respective publishers. On projects leading to Papers I and II, I was extensively involved in the planning and execution of experiments, data analysis of results and writing of the manuscripts. I was also extensively involved in all aspects of the projects leading to Papers III and IV. *The authors contributed equally to the execution of the study and writing of the article.

Additional papers not included in this thesis:

i. Dubbelboer, I.R.,, Lilienberg, E., Ahnfelt, E., Sjögren, E., Lennernäs, H. (2014) Treatment of Intermediate Stage Hepatocellular Carcinoma: a Review of Intrahepatic DOX Drug Delivery Systems. Therapeutic Delivery, 5(4):447–466

ii. Lilienberg, E., Dubbelboer, I.R., Sjögren, E., Lennernäs, H. (2016) Lipiodol does not affect the Tissue Distribution of Intravenous DOX Infusion in Pigs. Journal of Pharmacy and Pharmacology, 69(2):135-142

iii. Dubbelboer, I.R., Lilienberg, E., Karalli, A., Axelsson, R., Brismar,

T.B., Ebeling Barbier,C., Norén, A., Duraj, F., Hedeland, M., Bondesson, U., Sjögren, E., Stål, P., Nyman, R., Lennernäs, H. (In publication) Answer to “Commentary on ‘In vivo Drug Delivery Performance of Lipiodol-Based Emulsion or Drug-Eluting Beads in Patients with Hepatocellular Carcinoma’”. Submitted to Molecular Pharmaceutics

Contents

Background ................................................................................................... 11 Liver anatomy and function ..................................................................... 11 

Anatomy .............................................................................................. 11 Function ............................................................................................... 12 

Hepatocellular carcinoma ......................................................................... 12 Pathology ............................................................................................. 12 Incidence, mortality and risk factors ................................................... 13 Treatment ............................................................................................. 13 

Drug formulations used in TACE ............................................................ 15 Cytostatic Lipiodol® emulsions ........................................................... 15 Drug-eluting entities ............................................................................ 17 

The cytostatic drug doxorubicin ............................................................... 18 Pharmacology ...................................................................................... 18 Pharmacokinetics ................................................................................. 19 Doxorubicinol ...................................................................................... 21 

Pharmacokinetic modelling ...................................................................... 21 Compartmental models ........................................................................ 21 Physiologically based pharmacokinetic models .................................. 22 

Aims of the thesis.......................................................................................... 23 

Methods ........................................................................................................ 24 In vivo work .............................................................................................. 24 

Study design ........................................................................................ 24 Sampling, sample work-up and analysis of biological matrices .......... 26 

In silico models ........................................................................................ 27 Multi-compartment model ................................................................... 27 Semi-PBPK models ............................................................................. 28 PBBP models ....................................................................................... 30 Software and software parameters ....................................................... 32 

Data analysis ............................................................................................ 32 PK data analysis ................................................................................... 32 Analysis of additional output ............................................................... 33 

Results and discussion .................................................................................. 35 In vivo release of DOX from LIPDOX and DEBDOX ............................ 35 

Importance of site of measurement or sampling sites .......................... 35 DOX release from LIPDOX ................................................................ 36 DOX release from DEBDOX .............................................................. 39 

Effect of Lipiodol® on DOX and DOXol disposition .............................. 41 Effect of CsA on DOX and DOXol disposition ....................................... 42 Description of DOX tissue binding in PBPK modelling .......................... 44 

Effect of Kp,T on DOX disposition ....................................................... 44 Effect of intracellular binding sites on DOX disposition..................... 45 

Similarity in human and porcine doxorubicin disposition ....................... 45 Effect of liver cirrhosis on DOX disposition ............................................ 47 Variability in DOX PK in pig and human ................................................ 48 

Conclusions ................................................................................................... 51 

Populärvetenskaplig sammanfattning ........................................................... 52 

Populairwetenschappelijke samenvatting ..................................................... 54 

Acknowledgements ....................................................................................... 56 

References ..................................................................................................... 58 

Abbreviations

A amount of compound (A)AFE (absolute) average fold error AKR aldo-keto reductase aMSA advanced multi-sampling site acute AUC area under the plasma concentration-time curve B:P blood:plasma ratio of the drug C concentration CBR carbonyl reductase Cl clearance CP Child-Pugh CsA cyclosporine A (ciclosporin) (c)TACE (conventional) transarterial chemoembolization DCB DC bead™ DEB/DEE drug-eluting beads/entities DEBDOX drug-eluting beads (here DCB) loaded with DOX DOX(ol) doxorubicin(ol) EH apparent hepatic extraction ratio Fe fraction excreted Frel fraction released Fu,p the fraction of unbound drug in plasma Fvol,tr/un Volume fraction of treated or untreated liver section in

models GFR glomerular filtration rate GI gastro-intestinal HCC hepatocellular carcinoma IBS intracellular binding site k rate constant Kp,T tissue-to-plasma concentration partitioning coefficient LIP Lipiodol®

LIPDOX an aqueous doxorubicin solution emulsified with Lipiodol® NC1 or 2 non-clinical study 1 or 2 NCA non-compartmental analysis O/W oil-in-water PBBP physiologically based biopharmaceutical PBPK physiologically based pharmacokinetic PK pharmacokinetic(s)

PS ECOG performance status Q blood flow RDDS release of drug from formulation or drug delivery system t time t1/2 half-life V volume W/O water-in-oil

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Background

Liver anatomy and function Anatomy The liver is composed of left and right lobes. The lobes are divided into a total of 8 segments (Figure 1a). The left lobe comprises segments 1–4 and the right lobe comprises segments 5–8. The liver has a dual blood supply from the portal vein (75–80%) and the hepatic artery (20–25%). Each seg-ment has its own blood supply and biliary drainage.1

On a microscopic scale, the liver can be divided into lobules.2 The classic hepatic lobule forms a hexagonal structure (Figure 1b).2 The lobule compris-es all hepatocytes that are drained into one central vein, and is bound by two or more portal triads.2 A triad consists of the terminal branches of a hepatic artery and a portal vein and a bile duct.2 The terminal branches of the portal

Figure 1. (a) The liver is divided into eight segments; segments 1–4 form the left lobe and segments 5–8 form the right lobe. To demonstrate the blood supply to a tumour by a branch of the hepatic artery, segment 3 in the diagram contains a hepa-tocellular carcinoma (orange/yellow). (b) The microarchitecture of the classic hepat-ic lobule. The classic lobule is hexagonal, with a central vein in the middle. Blood from the hepatic arterioles and portal venules mixes in the sinusoids (square) and empties into the central vein. Bile is collected in the bile canaliculi which empty into the bile ducts on the outside of the lobule. The hepatic ateriole, portal venule and bile duct comprise the portal triad. (c) The sinusoids are lined with hepatocytes. Endothelial cells line the vascular walls, and the space of Disse is situated between the endothelial cells and the hepatocytes. Kupffer and stellate cells are also situated in the sinusoids. The figure was adapted from Bismuth2 and Siriwardena et al.2, 3

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vein and the hepatic artery converge into sinusoids, which drain into the central vein.2 The diameter of a portal venule or hepatic arteriole is in the range of 15–35 µm.4 The sinusoids are lined with hepatocytes, and are about 7-15 µm in diameter.2, 4 Each hepatocyte secretes bile into the bile canaliculi, which end in bile ductules and finally in the bile duct.2

The liver contains endothelial cells (2.8% of volume), Kupffer cells (2.1%), stellate cells (1.4%) and hepatocytes (~80%) (Figure 1c).2 Endothe-lial cells line the sinusoids, and the bile ductules and ducts.2 Endothelial cells in the sinusoids are fenestrated, i.e. have pores which are 0.05–0.15 µm in diameter.5 The fenestrations increase the flow of plasma solutes, but not blood cells, to the space of Disse.2 Kupffer cells are fixed macrophages that remove particulate matter, such as lipids, from the blood in the sinusoids.2, 6 Stellate cells are found in the space of Disse; these play a central role in fi-brogenesis after liver injury, which can lead to cirrhosis.2 Hepatocytes per-form most functions attributed to the liver.

Function The liver metabolizes, detoxifies and inactivates exogenous and endogenous compounds from the blood.2 Compounds that are degraded or biotrans-formed by the liver can be excreted back to the circulation or into the bile. Through the Kupffer cells, the liver filters particulate matter, such as bacte-ria, endotoxins, parasites and aging red blood cells, from the blood.

The liver stores and synthesizes important substances.2 Carbohydrates, peptides, vitamins, and some lipids from food can be stored by hepatocytes, and released when needed. Hepatocytes can synthesize plasma proteins (e.g., albumin), as well as substances that are important for the metabolic demands of the body (such as glucose, cholesterol, and phospholipids).

Hepatocellular carcinoma Pathology Hepatocellular carcinoma (HCC) is a solid tumour in the liver (Figure 1a).7 The majority of HCCs (70-90%) occur in cirrhotic livers.7 Either single or multiple tumours can be found and the tumours have different patterns of growth. Multinodular HCC (multiple tumours scattered throughout the liver) and diffuse HCC (multiple small nodules which mimic cirrhotic nodules) have been associated with a cirrhotic liver. Massive HCCs (where a solid tumour occupies much of the liver, possibly with some small satellite tu-mours) are found in noncirrhotic livers. The tumour itself can be expansive (distinct border) or spreading/infiltrative (no distinct border). Dependent on the time of diagnosis, an HCC can range from less than 1 to over 30 cm in

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diameter. HCCs are usually highly vascular, with a blood supply from the hepatic artery.

Incidence, mortality and risk factors About 80-95% of primary liver cancers are classified as HCC, and the terms are thus often used interchangeably.8 Around 782,000 people globally are affected by primary liver cancer each year and the incidence is rising.9 This makes primary liver cancer the sixth most common cancer form globally. The incidence ratio for women:men is 1:2.4, which means more men are diagnosed each year with primary liver cancer.9 The global incidence is 4.4- to 5-fold higher in less developed regions compared to more developed re-gions. For example, around 50% of the incidence occurs in China alone.

Nearly 745,000 people die yearly from primary liver cancer, making it the second most common cause of cancer death after lung cancer (1.6 million deaths).9 It has a poor prognosis, since the incidence:mortality ratio is around 1. There are no bigger differences in this ratio between sexes and regions.

The main causes of liver cirrhosis are the hepatitis B and C viruses and alcoholic liver disease. Hepatitis B and C increase the risk of HCC by 5- to 15-fold and 17-fold, respectively. It can take 2–3 decades for cirrhosis to develop in patients infected with hepatitis B or C. Heavy alcohol intake (>50–70 g/day) over prolonged time periods increases the incidence ratio for HCC 6-fold. Diabetes and obesity are risk factors as they increase the devel-opment and progression of hepatic fibrosis. Other risk factors for HCC are consumption of aflatoxin-contaminated foods, non-alcoholic fatty liver dis-ease, non-alcoholic steatohepatitis, and tobacco smoking.7

Treatment Clinical guidelines for the treatment of HCC have been published by the European Association for the Study of the Liver and the European Organisa-tion for Research and Treatment of Cancer.10 In these guidelines, treatment strategies are based upon the staging, or severity, of the disease. The BCLC (Barcelona Clinic Liver Cancer) classification divides HCC into 5 stages, from very early to advanced. The BCLC classification is based upon tumour size and nodularity, the Eastern Cooperative Oncology Group performance status (PS), and the Child Pugh (CP) score. The PS is defined as the patient’s level of functioning on a scale of 0–5, i.e., the impact of the disease on the patient’s daily living abilities.11 The CP score reflects the prognosis of chronic liver disease and cirrhosis.12 A CP score of A to C is given, based on five clinical features (bilirubin and albumin levels, prothrombin time, degree of ascites and grade of hepatic encephalopathy).

The treatment of HCC depends on the stage of the liver cancer.10 At a very early stage (single nodule, <2cm; PS0; CPA) the tumour is resected. At

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an early stage (single or up to 3 nodules, <3cm; PS0; CPA-B) the patient can receive a liver transplant or local ablation of the tumour by radiofrequency ablation or ethanol injection. At an intermediate stage (multinodu-lar/multifocal tumour; PS0; CPA-B) the patient can receive image-guided transarterial tumour chemoembolization therapy. Patients with advanced stage HCC (multinodular/multifocal tumour with portal invasion; PS1–2; CPA-B) receive systemic treatment with the cytostatic agent sorafenib. Ter-minal stage patients (PS > 2; CPC) receive the best supportive care.

Image-guided transarterial chemoembolization tumour therapy / TACE Image-guided transarterial tumour therapy is described as “the intravascular delivery of therapeutic agents via selective catheter placement with imaging guidance for the treatment of malignancy”.13 A schematic overview of this locoregional treatment option is given in Figure 2. Three treatment methods can be used, namely embolization, chemoembolization and radioembolization. Chemoembolization is most commonly used in the treatment of intermediate HCC. It involves the local infusion of a cytostatic agent combined with embo-lization of the blood vessel. Historically, image-guided tumour therapy with chemoembolization has been called transarterial chemoebolization (TACE). The location of administration and the used drug formulations make the rec-ommended image-guided transarterial tumour therapy with chemoemboliza-tion interesting from a pharmaceutical perspective. The locoregional admin-istration route could be seen as passive targeting of the tumour.

Two types of drug formulation have been used with TACE. The first is a cytostatic Lipiodol® emulsion; this formulation combined with the image-guided treatment procedure is usually called conventional TACE (cTACE). Historically, cTACE has described the administration of an aqueous solution with one or more cytostatic agents emulsified with Lipiodol® followed by additional embolization. Administration of this cytostatic Lipiodol® emul-sion without embolization has been called TOCE (transarterial oily che-moembolization) or TAI (transarterial infusion). However, recent guidelines

Figure 2. A schematic over-view of image-guided transarterial tumour therapy. A catheter is placed through the femoral artery into the hepatic artery by the interventional oncologist or radiologist. The drug formulation is then ad-ministered through the catheter and deposited close to the hepatocellular carcinoma (HCC).

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suggest the use of cTACE combined with a description of the procedure, independently of whether additional embolization was used.13

The second type of drug formulation is a drug-eluting entity (DEE) which, when combined with the image-guided treatment procedure, is usual-ly called DEE- or drug-eluting bead (DEB)-TACE. Both treatment options are used globally in the clinic to treat patients with HCC. The median sur-vival of patients with untreated intermediate HCC is 16 months.10 Che-moembolization treatment improves median survival to 19–20 months.10, 14 Meta-analyses of studies comparing cTACE and DEE-TACE show varying results. Generally, a trend for better disease control and overall survival with DEE-TACE has been observed.15-18

Drug formulations used in TACE Cytostatic Lipiodol® emulsions A wide variety of cytostatic Lipiodol® emulsions are used clinically world-wide. Both single-drug and multiple-drug emulsions are used, where doxo-rubicin (DOX) is the most commonly used additional drug.14, 19 Of 49 rele-vant studies published since 2016, 18 used DOX, either as a single or multi-ple drug emulsion.20-37

This thesis focuses specifically on LIPDOX. LIPDOX describes any emulsion of an aqueous solution containing DOX mixed with Lipiodol® (LIP).

Lipiodol® Lipiodol® (Guerbet, France) is a poppy seed oil which is iodinated (37% w/w, or 480 mg/mL iodine), making it suitable as a contrast agent.38 It has in fact been used in radiological applications since the 1920s. Since the 1980s, Lipiodol® has been used in the treatment of HCC. It is registered as an ap-proved drug product by the US Food and Drug Administration, and has the status of orphan drug designated for the management of known HCC since 2013. When administered through the hepatic artery of rats, Lipiodol® appears in the portal venules, and passes through to the sinusoids.39 This causes a tem-porary and partial stasis of the blood flow. In HCC tumours, Lipiodol® is visible for up to 90 days after administration. Several hypotheses have been suggested for the uptake and retainment of Lipiodol® by HCCs: (i) high vas-cularity and large microvessels improve Lipiodol® accessibility to the tu-mour, (ii) lack of Kupffer cells and lymphatic system in the tumour micro-environment reduces Lipiodol® elimination, and (iii) direct capture of Lip-iodol® by tumour and endothelial cells.38

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Composition of LIPDOX A variety of different LIPDOX emulsions have been used clinically, alt-hough the exact composition of the LIPDOX formulation has not always been described in published studies.40 The aqueous phase in the emulsions can contain water or a combination of water and contrast agent. As Lip-iodol® has a high iodine content, its density is 1.28, which is higher than most aqueous liquids.38 Equalizing the density of the aqueous phase to the Lipiodol® density increases the emulsion stability.41 Clinically, this can be done by adding a contrast agent to the aqueous phase. Of the previously mentioned 18 LIPDOX articles published since 2016, three stated that a con-trast agent was used to dissolve the drug.25, 31, 35 The dissolution medium was not specified in the remaining 15 articles. No mention of an emulsifier to further stabilize the emulsion was made in any of these 18 articles.

The ratio of the aqueous to Lipiodol® phases ranges from 4:1 to 1:3.33 in the clinic, but is mostly reported as 1:1.40 Only five of the 18 LIPDOX arti-cles published since 2016 mentioned the aqueous:Lipiodol® ratio, which ranged from 1:1–3.3.25, 26, 30-32, 35 The ratio of the phases can affect the emul-sion stability; lower Lipiodol® ratios make the emulsion less stable.42-44 The aqueous:Lipiodol® phase ratio can affect the type of emulsion obtained after mixing. Water-in-oil (W/O) emulsions with small droplets (2–3 µm in diam-eter) are formed when the aqueous:Lipiodol® ratio is 1:2–4.45 Oil-in-water (O/W) or more complex emulsions with bigger droplets (6–11 µm in diame-ter) are formed with aqueous:Lipiodol® ratios of 2–4:1.45

Clinical preparation of the emulsion LIPDOX is often prepared extemporaneously using a pumping technique.38,

40 That is, the syringe containing the aqueous phase with DOX and the sy-ringe containing Lipiodol® are connected with, for example, a three-way stopcock. The liquids are then mixed by pumping them back and forth be-tween the two syringes, as shown in Figure 3. This preparation procedure is not standardized, which affects the characteris-tics of the formed emulsion. For example, while using the pumping tech-nique, droplet size ranges of 2–3 µm and 30–120 µm have been observed.45,

46 The smaller size range was obtained by pumping the solutions back and forth for 5 minutes, while the larger size range was obtained by 20 pushes and pulls through the syringes.

Figure 3. The extemporaneous preparation (pump-ing) technique used in the emulsification of LIPDOX. A syringe containing Lipiodol® and a syringe containing an aqueous solution of doxoru-bicin are connected with a two-way stopcock. The solutions are then pumped back and forth between the syringes.

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The DOX dose is not standardized in LIPDOX. From the 18 reviewed LIPDOX articles published since 2016, the DOX dose ranged from 20 to 100 mg and 25 to 75 mg/m2 per treatment procedure.20-37

Administration LIPDOX can be administered lobularly, segmentally, or subsegmentally, and all administration sites are used clinically. LIPDOX administration can be followed by administration of embolic particles.38 These embolic particles can be biodegradable (e.g. gelatine sponge) or permanent (e.g. polyvinyl alcohol microparticles). From the 18 reviewed LIPDOX articles published since 2016, anywhere from 2-20 mL LIPDOX has been administered during a treatment procedure.20-37 The Lipiodol® dose is dependent on the tumour size, tumour physiology, and condition of the liver.40

Drug-eluting entities Several types of DEEs can be used in image-guided TACE; for example, DC Bead™ (DCB), HepaSphere™, LifePearl® and Tandem™.47 Of these, DCB and HepaSphere™ are used globally48, with more publications related to DCB. In this thesis, the abbreviation DEBDOX is used to describe DOX-loaded DEEs (DCB was the specific DEB used) of any size and with any DOX loading.

DC Bead™ DCB (Biocompatibles Ltd, UK) is a polyvinyl alcohol-based hydrogel.40 The hydrogel contains negatively charged sulfonate groups, to which sodium ions are bound prior to loading. These hydrogels are biocompatible and non-biodegradable. DCB has been available for DEE-TACE since 2006. There are several sizes of DCB hydrogels currently on the market: 70–150 µm (M1), 100–300 µm, 300–500 µm, and 500–700 µm.49 The size ranges 700-900 µm and 900-1200 µm were previously available.

Loading of drug Positively charged substances, such as DOX and irinotecan, can be loaded into DCB. Loading of DOX is achieved by an ion-exchange mechanism and self-aggregation of DOX.50, 51 Upon removal of the sodium solution and addition of DOX solution, up to 40 mg DOX can be loaded per mL DCB.52 The loading time depends on the concentration of the loading solution, the amount to be loaded and the bead size, and can range from 30 min (70–150 µm, 25 mg/ml DOX solution) to 24h (500-700 µm, 2 mg/ml DOX solution). Clinically, DCB is usually loaded with 37.5 mg DOX per mL DCB, a total of 75 mg DOX is thus loaded into each vial of DCB.

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Administration The administration of DEBDOX is rather standardized, and has been de-scribed in both the literature and the package insert.49, 53 DEBDOX should be administered segmentally or subsegmentally (superselectively) whenever possible, to avoid embolization of vessels not leading to the tumour. It is recommended that the smallest size of DCB is administered first during treatment, as smaller sizes will penetrate deeper into the tumour. However, the hydrogel size should be chosen according to the pathology. Before ad-ministration, DEBDOX is mixed with a non-ionic contrast agent. During infusion, the administration rate should be slow and the syringe should be agitated to avoid sedimentation of DEBDOX in the syringe. A maximum dose of 150 mg DOX can be administered during one treatment.

The cytostatic drug doxorubicin DOX, formulated in emulsion with Lipiodol® or loaded into DEEs such as DCB, is the most commonly used cytostatic drug for treatment of HCC. It is a bright red powder and forms an orange-red solution in water. Structurally, DOX comprises an aglycone with a daunosamine group (sugar component) attached by a glycosidic bond.54 The physicochemical properties and molec-ular structure of DOX and its active metabolite doxorubicinol (DOXol) are presented in Table 1.

Table 1. Physicochemical properties of doxorubicin and doxorubicinol.

Doxorubicin Doxorubicinol

Molecular structure

Molecular weight (g/mol)55, 56 543.525 545.541 Molecular formula55, 56 C27H29NO11 C27H31NO11 Polar surface area (Å2)55, 56 206 209 Hydrogen bond donors55, 56 6 7 Hydrogen bond acceptors55, 56 12 12 Solubility (mg/ml, PBS)57 1.25 LogP58-61 1.27 LogD7.4

62 2.42±0.08 1.19±0.06

Pharmacology DOX is an antineoplastic agent, classified as a cytotoxic anthracycline anti-biotic (ATC code: L01DB01). It is used in the treatment of multiple forms of

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cancer such as soft-tissue sarcomas, non-Hodgkin's lymphomas, and ovary, breast, and stomach cancers.63 There are at least three anti-tumour mecha-nisms mediating its effects: (i) reversible binding to topoisomerase I and II, (ii) intercalation to DNA base pairs, and (iii) free-radical generation, which causes DNA damage (Figure 4).54 The concentration of DOX required for 50% growth inhibition (IC50) in vitro is reciprocal with time and cell-line-dependent.64 Unpublished IC50 values for DOX in three HCC cell lines (HepG2, Huh7 and SNU449) were 3–120 µM at 24 h and 0.1–70 µM at 72 h.65

Pharmacokinetics When DOX is administered via the intravenous route, the plasma pharmaco-kinetics (PK) have been described by both two- and three-compartment models.66 The first (distribution) phase is rapid, and the terminal (elimina-tion) phase is slow. The half-life ranges from 3 to 47 min (distribution) and 14 to 50 h (terminal).66 In humans, DOX PK are not affected by the dose in the range 20–70 mg/m2.67-69 The oral administration route is not used for DOX because of its low bioavailability (<3%), poor and variable intestinal permeability (around 0.1*10-6 cm/s) and low fraction absorbed from the in-testine (>20%) in rats.70-72

Figure 4. The toxicity and disposition of doxorubicin (DOX). DOX inhibits the binding of topoisomerase (TOP2A) to DNA, intercalates to DNA, and enzymatic reduction forms reactive oxygen species (ROS). These three mechanisms lead to cell death. DOX is distributed and eliminated by passive diffusion (arrows) and carrier-mediated transport (arrows with orange circle). DOX is metabolized to doxorubicin-ol (DOXol) by carbonyl reductases (CBR1, CBR3) and aldo-keto reductases (AKR1A1, AKR1C3). Information in the figure is based on published data.58-61, 73-76

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Once infused into the blood circulation, DOX is distributed quickly to the tissues. Elevated DOX tissue concentration-time profiles have been observed in several species.77-79 Consequently, the tissue-to-plasma concentration par-titioning coefficient (Kp,T) is high (ranging between 50 and 1300 in pig, rat, guinea pig and rabbit).80, 81 DOX is known to bind to DNA and the acidic phospholipid cardiolipin, which are found intracellularly in the nucleus and the mitochondria.82-86 Accordingly, intracellular distribution favours the nu-cleus (50-fold higher than intracellular), which is in good agreement with the reported anti-tumour mechanisms.54

DOX passes through the cellular membrane by passive diffusion and car-rier-mediated transport (Figure 4). Absorptive transport in Caco-2 cells has been speculated to occur mainly via the paracellular route.71 A multitude of transporters have been identified to facilitate DOX transport (Figure 4):37-40,

46 Solute carrier organic anion transporter family member 1A2 (OATP1A2,

SLCO1a2, uptake), Solute carrier family 22 member 16 (OCT6, SLC22A16, uptake), Canalicular multispecific organic anion transporter 2 (MRP3, ABCC3, efflux), Multidrug resistance protein 1 (MDR1, P-gp, ABCB1, efflux), Breast cancer resistance protein (BCRP1, ABCG2, efflux), Bile salt export pump (BSEP, ABCB11, efflux), Canalicular multispecific organic anion transporter 1 (MRP2, ABCC2, efflux), Multidrug resistance-associated protein 1 (MRP1, ABCC1), Multidrug resistance-associated protein 6 (MRP6, ABCC6), Multidrug resistance-associated protein 7 (MRP7, ABCC10), ATP-binding cassette sub-family B member 8, mitochondrial (MABC1,

ABCB8), RalA-binding protein 1 (RLIP1, RALBP1)

DOX is eliminated by metabolism and excretion to bile and urine. It is me-tabolised to DOXol by aldo-keto and carbonyl reductases (AKR1A1, AKR1C3, CBR1, CBR3). These reductases are available in the cytosol of cells. The highest DOX-to-DOXol biotransformation rates have been found in the liver and kidneys, although intestine, heart, muscle and lung also have metabolic capacities.87 Other inactive, deglycosidated metabolites have been identified as well.88

Within 6 to 7 days after administration of DOX, about 50% of the dose has been excreted to the bile and 12% to urine.89 The portion eliminated in the bile consists of unchanged DOX (about 50%), DOXol (23%), and other metabolites (27%). The portion eliminated in the urine is mainly DOX (about 66%), with metabolites making up the remainder.

21

Doxorubicinol DOXol is about 75-fold less therapeutically active than DOX, but has been speculated to be the main cause of the cardio-related toxicity of DOX.90, 91 The half-life of DOXol in humans is similar to that of DOX, around 30h.66 The elimination half-life of DOXol is most likely formation rate-limited. The half-life after DOXol injection to dogs was 3.7 h, while it was up to 30h after administration of DOX.92

Pharmacokinetic modelling Mathematical or in silico modelling is frequently used in the field of PK to describe or elucidate the mechanisms behind the concentration-time profiles from plasma, tissue or the gastro-intestinal (GI) tract.93 Different types of modelling strategies can be adopted for this purpose, where the most com-mon one is by compartments connected to each other by mass-transport.93

Compartmental models Compartmental models usually contain a certain number of compartments needed to be able to describe the different phases of the plasma concentra-tion-time curves: absorption, distribution and elimination.93, 94 One-compartment models describe the plasma concentration-time curve after intravenous administration of a substance with first-order elimination kinet-ics. The mass-transport to and from the compartment is commonly described by rate constants (k), or clearance (Cl) and volume (V) as in the following equation (Eq 1).

∗ ∗ (1)

Multi-compartment models are used when there is a multi-phase decline in the plasma concentration-time curve.94 Here the compartments describe a central compartment and one (or several) peripheral compartment(s). The central compartment usually describes the plasma, while the other compart-ments are used to represent drug distribution to other parts of the body, e.g., peripheral tissues. The mass transport between two compartments is de-scribed by Eq 2.

∗ ∗ (2)

When a compartmental model is fitted to the observed data, the values of the micro-constants (k, Cl, V) are estimated. From these values, PK parame-ters such as half-life (t1/2) and area under the plasma concentration-time curve (AUC) can be derived. Multi-compartmental models are usually used in a descriptive manner.

22

Physiologically based pharmacokinetic models Physiologically based pharmacokinetic (PBPK) models are multi-compartmental models.93 Each compartment represents a specific physiolog-ically entity, e.g. plasma or tissue, described with representative values such as tissue weight or volume. The tissue compartments are connected by flow rates which represent the blood flows to and from the tissue. PBPK models commonly include “lumped” tissue compartments. Lumped compartments describe a collection of tissues for which the specific concentrations are ir-relevant to the purpose of the specific PBPK model, but which have the same properties, e.g. rapid or slow blood flow. PBPK models with lumped tissue compartments are usually described as semi-PBPK models.

Distribution of the drug to and from the tissue compartment is commonly regarded to be either perfusion or permeability limited.93 When the distribu-tion is perfusion limited, Eq.s 3 and 4 describe the distribution of the drug from the concentration on entering the arterial blood (Cab), to that on exiting the venous blood (Cvb,T) and that in the compartment tissue (CT):

, (3)

,∗ : ∗ ,

, (4)

where VT describes the tissue volume, QT the blood flow to and from the tissue, B:P the blood-plasma ratio of the drug and Fu,p the fraction of un-bound drug in plasma. However, if the tissue distribution is permeability limited, Eq.s 3 and 4 cannot be used.93 The tissue compartment will then probably be divided into two or more subcompartments describing the place of the rate-limiting step, such as the cell membrane. The distribution could be described by the rate of clearance over the permeability barrier.

Because of the physiological relevance of PBPK models, bottom-up ap-proaches can be applied.95 This means that specific biological processes can be scaled up from in vitro experiments. For example, the intrinsic hepatic clearance could be scaled up to the whole liver from in vitro experiments on isolated hepatocytes.93

PBPK modelling has been made easier in recent years by the availability of open source and commercial software, such as PK-sim, GastroPlus and Simcyp Population-Based Simulator.93, 96

Physiologically based biopharmaceutical (PBBP) models PBPK models which emphasize the release of the drug from the formulation or drug delivery system are also known as PBBP models. This term was introduced in 2014 for a model that described the release and PK of 2-hydroxyflutamide from a modified-release formulation to prostate tissue and plasma.97

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Aims of the thesis

This thesis seeks to improve understanding of drug formulations used in the treatment of intermediate HCC. The long-term goal of this project is to de-velop novel drug delivery systems with improved clinical outcomes. In order to optimize any process, one first needs to understand how the basics func-tion. In this case, the LIPDOX and DEBDOX formulations were studied from a biopharmaceutical perspective.

The aim of Paper I was to evaluate the effect of the excipient Lipiodol®

and cyclosporine A (ciclosporin; CsA) on the hepatobiliary disposition of DOX and DOXol in an advanced multisampling-site acute pig model. CsA was used as a positive control in this study, since it has an inhibito-ry effect on the biliary excretion of DOX. Multi-compartment PK mod-elling was used to evaluate the effect of CsA on the disposition of DOX and DOXol.

The aim of Paper II was to evaluate the in vivo release of DOX from LIPDOX and DEBDOX in human patients with HCC. In addition, uri-nary excretion of DOX from these formulations, and their efficacy and safety in human patients with HCC, was assessed.

The aim of Paper III was to describe the PK of DOX and DOXol in healthy pigs using PBPK modelling, in order to describe the pronounced intracellular binding of these compounds.

The aim of Paper IV was to predict the in vivo release of DOX from LIPDOX and DEBDOX in healthy pigs and human patients with HCC using biopharmaceutical modelling and simulation.

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Methods

In vivo work Two in vivo studies were carried out (these are described in Papers I and II). Paper I describes the effect of Lipiodol® and/or cyclosporine A (CsA) on the disposition of DOX and DOXol in the advanced multi-sampling site acute (aMSA) pig model. This pig study is also referred to as non-clinical study 2 (NC2) throughout this thesis. Drug concentrations in the tissues sampled in this study were published in Paper ii.80 Paper II describes the in vivo release of DOX and DOXol from LIPDOX and DEBDOX in a clinical study of patients with HCC, and the subsequent plasma PK.

Our group has previously published another DOX study in the aMSA pig model, by Lilienberg et al. (2014).98 This study is referred to in this thesis as non-clinical study 1 (NC1). NC1 comprised three treatment groups: those receiving a 50-minute intravenous infusion of DOX into an ear vein (IV group), those receiving LIPDOX via the hepatic artery (LIPDOX group), and those receiving DEBDOX via the hepatic artery (DEBDOX group). Plasma concentration-time and biliary excretion profiles were collected. Although the NC1 study was not performed as part of this thesis nor by the thesis author, the study is mentioned here as the historical data were used in the developed in silico models used in Papers III and IV.

Study design Effects of Lipiodol® and CsA on DOX and DOXol disposition (NC2) Twelve male, mixed-breed pigs were divided into four treatment groups (TI-TIV; Figure 5). Each pig received two consecutive intravenous infusions of 57.8 µmol DOX (at 0-5 and 200-205 min) into the right ear vein. Before the second dose of DOX was administered, each treatment group received addi-tional treatment administered into the portal vein. Thus, at 165–185 min, groups TI and TII received an infusion of saline, while groups TIII and TIV received an infusion of 250 mg CsA. Then, at 190–195 min, groups TI and TIII received a saline infusion, while groups TII and TIV received Lipiodol® emulsion (6 mL Lipiodol®, 1.8 mL H2O).

Blood was sampled from the hepatic vein and the hepatic artery (before and after the liver, local samples) and the femoral artery (systemic, peripher-al samples) during the whole study period (Figure 5). Bile was sampled at 20

25

Figure 5. The NC2 study design for the advanced multi-sampling site pig model. Doxorubicin (DOX, 57.8 µmol, black box) was administered into the right ear vein at 0-5 and 200-205 minutes. Lipiodol® (LIP, 6 mL in 1.8 mL sterile water, grey box) was administered via the portal vein to groups II and IV at 190-195 minutes. Cyclo-sporine A (CsA, 250 mg, grey box) was administered to groups III and IV at 165-185 min. When no Lipiodol® or CsA was administered, saline solution was adminis-tered (white box). Plasma ( | ) and bile (—X—) were sampled throughout the study period. Urine was collected continuously and sampled at the end of the study period (—*). Tissue samples from kidney, liver, lung and intestine were collected at the end of the study period (∆).

minute intervals. Urine was collected throughout the study period. At the end of the study period (360 min), the urine was sampled. The pigs were eu-thanized and tissue samples from liver, kidney, heart and intestine were col-lected (Paper ii).

Clinical study of DOX release from LIPDOX and DEBDOX and PK comparison Patients with HCC admitted to treatment centres at Uppsala University Hos-pital and Karolinska University Hospital were divided into two study arms (according to the hospital they attended) for this open, prospective, non-randomized, multicentre study. All patients were scheduled for 4 visits (Ta-ble 2). During Visit I, patients were screened for inclusion and exclusion criteria, their blood was sampled and their tumours were imaged. During Visit II, patients received the image-guided transarterial tumour therapy standard with chemoembolization at each clinic. Local (orifice hepatic vein in vena cava) and systemic (femoral vein) blood samples for PK analysis were collected up to 6 hours after the end of treatment. Systemic blood sam-ples for PK analysis and safety sampling were collected at 24h. Urine was collected for 24h and then sampled. During Visit III, blood samples were collected for PK analysis and safety. During Visit IV, patients received fol-low-up tumour imaging.

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Table 2. Study design for the clinical trial

Visit I Visit II Visit III Visit IV

Screening Treatment Check-up Final visit

Time period Pre-treatment 0–24h 5–7 days 4–6 weeks Blood sample: safety X X X Blood sample: PK X X Tumour imaging X X Uppsala University hospital Included patients 15 13 11 9 Tumour imaging technique

MR MR

Catheter placement Lobular Drug delivery system LIPDOX (no embolization) Karolinska University Hospital Included patients 15 12 12 11 Tumour imaging technique

CT CT

Catheter placement Subsegmental Drug delivery system DEBDOX CT = computed tomography; DEBDOX = doxorubicin-loaded DC Bead™; LIPDOX = doxo-rubicin-in-Lipiodol® emulsion; MR = magnetic resonance; PK = pharmacokinetics.

Patients at Uppsala University Hospital received LIPDOX without addi-tional embolization via a catheter with lobular placement. The LIPDOX emulsion contained an aqueous solution of 2.56 mL iohexol, 0.44 ml sterile water and 50 mg DOX mixed with 10 mL Lipiodol®. LIPDOX was consti-tuted extemporaneously immediately before administration by pumping the liquids back and forth between two syringes.

Patients at Karolinska University Hospital received DEBDOX via a catheter placed superselectively (subsegmentally). DEBDOX consisted of DOX-loaded DCB (37.5 mg DOX/mL DCB). All available bead sizes were used. Unloaded DCB hydrogels were administered if blood flow stasis was not obtained after the administered dose (150 mg DOX).

Sampling, sample work-up and analysis of biological matrices Blood samples were collected in EDTA vacutainers and stored on ice. Blood samples were centrifuged within 30 min of collection (Papers I and II). Urine was collected continuously until the end of the blood sampling period (Papers I and II). Bile was sampled on ice at 20 min intervals during the whole study period (Paper I). All biological matrices were aliquoted to dark polypropylene vials to protect DOX from light and were stored at −20 °C pending analysis.

27

All further sample work-up and analysis of the biological matrices was performed by employees at SVA (Statens Veterinärmedicinska An-stalt/National Veterinary Institute). Sample work-up and analysis with ul-traperformance liquid chromatography-tandem mass spectrometry is de-scribed in Papers I and II, as well as in Lilienberg et al.98

In silico models Different types of in silico models were used to describe and explore the disposition of DOX and DOXol in pigs and humans. A multi-compartment model was used in Paper I to elucidate the effect of CsA on DOX and DOXol disposition. In Paper III, semi-PBPK models were developed to describe the disposition of DOX and DOXol after intravenous administration to healthy pigs. PBBP models were used to evaluate the in vivo release of DOX from LIPDOX or DEBDOX in pigs and HCC patients (Paper IV).

Multi-compartment model Model development The mechanisms behind the effects of Lipiodol® or CsA on DOX and DOX-ol disposition in the NC2 study were investigated with a multi-compartment PK model (Figure 6). A three-compartment physiological model structure, representing plasma (central), tissue and liver, was adopted with first-order reactions describing the disposition processes (distribution/elimination). Eq. 5 describes the first-order mass transport in the model:

∗ ∗ (5)

where A is the amount of compound and t the time.

Figure 6. Multi-compartmental model describing the disposition of doxorubicin (DOX) and its metabolite doxorubicinol (DOXol). Ovals represent the distribution compartments for DOX and DOXol. Distribution to and from tissue, plasma, liver, bile and urine is shown with solid arrows, while metabolism of DOX and DOXol is shown with dashed arrows.

28

Study design The multi-compartmental model was fitted to the reference phase (0-160 min, P1) of all the observed NC2 data (n=12) to estimate 12 model parame-ters. Thereafter the model and the estimated parameters were used to simu-late the effect of Lipiodol® or CsA on the disposition of DOX and DOXol. Inhibition of metabolic and biliary excretion parameters was simulated by reducing parameter values to 1% of the estimated values in various combina-tions. The simulated inhibition started at 200 min and was constant until the end of the simulation (360 min). These simulations were compared with the observed porcine data.

Semi-PBPK models Two semi-PBPK models were developed in Paper III to describe the ob-served DOX and DOXol PK profiles. These PK profiles consisted of data from the NC198 (IV group) and NC2 (Paper I and Paper ii80) studies.

Model development The two semi-PBPK models, one generic and one binding-specific, followed the same basic model structure (Figure 7). The models comprised six tissue compartments, two blood compartments (arterial and venous) and two excre-tion compartments (bile and urine). The liver and kidney compartments were divided into three sub-compartments: vascular, extracellular and cellular. Lung, GI/spleen, and slowly and rapidly perfused tissues were each de-scribed as one compartment. The binding-specific semi-PBPK model also included an intracellular binding site (IBS) in each tissue compartment or tissue cellular subcompartment (liver and kidney). This model structure was adapted to describe the disposition of DOX and DOXol. The mass transfer between blood and tissue compartments was described by differential Eq.s 3 and 4 (see section in Background headed “Physiologically based pharmacokinetic models”, page 22). Distribution between the vascular and extracellular sub-compartments in the liver and kidney was described by the capillary wall diffusion clearance.

Intracellular binding sites (IBSs) were available in the binding-specific model, and distribution to and from the IBSs occurred as described in Eq. 6. Here the association clearance (Clon) is set to its estimated value; as the in-tracellular binding site concentration (Ct,IBS) reaches its maximum binding, Clon was set to 0. The dissociation clearance (Cloff) remained equal to its estimated value.

,, ∗ ∗ , (6)

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Figure 7. The model structure for the generic and binding-specific semi-PBPK mod-els. Note that the intracellular binding site is only included in the binding-specific model.

Metabolism in the liver and kidney was described by Eq.s 7 and 8, where Vmax and Km are constants of the Michaelis Menten equation, Ccel is the concentration in the cellular subcompartment, SFmet is the scaling factor cor-recting for interspecies and organ differences, MTPMH is the total protein content of hepatocytes, and HPGL is the hepatocellularity.

∗∗ (7)

∗ ∗ ∗ (8)

Hepatic and renal excretion (Clexcr) to bile and urine was described by unidi-rectional linear kinetics. Biliary excretion was modelled to take place from the hepatocellular subcompartment, while urinary excretion was specified from the vascular space via glomerular filtration (glomerular filtration rate, GFR) and from the kidney cellular space via renal excretion.

Study design The generic and binding-specific semi-PBPK models were fitted to NC2 data from pigs not receiving CsA (groups TI and TII; Paper I and Paper ii80). The parameters were estimated during the fitting of the model to the plasma concentration-time profiles, biliary and urinary excretion profiles and liver and kidney concentrations, simultaneously. The model that fitted the observed data best was chosen to continue the study.

30

The performance of the best model (binding-specific) was then evaluated by simulating the observed data from the NC1 data98 (subset: IV group). Here, 4 pigs received a 50-minute infusion of DOX into an ear vein. Data for plasma concentrations and biliary excretion were available.

Because of differences observed between simulated and observed data from NC1, the model was fitted to the IV group of the NC1 data set. A re-duced number of parameters was estimated, as urinary excretion and tissue concentrations were not available in this study.

Finally, a sensitivity analysis was performed. The estimated parameters were increased and reduced 2-fold from the original value. Each parameter was evaluated separately from other parameter changes.

PBBP models Porcine and human HCC PBBP models were developed from the binding-specific PBPK model. The aim of the PBBP models was to describe DOX PK profiles after administration of LIPDOX or DEBDOX to pigs and HCC patients. Model development The following alterations were made for the porcine and human HCC PBBP models: The liver compartment was split into two sections: untreated and treated.

Each liver section contained the vascular, extracellular and cellular sub-compartments. Distribution parameters and blood flow were adjusted to the chosen size of the liver section. The treated and untreated liver sections were supplied with blood from the portal vein (80%) and the hepatic artery (20%) in the pig PBBP model. In the human PBBP model, the treated section was supplied with blood from the hepatic artery (100%). Blood flow to the untreated sec-tion was adjusted accordingly.

The administration site was changed to the vascular compartment of the treated liver section.

The following alterations were also included in the human HCC PBBP mod-el: Species-specific parameters were changed from porcine to human val-

ues. The option to simulate different degrees of liver cirrhosis in the untreat-

ed liver section was included, classified using the CP classes. Simulated liver cirrhosis altered the cardiac output, organ blood flow, GFR, frac-tion of unbound drug, blood:plasma ratio and the functional liver mass.99,

100

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DOX release from LIPDOX and DEBDOX In the PBPK models, the input of DOX into the system was modelled as a constant infusion, i.e., a constant inflow of DOX per time unit during the administration period. When administering LIPDOX or DEBDOX, the input of DOX into the system is equal to the release rate of DOX from each of the formulations. The release rate of DOX from these formulations is not con-stant over time. To model the input of DOX into the pig and human HCC PBBP models, 53 release data sets were obtained from published reports or via personal communication.43, 51, 57, 98, 101-108 A modified version of the Weibull equation (Eq. 9) was fitted to the release data sets to mathematically describe the release profiles and obtain release parameter estimates.

∗ , ∗ 1 (9)

where Arel is the cumulative amount/percentage/fraction released, dose is the dose loaded into the formulation, Frel,max is the maximum fraction of the dose that could be released from the formulation, t is time (min), and A and B are constants affecting the shape of the release curve.

The release of DOX into the porcine PBBP model was described using a derivative of the Weibull equation (Eq. 10) and the estimated release param-eters from the release data sets. It was assumed that the formulation was administered as a bolus dose.

∗ , ∗ ∗ ∗ ∗ (10)

where RDDS is the rate of release of DOX from the formulation. In the human HCC PBBP model, the following equations (11 and 12) were used to de-scribe the release of DOX from the administered formulation after the first minute, assuming a constant administration rate.

, ∗ , ∗ ∗ ∗ ∗ e (11)

, ∑ , (12)

Embolization of treated vessels In the porcine and human HCC PBBP models, it was assumed that LIPDOX and DEBDOX caused embolization of the blood supplying arteries (hepatic artery and portal vein in pig, and hepatic artery in human HCC). The embo-lization caused by LIPDOX is described by Eq.s 13 and 14. Blood flow (Q) in the treated area (Fvol,tr) is gradually recovered after administration of LIPDOX (after 3 days in rats).109

∗ , ∗ 1 ∗ (13)

/ (14)

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DEBDOX is administered until complete and irreversible embolization in the treated hepatic artery is achieved. However, the treated section is often supplied by two or more hepatic arteries110, 111 and DEBDOX will only em-bolize the specific vessel used for its administration. In line with this, a per-manent embolization of 50% from the first minute of administration was applied during simulations with DEBDOX.

Study design The PBBP models were used to predict the DOX plasma concentration-time profiles of HCC patients treated locoregionally with LIPDOX or DEBDOX.

In order to predict these concentrations, 53 release data sets were collect-ed and values for release parameters were estimated. The release parameters from each data set (separate) were used in the porcine PBBP model to simu-late in vivo plasma concentration-time profiles and biliary excretion. The simulations were compared with the observed PK porcine data from NC1 (groups LIPDOX and DEBDOX).98 The DOX release data sets with the best predictive properties were identified.

The identified release data sets were thereafter used in the human HCC PBBP model. The resulting simulated plasma concentration-time curves were compared with observed plasma concentration-time curves for human HCC patients (Paper II).

Software and software parameters The multi-compartmental model was developed using Berkeley Madonna (Version 8.3.18, University of California at Berkeley). All parameter estima-tions were performed using Phoenix 64 WinNonlin 6.3 (Certara USA, Inc., USA). Standard settings used in model options were: 1/ŷ2 weighting scheme for plasma PK profiles, and uniform weighting scheme for biliary and uri-nary excretion.

Data analysis PK data analysis Non-compartmental analysis DOX and DOXol plasma concentration-time curves, and biliary and urinary excretion were analysed using non-compartmental analysis (NCA) using Phoenix WinNonLin 6.3 (Papers I, II, IV). All NCAs were performed using the pre-set settings with some adjustments. The linear and logarithmic trape-zoidal computational method was used for the AUC calculations. A 1/ŷ2 weighting scheme was used for plasma PK profiles, and a uniform weighting scheme was used for biliary and urinary excretion. The following PK param-

33

eters were reported from the NCA: maximum concentration (Cmax), time to Cmax (tmax), AUC, t1/2, Cl, volume of distribution at steady state (Vss), fraction excreted (fe). Other PK parameters were calculated from these PK parame-ters: apparent hepatic extraction ratio (EH), apparent biliary clearance (Clapp,bile), apparent urinary clearance (Clapp,urine).

Compartmental analysis The plasma concentration-time profiles of the reference study phase (P1, 0-160 min) for the NC2 data set (Paper I) were evaluated using compart-mental analysis. The plasma concentration–time curves for DOX from each sampling site (portal, hepatic and femoral vein) were analysed using one-, two- and three- compartment models, adopting a 1/ŷ2 weighting scheme.

Deconvolution: in vivo release from LIPDOX and DEBDOX In Paper II, the in vivo release rate of DOX from LIPDOX and DEBDOX was estimated by deconvolution of the HCC patient plasma concentration-time curve data using WinNonLin and a three-compartment model. As no individual reference intravenous plasma concentration-time curves were available, observed intravenous DOX plasma concentration-time curves for HCC patients were obtained from the literature.112 Frel from LIPDOX or DEBDOX into the systemic (femoral vein) and local (orifice hepatic vein/vena cava) sampling sites was determined at 6h and 24 h (systemic only).

Analysis of additional output The results from the models were compared during model development, curve fitting and parameter estimation, and model discrimination. Different methods were used to compare output.

The Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) relate the weighted residual sum of squares to the number of parame-ters used in the curve fitting. The lower the number, the better the result. These values were used to evaluate whether a one-, two-, or three-compartment model best fitted the observed data (Paper I), to evaluate the best fitting developed multi-compartment model (Paper I), and to evaluate the best fitting semi-PBPK model (Paper III).

The results were also visually evaluated; fitted or simulated curves that best followed the observed PK profiles were deemed the best. This was ap-plied in Papers I, III and IV.

Finally, the results of model development (Papers III and IV), and agreement between observed and simulated or fitted data sets, or agreement between two simulated data sets, were evaluated with the absolute average fold error (AAFE, eq. 15) and the average fold error (AFE, eq 16).

34

10∑| / |

(15)

10∑ /

(16)

The AAFE can only be 1 or greater than 1 and the accuracy of the simulation gets better the closer to 1 AAFE comes. An AAFE value of one indicates a perfect agreement between data sets while a value of two indicates an aver-age 2-fold difference between evaluated data sets. The AAFE does not indi-cate how the data sets relate to each other, it only indicates a difference. AFE shows the direction of the difference between the data sets, and was used as such.

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Results and discussion

In vivo release of DOX from LIPDOX and DEBDOX An in vivo input rate of DOX from LIPDOX and DEBDOX in human HCC patients was obtained in Paper II, by deconvolution of plasma concentra-tion-time profiles. The in vivo input rate of DOX from LIPDOX and DEB-DOX in pigs was previously studied in NC1.98

Importance of site of measurement or sampling sites The site of measurement, which here is equal to the sampling site, is im-portant when determining the in vivo release rate, or rather the in vivo input rate. As the name suggests, the input rate describes the rate of DOX coming in to the sampling site, while the release rate describes the rate of DOX re-leased from the formulation. For both LIPDOX and DEBDOX, the assump-tion was that the formulation would stay close to the administration site, i.e. passive targeting of the liver tumour.

The input rate and cumulative input of DOX could be lower than the re-lease rate or cumulative release of DOX from the formulations depending on the distance from the site of administration (e.g. pre-tumour) to the site of measurement (e.g. femoral vein), because of distribution of DOX to the tis-sues. This theory was confirmed by the observed decrease (P = 0.0039) in cumulative DOX input from LIPDOX from the local to systemic sampling sites in the pig (Table 3). No significant decrease was observed for cumula-tive input from DEBDOX or in human HCC patients. However, it should be

Table 3. The in vivo cumulative input (%) of DOX from LIPDOX and DEBDOX in HCC patients (Paper II) and pigs (NC1)98 6h after start of administration. Input data were obtained by deconvolution of the observed plasma concentrations.

Sampling site/ site of measurement

Species LIPDOX DEBDOX

Local

Vena hepatica Pig (NC1) 100±44% (n=4) 30±11% (n=4)

Orifice vena hepatica/vena cava HCC patient 60±21% (n=13) 14±5.6% (n=11) Systemic Femoral vein Pig (NC1) 48±29% (n=4) 16±6.5% (n=4)

Femoral vein HCC patient 51±17% (n=13) 12±4.6% (n=11)

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noted that the local sampling sites in pig and human were slightly different. The local sampling site (the hepatic vein) was closer to the administration site for the pig than the sampling site (the orifice of the hepatic vein in the vena cava) for the HCC patients. This means that the human blood sample from the hepatic vein could have been diluted with blood from the vena cava. Accordingly, the local cumulative input from LIPDOX was higher (P = 0.0075) for pigs than for human HCC patients (Table 3). The systemic site of measurement was the femoral vein for both species, and no significant differences in cumulative input were found between these.

The importance of the sampling site was also demonstrated with the por-cine and HCC patient PBBP models (Paper IV). Predictions of in vivo PK profiles were improved when the local rather than systemic cumulative input from pigs was used to simulate release of DOX from LIPDOX and DEB-DOX. However, the peak plasma concentration was still 2-fold underpre-dicted when the in vivo local cumulative input data sets were used, suggest-ing an underprediction of the actual release rate.

These results strongly suggest that the cumulative input into the site of measurement is not similar to the in vivo cumulative release from a formula-tion. The input into the site of measurement will be affected by release from the formulation and disposition of the drug en route to the sampling site. Consequently, the in vivo release from the formulation can be higher, but not lower, than the input to the measuring site.

DOX release from LIPDOX Preferentially, parenteral emulsions are O/W emulsions with an oil-soluble drug dissolved in the oil phase,113, 114 and have a droplet size under 3 µm to prevent oil embolisms.113 The objective with a LIPDOX emulsion is the opposite: temporary embolization is wanted as an effect in addition to the assumed drug delivering properties of the emulsion.

Formulation specifics affecting release The release of DOX from LIPDOX should be controlled and extended, and multiple studies have identified factors which influence this release (in vitro). One important aspect in in vitro studies is the emulsion type, since W/O emulsions result in the extended release of DOX from LIPDOX.40 Pre-liminary solubility studies showed that DOX is practically insoluble in Lip-iodol® (0.006 mg/ml) and slightly soluble in pure water (8 mg/ml) and the contrast agent iohexol (4 mg/ml).57 When formulated as a LIPDOX emul-sion, (preliminary) results showed that only 0.5–6% of the DOX content had partitioned to Lipiodol® within one hour of preparation, which suggests slow partitioning into Lipiodol®.57, 115 Thus, when formulated in a W/O emulsion, DOX first needs to traverse the continuous outer Lipiodol® phase, which is the rate-limiting step.40 When formulated in an O/W emulsion, the DOX is

37

dissolved in the outer phase, and can mix instantaneously with the release media in in vitro release studies.

Generally, the volumes of the two liquids determine the emulsion formed; the liquid with the bigger volume forms the outer or continuous phase.113 This has been observed for LIPDOX emulsions as well. With an aqueous phase consisting of water or contrast agent, prepared with the pumping tech-nique, and without addition of emulsifiers or densifiers, W/O emulsions are formed with aqueous:Lipiodol® ratios of 1:2–4.4524, 86, 88

Another factor affecting extended release from LIPDOX is the stability of the emulsion. In vitro, LIPDOX emulsions have been stabilized with emulsi-fiers (e.g. hydrogenated castor oil) and densifiers (e.g. contrast agent).41, 106,

108 Emulsion stability was also affected by the speed of incorporation of DOX solution into Lipiodol®. A slower incorporation created more stable emulsions.44

In vivo release The in vivo release rate from a LIPDOX emulsion was studied in Paper II. The LIPDOX formulation was composed of 3 mL aqueous phase (0.44 mL sterile water, 2.56 mL iohexol, 50 mg DOX) and 10 mL Lipiodol®, and it was emulsified with the pumping technique. This should, in theory, form a stabilized W/O emulsion. Our in vivo results suggested, however, that release of DOX from this LIPDOX emulsion was not controlled. The input rate of DOX from LIPDOX steadily decreased over time and did not settle at a plateau (Figure 8), as would have been expected with a controlled-release product. The max-imum input rate of DOX from LIPDOX was reached during the administra-tion period. The period of release was slightly extended, as the cumulative

Figure 8. Input rate (mg/min) and cumulative input (% of dose) of doxorubicin from LIPDOX into local and systemic sites of measurement. Data were obtained from deconvoluted hepatocellular carcinoma patients (human, n=11, Paper II) and por-cine (pig, n=4, NC198) plasma data. Data are shown as means.

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input reached a plateau within 1 h for 11 of 13 patients. After 6h, the input rate was negligible. This suggests that the input rate is steered by the admin-istration rate and also slightly by extended release from the formulation. Similar results were observed in the NC1 pig study (Figure 8), although a more gradual decline in input rate was observed.98 Simulations with the PBBP model (Paper IV) confirmed that this LIPDOX emulsion had no or only slightly extended release, as tested data sets of LIPDOX emulsions with extended in vitro release overpredicted the time to reach peak plasma con-centrations. These simulations further suggested that >90% of the loaded DOX dose was released within 0.8 to 2.1 hours after administration. The simulations also suggested that in vitro release methods using a diffusion barrier, such as a dialysis membrane, do not produce in vivo-like release data sets.

The effect of different emulsion specifics on the plasma PK of DOX has been studied in vivo. In rabbits with VX2 carcinomas, lower peak plasma concentrations and plasma exposure were observed for up to 1 day for LIPDOXW/O compared to LIPDOXO/W or a DOX solution, and for a 1:4 (aq:LIP) emulsion compared to a 1:1 emulsion.43, 107, 116 In healthy dogs, a stabilized LIPDOX emulsion had a longer terminal half-life than a non-stabilized emulsion, causing lower peak plasma concentrations but higher 48h plasma exposure.108 In the NC1 pig study, where the same LIPDOX emulsion was used as in the HCC patient study (Paper II), there were no differences in the terminal half-life of DOX from LIPDOX or intravenous infusion.98 Again, this could suggest that the release of DOX from LIPDOX is not or is only slightly extended, as this would have altered the terminal half-life.

One possible reason for the lack of profoundly extended in vivo release of DOX from LIPDOX could be that the emulsion breaks upon contact with the blood stream. In fact, during administration of LIPDOX emulsions to healthy rats, the emulsion appeared as an oil drop containing water drops in the blood stream45 and then, in the sinusoids and upon contact with blood flow, the water droplets were washed away from the oil droplets. In general, the emulsions were distributed and circulated as if Lipiodol® were adminis-tered alone. Furthermore, the stability of a LIPDOX formulation is seldom tested in in vivo-like conditions, e.g. administered into high flows resembling blood flow. Breaking of a W/O emulsion would cause the inner aqueous phase to mix with the blood instantaneously, and no extended release from the aqueous phase would be possible. Only if DOX were dissolved in the Lipiodol® phase would extended release be possible. However, as mentioned above, the amount of DOX diffusing into the Lipiodol® phase is negligible.

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DOX release from DEBDOX

Formulation and method specifics affecting release The in vitro release of DOX from DEBDOX has been extensively investi-gated.43, 51, 52, 98, 101-104, 117, 118 The size of the DCB hydrogels in DEBDOX affects the DOX release: as the diffusion pathway decreases with decreasing bead sizes, the in vitro release rate increases.104 A higher loading of DOX increased the release rate from DCB hydrogels500-700µm, while the release rate was seemingly independent of DOX loading for DCB hydrogels100-300µm.40 DCB hydrogels shrink during loading and swell during DOX release, and the minimum and maximum diameters of larger hydrogels change more.104 This difference in the change of diffusion pathway length could account for the impact of loading on release rate for the larger bead sizes.

The in vitro release method specifics can also influence the release rate. Increasing the ionic strength or the temperature, but not the pH, of the re-lease medium increased the DOX release rate from DEBDOX.51, 101, 102 In-creasing the flow rate of or the rotation speed in the release medium in-creased the release rate, which indicates an effect of hydrodynamics on re-lease.51, 103 Finally, complete DOX release from DEBDOX was only achieved when the release medium was repeatedly replaced,51, 101 or when the release medium consisted of 9% NaCl or a 30:70 water:ethanol mixture containing 20% w/v potassium chloride.102, 103

In vivo release The in vivo release rate of DOX from DEBDOX was studied in Paper II. DEBDOX was composed of DCB loaded with 37.5 mg DOX per mL DCB. All available bead sizes were used in the study: 70–150 µm (M1, 5 patients), 100–300 µm (10 patients), 300–500 µm (4 patients), and 500–700 µm (2 patients) as loaded DEBDOX, and 300–500 µm (2 patients), 500–700 µm (2 patients), and 700–900 µm (1 patient) as unloaded DEBDOX, to achieve complete embolization. Multiple bead sizes were used in most patients. Our in vivo results showed a burst release of DOX from DEBDOX in the deconvoluted human HCC plasma data. This is shown in Figure 9, where the input rate declined after a sharp increase for DEBDOX. A burst release, or the release of an initial bolus of drug before the release rate reaches a stable profile, is not uncommon for controlled-release formulations.118 A burst re-lease from DEBDOX has been observed in vitro from hydrogels loaded with 5 mg, 10 mg or >45 mg DOX/mL DCB, although the percentage was not mentioned.101, 104 Others have not mentioned an in vitro burst release from DCB.51, 52, 102, 117 In the clinical study, a portion of DEBDOX was first mixed with a contrast agent, and then diluted with saline solution prior to admin-istration. Upon mixing with saline solution, ions necessary for the release of DOX become available. It could thus be speculated that a small amount of

40

Figure 9. Input rate (mg/min) and cumulative input (% of dose) of DOX from DEBDOX into local and systemic sites of measurement. Plasma data were obtained from deconvoluted hepatocellular carcinoma patients (n=11, Paper II) and pigs (n=4, NC198). Data are shown as means.

DOX had already been released from DEBDOX before its intra-arterial ad-ministration. However, ions needed for release are also available immediate-ly after administration to blood.

Like the in vitro observations, the in vivo results suggested that the release of DOX from DEBDOX is extended and controlled. The input rate of DOX from DEBDOX reached a plateau after 1.5–2 hours, which was maintained for at least 14 hours (Figure 9). Cumulative input did not reach a plateau at the systemic sampling site; it increased from 12% at 6h to 15% at 24h. These results were again a good match with the NC1 pig data.98 The peak input rate occurred later in the clinical study than in the porcine study, which could simply be explained by the longer administration times in humans (mean 13 min) compared to pigs (~2 min). The simulations with the PBBP model (Pa-per IV) confirmed the incomplete release of DOX from DEBDOX over 6h (NC1 pig study) and 24h (human study). The simulations suggested release of ~32% of the loaded DOX after 6h.

The in vivo cumulative input and the simulations are in good agreement with the incomplete release of DOX from DEBDOX, which has been ob-served over up to 90 days in porcine and human tissue samples.119, 120 One reason for this incomplete release could be the formation of DEBDOX ag-gregates, which have been observed in the arteries.119-122 These aggregates or clusters containing more hydrogels result in an increased percentage of the loaded dose (~42%) being left in the formulation after 80 days.119 It was speculated that this happens because of a saturated drug environment.119 Another explanation might be the longer diffusion pathway in larger aggre-gates for both DOX and the counter ion needed for drug release. A third explanation could be that fibrotic tissue forms around DEBDOX. This phe-

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nomenon, which resembles a fibrotic encapsulation or “foreign body reac-tion”, has been observed in humans122 and can occur within three weeks,123 possibly severely reducing the release of DOX to the surrounding tissues.

Effect of Lipiodol® on DOX and DOXol disposition In NC2 (Paper I), the administration of Lipiodol® to pigs via the portal vein did not affect the disposition of DOX administered via the ear vein. DOX and DOXol concentration-time curves and biliary and urinary excretion were not altered by the administration of Lipiodol®. Tissue concentrations of DOX and DOXol were not altered by administration of Lipiodol® (Paper ii).80 For visual confirmation, see the section headed “Variability in PK of DOX in pig and human”, Figure 13. These results suggest that Lipiodol® does not alter the uptake, metabolism or excretion of DOX or DOXol in healthy pigs when it is administered separately from DOX.

In the NC1 pig study98, Lipiodol® and DOX were administered as LIPDOX. The administration of LIPDOX did not significantly alter the bili-ary excretion, plasma clearance and terminal half-life compared to an intra-venous infusion of DOX alone. These results, combined with the results from Paper I, suggest that Lipiodol® does not alter the disposition of DOX or DOXol in healthy pigs. Both studies were acute studies, where samples were collected over 6h. The half-life of DOX has a reported half-life of 14–50 h66, and later effects of Lipiodol® on DOX or DOXol disposition could thus not be observed.

Interestingly, in vitro experiments and clinical studies have shown that Lipiodol® can affect DOX disposition. Uptake of DOX into liver cancer cells was enhanced in the presence of Lipiodol®.124, 125 It has been suggested that DOX is taken up together with Lipiodol® by pinocytosis into the cell, in-creasing the intracellular DOX concentrations. Intra-arterial administration of LIPDOX (without additional embolization) compared to DOX alone low-ered the DOX peak plasma concentration and 1h exposure, but not the total exposure or terminal half-life.41, 112, 126 DOX tumour concentrations were increased compared with the surrounding liver tissue after intra-hepatic LIPDOX administration to VX2 rabbits and patients with HCC.41, 126, 127 However, the intra-tumour distribution of DOX does not correlate with the intra-tumour distribution of Lipiodol®.128, 129

In all, it appears that Lipiodol® alone does not affect any of the disposi-tion processes of DOX or DOXol in healthy pigs. When DOX is emulsified with Lipiodol®, however, it is possible that DOX is taken up with Lipiodol® into the cells, increasing the intra-tumoral concentrations.41, 126, 127

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Effect of CsA on DOX and DOXol disposition The effect of CsA on the disposition of DOX and DOXol was examined as a control for the possible effect of Lipiodol® in Paper I (NC2). As was dis-cussed in the previous section, Lipiodol® did not have an effect on the PK profiles of DOX and DOXol. Therefore, treatment groups TI and TII were combined into one group (–CsA, n=6) as were groups TIII and TIV (+CsA, n=6).

DOX plasma concentrations were not significantly altered by administra-tion of CsA (Figure 10). However, biliary and urinary excretion of DOX were significantly decreased after treatment with CsA (Figure 11). We con-clude that CsA inhibits the canalicular located efflux transporters of DOX (P-gp, BCRP, BSEP, and/or MRP2),58-61 which is in agreement with previ-ous studies.130-133 The decrease in urinary excretion of DOX after addition of CsA may be explained by the inhibition of renal tubular efflux mediated by P-gp and/or MRP2.74 CsA is also an inhibitor of the OATP1A2 transporter, and has the potential to affect DOX plasma concentrations by decreasing hepatic uptake. This was not observed in Paper I, probably because of the short sampling time. Several studies with longer sampling periods (>24h) have shown increased DOX plasma concentrations when CsA is co-admini-

Figure 10. Porcine plasma concentration-time curves for DOX and DOXol during the 6h study. All pigs received DOX at 0–5 min (reference phase; 0-160 min) and 200–205 min (test phase; 200-360 min). Of these, 6 pigs also received cyclosporine A (+ CsA) at 160-180 minutes. Peak plasma concentrations (Cmax) and exposure (AUC) during the test phase are shown in the table. The grey area and the asterisk (*) in the graph depict the time points where the plasma concentration significantly differed (P < 0.05) between the two treatment groups.

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stered,130, 134 while studies with short sampling times (<4h) did not observe an effect on plasma concentration.130-133

For DOXol, both peak plasma concentrations and plasma exposure were significantly increased when CsA was administered (Figure 10). Biliary ex-cretion of DOXol was significantly decreased after treatment with CsA (Fig-ure 11). Our results support previous suggestions that DOXol is transported by P-gp, as its biliary excretion is inhibited by CsA.130-132 We further suggest that DOXol may be transported by the same carrier-mediated uptake and efflux mechanisms as DOX, as CsA inhibited the biliary excretion of both DOX and DOXol to the same extent. The inhibition of biliary excretion of DOX would probably lead to higher intracellular availability of DOX for metabolism to DOXol. The combination of increased DOXol formation and decreased excretion to bile could cause a redistribution of DOXol to plasma. This theory is supported by the observed increased DOXol plasma concen-trations.

The observed plasma and biliary PK profiles were replicated with the multi-compartment model (Paper I) by inhibiting biliary excretion of DOX and DOXol by 99%, thus confirming the above suggestions. The effect of CsA on DOX distribution was also evaluated with the binding-specific semi-PBPK model (Paper III). DOX and DOXol PK profiles were adequately predicted, with a 90% decrease in biliary excretion (AAFE < 2). This further supported the above conclusion that CsA inhibits the biliary excretion of these substances.

Figure 11. The fraction of doxorubicin (DOX) and doxorubicinol (DOXol) excreted to bile (0–3 and 3–6 h) and urine (0–6 h) in pigs is shown with box-and-whisker plots on a logarithmic scale, showing min-max and median. All pigs received DOX at 0–5 and 200–205 min. Of these, 6 pigs also received cyclosporine A (CsA: +) at 160–180 minutes. Closed circles show individuals not receiving Lipiodol® treat-ment, and open circles show individuals receiving additional Lipiodol® treatment at 190–195 minutes. The asterisk (*) indicates a significant difference (P < 0.05) be-tween the two treatment groups.

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Description of DOX tissue binding in PBPK modelling In Paper III we concluded that the disposition of DOX and DOXol could only be described by a PBPK model when there was a possibility of tissue retention.

Effect of Kp,T on DOX disposition In the generic semi-PBPK model, tissue distribution to non-eliminating, non-metabolizing tissues was described using the traditional Kp,T. A Kp,T > 1 indi-cates distribution of the compound to the investigated tissue. The proper definition of Kp,T is the total tissue-plasma concentration ratio at equilibri-um.135 However, in PBPK models, Kp,T is used to describe the distribution ratio both at equilibrium and when equilibrium is not present. Several meth-ods of calculating Kp,T for a substance have been devised.136 Kp,T prediction methods have included using the octanol:water partitioning coefficient; the vegetable oil:water partitioning coefficient; the solubility of the substance in the lipid, phospholipid and water content of tissues; and the in vivo-based volume of distribution and in vivo partitioning coefficients.136

The possibility of using the predicted Kp,T for non-eliminating, non-metabolizing tissue was evaluated during the early development of the ge-neric semi-PBPK model in Paper III. In vivo and in vitro partitioning coef-ficients (either taken directly from or calculated using plasma/tissue data) from multiple species at multiple time points were collected,77, 78, 80, 81, 98, 137,

138 and were used as input in the generic semi-PBPK model. All the Kp,T values underpredicted the peak plasma concentration 4- to 100-fold. This indicated that the used Kp,T overpredicted the tissue distribution during the distribution phase. Kp,T calculated using lipid and water content in tissues139 also poorly predicted the observed DOX plasma concentrations in NC2. Interestingly, the authors of this in silico prediction method concluded that the predicted Kp,T values for DOX under-predicted the observed Kp,T values.139 Even when the Kp,T values were estimated by curve-fitting the generic model to the observed data, the fit of DOX plasma concentration-time profiles was poor.

The metabolizing, eliminating tissues (kidney, liver) were not described as perfusion-limited compartments, but as permeability-limited tissues. In-stead of using Kp,T to describe the disposition to these tissues, clearance over vascular and cellular membranes and the fraction of unbound drug were used to increase the tissue concentration. Decreasing the fraction of unbound drug from 0.1 to 0.01 improved the simulated concentrations in these tissues greatly. This, however, worsened the curve fittings to the observed DOX and DOXol plasma concentration-time profiles and urinary excretion.

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Effect of intracellular binding sites on DOX disposition To improve the description of the DOX and DOXol disposition by the PBPK model, an intracellular binding site was included in each tissue compartment (Figure 7). The drug distribution to the intracellular binding sites was de-scribed by association and dissociation binding clearances, which were iden-tical in all tissues. Kp,T was accordingly set to 1 for all non-metabolizing and non-eliminating tissues. There is no indication that facilitated cell membrane translocation of DOX and DOXol is important in these tissues.

The addition of the intracellular binding sites improved the overall curve fitting. Descriptions of DOX plasma concentration-time profiles and biliary excretion and liver and kidney concentrations were improved, as were the DOX biliary excretion and kidney concentrations. The intracellular binding sites represented all intracellular binding for DOX and DOXol, e.g. DNA and cardiolipin.82-85 These results agree well with results from a previously published PBPK model incorporating specific binding of DOX to DNA and cardiolipin.79 This model was able to predict concentration-time profiles in several tissues and plasma from mouse, dog and human.

The estimated association clearance was larger than the dissociation clearance for both DOX and DOXol. This indicates prolonged tissue bind-ing, and thus prolonged residence time in the tissue,140, 141 which is in good agreement with studies showing high tissue concentrations or high Kp,T val-ues.77-81 The prolonged residence time could well be explained by the bind-ing of DOX to DNA, which is in good agreement with the reported anti-tumour mechanisms.54

Similarity in human and porcine doxorubicin disposition Throughout this thesis, the pig has been used as a model for the human HCC patient. The healthy porcine liver is macroscopically different from the healthy human liver, in that it has three lobes instead of two.142 However, and more importantly, the segmental anatomy, vascularity, and biliary tree of the livers are similar.142 The healthy pig and human gut physiology is also similar.143 Most porcine and human transporters and metabolizing enzymes are closely related and located similarly. For example, activity and expres-sion levels of CYP isoforms are similar in humans and mini pigs.144 OATP1A2 is closely related in pigs and humans and is located in the liver in both species.145-147 P-gp and MRP2 are highly expressed in the livers of hu-mans and pigs.74, 146 Both CBR1 and AKR1C3 have been detected in humans and pigs.87, 146 All this indicates that the pig is an appropriate model for in-vestigations of DOX and DOXol disposition after administration of LIPDOX and DEBDOX. However, one important difference is the liver status of the two species: human HCC patients have impaired liver function while pigs

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have healthy livers. Another difference is age: the studied pigs were young adults (around 12 weeks), while human HCC patients were more senior (>50 years).

The dose- and weight-corrected plasma concentration-time data from hu-mans and pigs treated with LIPDOX and DEBDOX are shown in Figure 12. The data show that the DOX plasma concentrations decreased faster in hu-mans than in pigs. The DOXol plasma concentrations increased more slowly in humans than in pigs. The formation of DOXol still exceeded its elimina-tion after 6h in humans, but had already turned after 2 h in pigs. In Paper IV, the binding-specific semi-PBPK model was translated from the healthy pig to the healthy human. When simulating intravenous DOX infu-sions to humans with healthy livers, the observed DOX plasma curves were well described by the model (AAFE < 1.6). This suggests that the pig is a good model for PK studies of DOX, as the only alteration to the model was to change physiological parameters from porcine to human where appropri-ate. However, the DOXol plasma concentrations were underpredicted in

Figure 12. Dose- and weight-corrected (1 mg, 1 kg) plasma concentration-time profiles after administration of LIPDOX (a, b) or DEBDOX (c, d) to healthy pigs (NC1)98 and human HCC patients (Paper II). (a, c) Doxorubicin PK (left-hand graphs) and (b, d) doxorubicinol PK (right-hand graphs).

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HCC patients. It is likely that there were uncertainties in the estimated pa-rameter values for DOXol. The observed PK data set (Paper I and Paper ii) was less comprehensive for DOXol than for DOX; DOXol concentrations were only measurable in kidney tissue, not in liver, heart and intestine. Therefore, association and dissociation binding clearances for DOXol were more variable than those for DOX.

Effect of liver cirrhosis on DOX disposition The binding-specific semi-PBPK model was further developed from a pig PBPK model to a human PBPK, a human cirrhosis PBPK and finally a hu-man HCC PBBK model in Paper IV. The effects of chronic liver dis-ease/cirrhosis on DOX disposition could thus be examined with the model.

Simulations from this PBBP model suggested that the PK of DOX does not change with changed liver status. Liver extraction of DOX has been re-ported as 0.05 to 0.5 during intrahepatic infusion and 0.03 to 0.105 after intravenous injection.148, 149 DOX is thus classified as a low to intermediate hepatic extraction drug. In a well-stirred model, total clearance of DOX would largely be determined by plasma protein binding and intrinsic clear-ance via the main elimination route. In our PBBP model, intrinsic clearance was described intracellularly by metabolism and excretion into bile. To ad-here to the reported changes in liver function in a cirrhotic liver,74, 99 meta-bolic and excretory clearances were decreased. As plasma albumin and α1-acid glycoprotein decrease with increasing levels of cirrhosis,99, 100 the frac-tion of unbound DOX was calculated to increase. Interestingly, the model simulations suggested that the effects of decreased intrinsic clearance and increased fraction of unbound DOX with increasing liver impair-ment/cirrhosis cancelled each other out for the total clearance of DOX. This explains the lack of effect of cirrhosis on DOX plasma concentration-time profiles.

Literature reviews have found contradictory results regarding the effect of chronic liver disease/cirrhosis/primary hepatic malignancies on the PK of DOX.150, 151 In short, multiple studies have found increased DOX plasma exposure and an increased half-life in patients with impaired liver function, e.g. hyperbilirubinaemia,112, 152-155 while others have not been able to confirm these results.156-158 It has been suggested that liver cirrhosis or impaired liver function might alter DOX PK, but that primary liver tumours will not affect DOX PK.159 Unfortunately, none of these studies classify liver impairment with CP classes, making a more specific comparison with our results diffi-cult.

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Variability in DOX PK in pig and human Variabilities in the disposition of DOX and DOXol in the pig were noticed when the binding-specific PBPK model was used to simulate the observed intravenous data from NC198 using parameter estimates from NC2 (Paper III). When simulating NC1 data, prediction of DOX plasma concentrations was acceptable. DOX 3h plasma exposure and clearance were similar in the studies: mean AUC 0.44 (NC1) vs 0.6 µM*min (NC2), and mean clearance 59 (NC1) vs 48 ml/min/kg (NC2) (Figure 13a).160 However, DOXol plasma concentrations from NC1 were 4.5- to 6.8-fold overpredicted when NC2 parameter values were used and a 10-fold lower DOXol plasma exposure was observed in NC1 compared to NC2 data.160 The fraction excreted to bile was two-fold higher for DOX and DOXol in NC1 than in NC2. From Figure 13 it is clear that the pigs in the two studies had different DOX and DOXol dispositions. In three pigs in NC1 the disposition of DOX and DOXol dif-fered from that in the pigs in NC2, while one behaved more like the NC2 group of pigs.

In general, there was wide interindividual variability in DOX and DOXol disposition in these studies. At any given time point, the plasma concentra-tions between pigs within each study could vary as much as 4.5-fold for DOX and up to 10-fold for DOXol. The fraction excreted to bile could vary 3.5-fold for both DOX and DOXol. Wide interindividual variation has also been observed in humans.69, 161 Plasma exposure and terminal rate constants varied at least 3-fold in cancer patients (no involvement of the liver).69 An-other study reported a coefficient of variation (CV%) of over 38% for plas-ma exposure, elimination rate constant and clearance in cancer patients (no involvement of the liver).161 The pigs included in the NC198 and NC2 studies were male and of a mixed race (Yorkshire and Swedish landrace). They were not genetically identical, as is usual for rats and mice used in research, for example. However, in this respect, the pigs resembled the human population. One reason behind the wide variability could be genetics. Different poly-morphisms exist for the OATP1A2, MRP2, MRP3, P-gp and BCRP drug transporters.162 Polymorphisms of P-gp, but not BCRP, affect the PK of DOX.163 MRP1 and MRP2 polymorphisms have been associated with an increased risk of anthracycline-induced cardiotoxicity.164 It could be specu-lated that the polymorphisms of the other transporters could also affect the DOX PK. Polymorphisms for the aldo-keto reductases and carbonyl reduc-tases have also been reported.165, 166 Polymorphisms of AKR1C3 and CBR1, but not CBR3, have been shown to have an effect on the PK of DOX.167, 168 Most of these polymorphisms were identified in humans. However, consid-ering the similarities between the two species, one could assume that similar polymorphisms are present in pigs.

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Figure 13. Dose (50 mg)- and weight (27 kg)-corrected plasma exposure (A, B), biliary excretion (C, D), fraction excreted to bile and urine after 6h (E), and tissue concentrations (F) for doxorubicin (DOX) (A, C, E, F) and doxorubicinol (DOXol) (B, D, E, F). Individual data are shown for non-clinical study 1 (NC1, n=4)98 and study 2 (NC2, n=6, Paper I and Paper ii). DOX was administered to the right ear vein in pigs over 50 min (NC1) or 5 min, twice (NC2, at 0 and 200 min). Individuals TII04, TII05, TII06 received 6 mL Lipiodol® at 190-195 min.

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Consequently, the variations between the individual pigs in the NC1 study98 could be the result of variations in excretion caused by transporter or metabolizing enzyme polymorphisms. The binding-specific semi-PBPK model was curve-fitted to the NC1 data set by estimating hepatic excretion, the scaling factor for metabolism, and cell membrane clearance (Paper III). This resulted in a good fit to the observed data. The results suggested that the hepatic excretion rate of DOX was increased 2-fold in the three pigs that had lower DOXol plasma curves and higher DOX biliary excretion. Interesting-ly, the estimated metabolism did not differ between the different pigs. The variability between NC1 and NC2 in the hepatic excretion parameter estima-tions for both DOX and DOXol seems to suggest that the biliary variability in excretory transporters is more important than the variability in metaboliz-ing enzymes.

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Conclusions

In this thesis, the pharmacokinetic profiles of DOX and DOXol were inves-tigated in vivo. The release of DOX from the clinically used formulations LIPDOX and DEBDOX and the effect of Lipiodol® and CsA on the disposi-tion of DOX and DOXol were studied. PBPK and PBBP models were devel-oped to provide a better understanding of these processes.

Specifically: The in vivo release of DOX from LIPDOX did not reach a steady release

rate and was not or was only slightly extended (Papers II and IV). The in vivo release of DOX from DEBDOX reached a steady release rate

after 2 h, which was continued for at least 14 h (Papers II and IV). DOX was released from LIPDOX and DEBDOX as a burst in the early

phase of administration (Papers II and IV). The choice of sampling site/site of measurement is of importance when

determining in vivo release rate (Papers II and IV). Lipiodol® by itself did not affect the hepatobiliary disposition of DOX or

DOXol in healthy pigs (Paper I and Paper ii). CsA (a positive control for Lipiodol®) seemed not to affect the metabo-

lism of DOX, but inhibited the excretion of DOX and DOXol to bile in the healthy pig (Papers I, III, Paper ii).

The prolonged tissue binding of DOX was only established when intra-cellular binding sites were added to the semi-PBPK model describing the PK of DOX and DOXol (Paper III).

There was good agreement between healthy porcine and human disposi-tion data for DOX, as shown by the ease of translation of the semi-PBPK pig model to the human PBBP model (Paper IV).

In vivo release of DOX from LIPDOX and DEBDOX was described using the human HCC PBBP model using in vitro release profiles as in-put (Paper IV).

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Populärvetenskaplig sammanfattning

Primär levercancer, eller hepatocellulärt carinom (HCC), är en elakartad tumör i levern. Globalt insjuknar årligen ca 780 000 människor i HCC och 745 000 avlider i sjukdomen. Det gör HCC till den näst dödligaste cancer-formen globalt. I Norra Europa är det årliga insjukningstalen 6 500 och 6 300 avlider. Fler män än kvinnor drabbas och HCC är vanligare i utveckl-ingsländer. Den maligna levertumören uppstår oftast i en redan sjuk lever, till exempel cirrotiskt lever eller skrumplever. Sjukdomsförloppet kan delas in i fem stadier; intermediär HCC är ett av dessa stadier.

Standardbehandlingen av intermediär HCC är chemo-embolisering. Denna behandlingsmetod saktar ner sjukdomsförloppet, men stoppar det inte. I chemo-embolisering injiceras en läkemedelsformulering* i leverartär-en nära tumören. Leverartären är ett blodkärl som förser tumören och resten av levern med syrerikt blod. Två olika typer av formuleringar vid chemo-embolisering används för närvarande. Den första formuleringen kallas för LIPDOX i denna avhandling. I LIPDOX är vatten och olja blandad till en emulsion (som en salladsdressing). Vattnet innehåller läkemedlet doxoru-bicin, ett cellgift som dödar tumörcellerna. Oljan består av Lipiodol, som efter injicering kan ses på röntgen. Den andra formuleringen kallas för DEBDOX i avhandlingen. I denna formulering finns doxorubicin i mycket små gel-partiklar. Både LIPDOX och DEBDOX ökar överlevnadstiden från 16 till ungefär 18-19 månader. Att effekten på överlevnadstid är samma för båda formuleringarna är intressant för en farmaceut, eftersom dessa formule-ringar har mycket olika egenskaper.

I avhandlingen har det undersökts vad som händer med läkemedlet doxorubicin i kroppen efter injicering av LIPDOX eller DEBDOX. Doxoru-bicin frisätts nämligen från formuleringarna och fördelar sig i kroppens or-gan och vävnader. Därefter kan doxorubicin utsöndras från kroppen med urinen och via galla till avföring. Doxorubicin kan även brytas ner i kroppen till sin nedbrytningsprodukt doxorubicinol. Doxorubicinol har en svagare effekt än doxorubicin. Hur mycket doxorubicin som frisätts från formule-ringen och med vilken hastighet frisättningen sker är beroende av formule-ringens egenskaper och kroppens fysiologi. Ett av målen med båda formule-ringarna är att långsamt frisätta doxorubicin nära tumören. Ett annat är att täppa till blodkärl nära tumören, vilket stoppar blodflödet och gör att doxorubicin inte kan spolas bort från tumören. I teorin gör den långsamma frisättningen tillsammans med det stoppade blodflödet att tumören blir utsatt

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för höga halter av doxorubicin under en längre period. Det borde då öka doxorubicinets effekt på tumören.

Vi har undersökt frisättingen av doxorubicin från båda formuleringarna, LIPDOX och DEBDOX, i patienter med HCC. Våra resultat visar att frisätt-ningen av doxorubicin från LIPDOX är snabb och inom 1-2 timmar har allt doxorubicin frisatts från formuleringen och spridit sig i kroppen. Eftersom doxorubicin har en snabb spridning i kroppen samt bryts ner och utsöndras hastigt blir halten doxorubicin i blodet snabbt låg. Därmed utsätts tumören för en lägre mängd doxorubicin än vad som önskas. Med DEBDOX ser vi ett annat mönster. Det är en långsam frisättning. Efter ett dygn har bara 15 % av doxorubicinet frisatts från formuleringen. Frågan är dock om allt doxoru-bicin verkligen kan frisättas från DEBDOX.

Med all information vi samlat in kunde vi programmera så kallade farmako-kinetiska datormodeller, som beskriver allt som händer med doxorubicin i krop-pen. Dessa datormodeller kombinerades med information om hur doxorubicin frisätts från formuleringarna in vitro (d.v.s. i provrör) som gjorts av andra fors-kare. När in vitro-resultaten kombinerades med modellerna kunde vi således simulera vilka halter doxorubicin HCC-patienter hade i blodet. Simuleringarna bekräftade resultaten som visades i studien med HCC-patienterna. Simuleringar från våra farmakokinetiska modeller visar även att grisen är en bra försöksmo-dell för vad som händer i människor. Genom att ändra fysiologiska värden (som organvikt) från gris till människa i modellen kunde doxorubicinhalten i blodet hos människor med frisk lever förutses. Våra simuleringar visar även att skrumplever inte påverkar doxorubicinets fördelning och nedbrytning i kroppen.

Man vet att vissa substanser kan ha effekt på vävnadsfördelning, nedbrytning eller utsöndring av doxorubicin. I vår forskning undersökte vi huruvida oljan i LIPDOX, Lipiodol, har en sådan effekt i friska grisar. Det visades sig att Li-piodol inte ändrade någon av doxorubicinets tidigare nämnda processer i friska grisar. Vi testade även läkemedlet ciklosporin, där det har visats tidigare att den blockerar proteiner som har som roll att utsöndra främmande ämnen ur kroppen. Vi visade att ciklosporin minskade doxorubicinets utsöndring till galla och urin i friska grisar. Eftersom utsöndringen av doxorubicin minskade bildades mer DOXol, vilket ökade dess halt i blodet.

Sammanfattningsvis har avhandlingen bidragit till ökad kunskap om hur doxorubicin frisätts från två formuleringar efter att dessa har injicerats nära en levertumör. Kombinationen av försök i friska grisar och människor med HCC i kombination med farmakokinetiska matematiska modeller ger tyngd åt våra slutsatser.

________________________________________ *Formulering: en produkt som består av ett läkemedel och hjälpämnen. En tablett är ett ex-empel på en formulering. Hjälpämnen i tabletten gör till exempel att tabletten kan behålla sin form utan att falla sönder. Hjälpämnen kan även exempelvis förhindra att tabletten löses upp i magsäcken, utan först när den nått fram till tunntarmen.

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Populairwetenschappelijke samenvatting

Primaire leverkanker wordt ook wel hepatocellulair carcinoom (HCC) genoemd en is een kwaadaardige tumor die in de lever ontstaat. Jaarlijks worden er wereldwijd ongeveer 782.000 mensen met deze ziekte gediagnostiseerd en overlijden er 745.000 mensen aan de ziekte. Dit maakt HCC de op een na dodelijkste kankervorm. In West Europa werden er in 2012 ongeveer 20.500 mensen gediagnostiseerd en overleden er 18.900 personen aan HCC. Deze cijfers zijn hoger in ontwikkelingslanden en voor mannen. Deze kwaadaardige tumor ontwikkelt zich voornamelijk in een chronisch ontstoken lever, waarin littekenvorming is ontstaan, dit wordt ook wel een cirrotische lever genoemd. Het verloop van HCC kan in verschillende stadia worden ingedeeld, waarvan intermediaire HCC er één is.

Intermediaire HCC kan behandeld worden met chemo-embolisatie. Deze behandelingsmethode vertraagt de voortgang van de ziekte, maar geneest niet. Bij chemo-embolisatie worden twee verschillende soorten preparaten gebruikt. Het ene preparaat wordt LIPDOX genoemd. Dit is een emulsie waarin een waterdeel en een oliedeel gemengd zijn (net zoals in een saladedressing). In het waterdeel is een cytostatisch geneesmiddel opgelost, in dit geval doxorubicine. Het oliedeel bestaat uit de olie Lipiodol. Lipiodol is zichtbaar op röntgen en zorgt ervoor dat de arts kan zien waar LIPDOX zich bevindt. Het andere preparaat wordt DEBDOX genoemd. Dit preparaat bestaat uit erg kleine gel deeltjes waar wederom het geneesmiddel doxorubicine in zit. Tijdens de behandeling wordt het preparaat in de leverslagader geïnjecteerd. De leverslagader voorziet de lever en dus ook de tumor van bloed, op deze manier komen LIPDOX en DEBDOX dus direct bij de tumor aan. Beide preparaten geven een vergelijkbare verlenging van de levensduur: van 16 maanden tot 18-19 maanden. Voor een farmaceut is dit interessant, aangezien de twee preparaten erg verschillende eigenschappen hebben.

In dit promotietraject hebben we onderzocht wat er met het geneesmiddel doxorubicine gebeurd vanaf het moment dat LIPDOX of DEBDOX in de leverslagader geïnjecteerd zijn. Doxorubicine komt namelijk vrij uit het preparaat en verdeelt zich daarna over de tumor en de rest het lichaam. Doxorubicine kan daarna uitgescheiden worden via de gal, en vervolgens de ontlasting, of via de urine. Doxorubicine kan ook afgebroken worden in de metaboliet doxorubicinol. Doxorubicinol heeft een minder sterk effect in vergelijking met doxorubicine. De snelheid en de volledigheid waarmee

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doxorubicine uit de preparaten vrijkomt wordt mede bepaald door eigenschappen van het preparaat, maar ook door de fysiologie van het lichaam. Het eerste doel van deze preparaten is om doxorubicine langzaam vrij te laten komen in en om de tumor. Het tweede doel is om een afsluiting van het bloedvat bij de tumor te veroorzaken, waardoor doxorubicine niet met het bloed weggespoeld kan worden. Deze twee doelen zouden er in theorie voor moeten zorgen dat de tumor gedurende een langere periode aan hoge concentraties doxorubicine blootgesteld wordt, wat de cytotoxische werking van doxorubicine zou kunnen verbeteren.

Onze resultaten in patiënten met HCC wijzen erop dat doxorubicine snel uit LIPDOX vrij komt: binnen 1-2 uur is alle doxorubicine vrijgekomen in het lichaam. Door de snelle verdeling van doxorubicine naar andere weefsels, en de eliminatie van doxorubicine via de gal en urine dalen de concentraties in het bloed snel en krijgt de tumor een lagere dosis doxorubicine. Met DEBDOX zien we een ander patroon: doxorubicine komt langzaam vrij uit dit preparaat. Doxorubicine er komt zelfs zo langzaam uit, dat het niet zeker is of alle doxorubicine ooit vrij zal komen. Na één dag is er namelijk nog maar 15% afgegeven. Met de verzamelde gegevens konden er zogenaamde farmacokinetische modellen op de computer gemaakt worden die de doxorubicine concentraties in het bloed konden simuleren. Het vrijkomen van doxorubicine uit deze preparaten is verder ook in vitro (in reageerbuis) door andere onderzoekers getest. Door de modellen met de in vitro resultaten te combineren, konden we de conclusies van de humane studies bevestigen. De simulaties met de farmacokinetische modellen duiden er verder op dat het gezonde varken een goed experimenteel model voor de mens is. Door fysiologische waarden (zoals orgaan gewicht) van varkens naar menselijke waardes te veranderen, konden doxorubicine concentraties in het bloed van mensen zonder leverkanker worden voorspeld.

Verschillende stoffen kunnen de verdeling in of eliminatie van doxorubicine uit het lichaam veranderen. We hebben onderzocht of Lipiodol een dergelijke werking heeft in gezonde varkens. Onze conclusie was dat Lipiodol niet de verdeling of eliminatie van doxorubicine uit het lichaam van gezonde varkens verandert. We testten ook de stof ciclosporine, waar het wetenschappelijk van aangetoond is dat het de eliminatie naar de gal en urine van doxorubicine wordt verminderd. Onze resultaten bevestigden dat dit ook het geval is gezonde varkens. Door de verminderde eliminatie van doxorubicin, wordt er extra doxorubicine omgezet naar de metaboliet doxorubicinol. Hierdoor stegen de concentraties van doxorubicinol in het bloed.

In conclusie heeft dit proefschrift bijgedragen tot het vergroten van de kennis over hoe doxorubicine uit deze twee preparaten vrijkomt, nadat ze dicht bij de tumor geïnjecteerd zijn. De combinatie van testen in gezonde varkens, HCC patiënten en modellen sterken onze conclusies.

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Acknowledgements

The work presented in this thesis was carried out at the Department of Phar-macy, Faculty of Pharmacy, Uppsala University, Sweden. I would like to express my gratitude to Apotekare C D Carlssons stiftelse (Apotekarsociete-ten), IFs stiftelse (Apotekarsocieteten), Anna Maria Lundins Stipendienämnd (Smålands Nation) for the grants which allowed me to attend scientific meet-ings. This work would not have been possible without the help of my supervisor Hans Lennernäs and co-supervisor Erik Sjögren. Thank you Hans for ac-cepting a strong-headed person as a PhD student and for all the freedom I have been given in this project. Many thanks also for the help during the final stages of the project. And I think it was great that a cytostatic-lab was built in our lab so we could work safely with these mean substances. Thank you, Erik, for all the discussions on the project, (mostly) regarding model-ling. It has been inspiring to have somebody around who shares the enthusi-asm of an “acceptably” predicted curve. I would like to thank all our collaborators for fruitful collaborations. Every-body from Uppsala University Hospital and Karolinska University Hospital, in no particular order: Charlotte Ebeling Barbier, Agneta Norén, Frans Du-raj, Rickard Nyman, Amar Karalli, Rimma Axelsson, Torkel Brismar, Per Stål, Pia Loqvist. Without you the clinical trial could not have been started, let alone have been finished. Everybody from SVA for the professional analysis of our samples: Mikael Hedeland, Ulf Bondesson, Elisabeth Fred-riksson. And finally Anders Nordgren for the expert handling during the animal experiment. Thank you for all the hard work which has made this thesis a reality. My gratitude and appreciation go out to all who have been around me during my PhD period: The people in the Biopharmacy group, former and current. Especially Elsa and Emelie, without you this project would definitely not have come this far! The discussions about our work in the project and anything between heaven and earth has been much appreciated. Also walks, very good.

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The PhD students, post-docs and other employees, former and current, at the Department of Pharmacy. Thank you for all the walks, talks, laughs, and sometimes seriousness combined with all the help I have gotten. It was great to always have somebody to share a fika or lunch with. BTW, André and Anna, I still miss you at the department. One of the downsides of working in academia is the loss of great people moving forward to better positions. Rebecka, Erik M, Annelie, Caroline, for making it such a great experience to organize the Young Scientist Satellite Conference and attend the PSWC conference, and for almost making it difficult to finish this thesis because of all the super interesting (no irony here! Or was it?) messages. The “anti-stress group”! Doing a PhD is not always a walk in the park, and our fikas were sorely needed at times. All the other random people I have gathered around me during the years, again in no particular order: Henrik for being my guide to Sweden, Swedish language, people and traditions and anything else Swedish. Emma for the great time we had during and after the master thesis projects. Cynthia, Susan, Marjolijn, for the link to the dutch pharmacy, although none of you work in a traditional pharmacy. And for keeping in touch with me. Maartje, although I tend to avoid them like the plague, it is great having a fellow Dutchie in Sweden! Guido for your adventures and experiences. Kitty, sorry that I have moved so far away! Also everybody from Bamm 2017 #nobang (som kon-stig nog ändå blev en bang….. Oväntat). Febe, Stig, Tova, Sebastian och Charlie. Ni är alltid positiva och glada. Det finns en livslust i er som inte verkar kunna ta slut! En natuurlijk wil ik mijn eigen familie bedanken. Mama, de sterkste persoon in de hele wereld. Nobody can ever fill your shoes. Zonder jouw steun was ik nooit gekomen waar ik nu ben. Ik neem m’n petje voor je af. Kristiaan, Eva, Tjakka, Daisy, Inge, Klaas Jan, Joost, Bert en Rianne: wat een ongein en geneuzel. Tot de volgende keer maar weer! Mijn eigen kleine gezinnetje, luff jullie ♥ En toen kwam er een olifant met een hele lange snuit en die blies het hele verhaaltje uit

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Acta Universitatis UpsaliensisDigital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Pharmacy 240

Editor: The Dean of the Faculty of Pharmacy

A doctoral dissertation from the Faculty of Pharmacy, UppsalaUniversity, is usually a summary of a number of papers. A fewcopies of the complete dissertation are kept at major Swedishresearch libraries, while the summary alone is distributedinternationally through the series Digital ComprehensiveSummaries of Uppsala Dissertations from the Faculty ofPharmacy. (Prior to January, 2005, the series was publishedunder the title “Comprehensive Summaries of UppsalaDissertations from the Faculty of Pharmacy”.)

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