Redefining Disease, New Molecular Definitions and Personalised

Medicine

Dr Harsukh ParmarGlobal Discovery Medicine

Respiratory & Inflammation Therapy Areaharsukh.parmar@astrazeneca.com

U.S. Drug Industry R&D Expenditures and Drug Approvals, 1963-2000

U.S. Drug Industry R&D Expenditures and Drug Approvals, 1963-2000

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Source: Tufts CSDD Approved NCE Database, PhRMAR&D expenditures adjusted for inflation

R&D Expenditures

NCE Approvals

Main Reasons for Termination of Development LACK OF EFFICACY & SAFETY !

One Size Does NOT Fit ALL !Toxicology

19.4%

Other6.2%

Various10%

Clinical Efficacy22.5%

PortfolioConsiderations

21.7%

Clinical Safety20.2% Clinical

Pharmacokinetics/Bioavailability

3.1%

Preclinical efficacy3.1%

PreclinicalPharmacokinetcs/

Bioavailability1.6%

Formulation0.8%

Patent or CommercialLegal0.8%

Regulatory0.8%

Current Treatment is Population Based

What is Personalised Medicine?Personalised Medicine links the patient to a disease (segment or part of the disease) to a drug using a diagnostic or biomarker orclinical test that:

• Defines the disease and/or• Predicts response and risk and/or• Determines dose

Leading to improved patient outcomes, targeted therapies and newcommercial opportunities. Personalised Medicine involves testing patients prior to treatment to enable clinicians to prescribe:

• The Right Drug• At the Right Dose• For the Right Disease• To the Right Patient

Pharmacogenomics –Redefining DiseaseMaking Personalised Medicines

Patient Segmentation is Not New

•Historically we have always done this usingClinical, Biochemical, Histological features:

!Inclusion/Exclusion Criteria in ClinicalTrials

!Regulatory Approved Data sheets oftendefine the approved indications andsubset of patients suitable for theapproved therapy

• BMS - Taxol: first cancer blockbuster, now facing generic competition

• Novel taxanes have entered market

• Beta-tubulin gene contains mutations that predict for patterns of response and resistance

• Beta-tubulin pharmacogenomic test for differential prescription: Taxol or taxane

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Wild-TypeN=33

MutatedN=16

Taxol Response rate(%)Median survival(months)

Genotype

NSCLC treatment with TAXOL

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PharmacogenomicsImportance is clear and growing

•The vast array of technology to define patient subgroups•These range from biochemical, immunocytochemistry,genetics, proteomics, to new evolving technology such asreal time chemotaxis assays•Molecular re-classification of disease through genotype•Better understanding & use of biomarkers for patientstratification•Better understanding & use of biomarkers for patient segmentation & enriched clinical trials•Greater societal expectation on efficacy and safety•Increasing costs leading to better targeted therapies

So What Has Changed ?

20/04/2005 15

Discovery MedicineUtilize and Integrate Human

Pathophysiology and Disease Models

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•Validated targets•Pathophysiologicalunderstanding•Biological Mechanism•Disease stratification•Biomarkers•Patient segmentation

Platforms•Genetics•Genomics•Proteomics•Metabonomics•Lipidomics•Glycomics•Imaging•Epidemiology•Physiology Bioinformatics and Informatics

Clinical DataTarget Validation

Deliverables

Benefit-Risk of Biomarkers in R & DBenefits Risks

1. For NMEs with a novel mechanism of action, biomarkers are key to understanding PoM and establishing PoP/PoC.

2. Biomarkers should help contain the cost of drug development by allowing early termination or rapid progression to Launch.

3. Biomarkers may help pre-select patient populations that are most likely to benefit.

4. Biomarkers that predict the course of disease may serve as a useful tool for clinicians, health care systems.

5. Diagnostic kits could be developed where appropriate patient segmentation may reduce the size of trials required

1. Biomarkers that are nonspecific and do not correlate with clinical outcome may lead to incorrect conclusions.

2. Biomarkers associated with only a portion of the clinical outcome, may not identify all of the relevant effects of the therapy, including adverse effects.

3. Biomarker analysis can be expensive and time-consuming.

4. Biomarker-based decisions could become biased unless a priori criteria are set up for decision-making in addition to biomarker data.

5. Patient pre-selection using biomarkers may reduce the potential market size.

•In a 15,000 patient study, independent drug safety committee recommended stopping further development since mortality was about 60% (82 versus 51) higher in Torcetrapib group.

•Biomarkers did not predict.

•However human genetics (CTEP) in Japanese study didpotentially predict poor outcome because of ineffective “HDL” produced by such inhibition

•Increase in BP may be another factor for increased mortality

Biomarkers & Clinical Outcomes

Disease reclassification at the molecular level

!Genes distinguishing ALL from AML The 50 genes that correlate most highly between ALL and AML are shown.

!The top panel shows genes that are highly expressed in ALL, whereas the bottom panel shows genes more highly expressed in AML.

!While as a group, these genes are correlated with pathologic class, no single gene is uniformly expressed across the class, illustrating the value of whole-genome expression analysis in class prediction

Molecular classification of Acute LeukaemiaGolub TR et al. Science 1999; 286: 531

Acute Myeloid Leukaemia

Similarly with the EGFR Antibody, Erbitux, Approved as Personalised Medicine, Based on EGFR Expression

Rheumatoid Arthritis

GENE EXPRESSION ANALYSIS USING GENELOGIC DATA

!Pathways that are significant to the pathophysiology of

Rheumatoid Arthritis and Anti-TNF treatments have been

highlighted in the table.

!Knowledge of immune response genes can potentially be

useful for identification of surrogate markers of clinical endpoint

or disease/treatment/response markers according to the project

needs.

GenelogicTM Expression Data

Overview of Analysis• Gene expression data from three types of sample

populations analyzed:

!WBC samples from Normal individuals!WBC samples from Rheumatoid Arthritis patients.!WBC samples from RA patients, 6 weeks after

Remicade Infusion.

• Set of 25 genes were identified as a marker set for patient stratification in future novel NME target discovery and development.

Speed and Simplicity

Since it is based on direct genomic detection and not target amplification, ClearRead makes molecular testing faster and simpler. Current methods require highly specialized scientists and lab technicians for processing and interpretation, while ClearReadassays are easy to perform and produce definitive results.

Verigene Mobile

!The next generation Verigene Mobile will transfer the power and accuracy of the Verigene AutoLab to an affordable, hand-held device.

!Its portability will make it ubiquitous at point-of-care settings such as doctor's offices, hospital bedsides and even in patients' homes.

Drugs with Personalised Medicine Properties/Potential•Antibiotics are Personalised Medicines•Herceptin in Oncology •Protease Inhibitors in HIV•Protease Inhibitors in HCV•Diabetic Treatment & Monitoring•Neuroamidase Inhibitors in Influenza e.g. Tamiflu, Relenza•Rituximab, Anti-CD20 in NHL, RA etc•Xolair, Anti-IgE in asthma•Anti-TNF’s & Anti-IL1 in RA•Campostar in Oncology•Xeloda, Gemcitabine, Velcade in Oncology•Taxol & Taxanes in Oncology•UDF in Oncology•EGFR Antibodies & TK inhibitors e.g. Tarceva, Iressa, Erbitux•Potentially VEGF Antibodies (Avastin) and TK inhibitors•Various Monoclonal Antibody Targets