Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954

Contents lists available at ScienceDirect

Journal of Pharmaceutical and Biomedical Analysis

j o ur na l ho mepage: www.elsev ier .com/ locate / jpba

Efcien ctsearch, a

Lin Wang b, Va Merck Researb Merck Manuf

a r t i c l

Article history:Received 11 JuReceived in reAccepted 31 OAvailable onlin

Keywords:HPLCChromatograpACD/LabsLoratadinePhysico-chemical prediction

od foe dev

methhed b

archreusehysicitiond mo

optimized temperature and gradient program. The optimized new method was then uploaded to internaldatabases as knowledge available to assist future method development efforts. Routine implementationof such standardized workows has the potential to reduce the number of experiments required formethod development and facilitate systematic and efcient development of faster, greener and more

1. Introdu

Analyticduring thein the pharthat has bincluding asdation stud[14]. GiveR&D laboraquickly to sapproachesopment hasystem is phase/statioaration is as DryLab tools allowbased upon

CorresponE-mail add

http://dx.doi.o0731-7085/ robust methods leading to greater productivity. In this article, we used Loratadine method developmentas an example to demonstrate efcient method development using this new workow.

2014 Elsevier B.V. All rights reserved.

ction

al testing and control strategy plays a critical role entire life cycle of the drug development processmaceutical industry. HPLC is the major work horseeen used for all aspects of pharmaceutical analysissay, dissolution analysis, impurity prole, forced degra-ies, process control, and drug metabolism studiesn the time constraints and limited resources in antory, it is imperative to develop robust HPLC methodsupport the drug development process. Many different

to improve the performance of HPLC method devel-ve been reported [58]. Often, a column screeningused to nd a promising combination of mobilenary phase which meets desired criteria, and the sep-

subsequently optimized using a software tool such[712] or Chromsword [5,6,1316]. These software

the scientist to model chromatographic separations retention data from a limited number of scouting

ding author. Tel.: +1 732 594 4515; fax: +1 732 594 3887.ress: jinjian.zheng@merck.com (J. Zheng).

experiments, and optimal separation conditions can be predictedby the modeling software. This approach avoids labor intensivetrial-and-error experiments, potentially resulting in signicantimprovement in method development efciency and nal methodquality.

In spite of the successes with software simulation, there are cer-tain limitations. Typically, software simulation is done with onestationary phase and one set of mobile phases. Therefore, it is criti-cal to select the appropriate combination of stationary and mobilephases for evaluation in scouting experiments. Screening exper-iments can help the scientist make informed decisions on goodstationary phase and mobile phase candidates. However, without agood understanding of the physicochemical properties of analytessuch as pKa, log P, log D, and solubility, these screening experi-ments may not yield desired results within a reasonable time framedue to excessive trial-and-error experimentation. Ultimately, thechromatographic experience of the scientist is as important afactor in overall success as the automation and simulation toolsmentioned above. Therefore, we think that the optimal work-ow for efcient method development must thoughtfully combineelements of knowledge management, software physicochemicalproperty prediction, chromatographic simulation, and focusedexperimentation.

rg/10.1016/j.jpba.2014.10.0322014 Elsevier B.V. All rights reserved.t HPLC method development using stru physico-chemical prediction and chroma, Jinjian Zhengb,, Xiaoyi Gonga, Robert Hartman

ch Laboratories, Merck, Rahway, NJ 07065, USAacturing Division, Merck, Rahway, NJ 07065, USA

e i n f o

ly 2014vised form 17 October 2014ctober 2014e 8 November 2014

hic simulation

a b s t r a c t

Development of a robust HPLC methconsuming. In our laboratory, we havto improve the performance of HPLCmethod databases that can be searcexisting knowledge of HPLC methodsHPLC method development, or even the software to predict compound phelp select appropriate method condstationary and mobile phases, we useure-based databasetographic simulation

incent Antonuccia

r pharmaceutical analysis can be very challenging and time-eloped a new workow leveraging ACD/Labs software toolsod development. First, we established ACD-based analyticaly chemical structure similarity. By taking advantage of theived in the databases, one can nd a good starting point for

an existing method as is for a new project. Second, we usedochemical properties before running actual experiments tos for targeted screening experiments. Finally, after selectingdeling software to simulate chromatographic separations for

50 L. Wang et al. / Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954

Fig.

Herein, developmescreening rinto structuis preservesearching sting point (suFollowing tpound physrunning actthumb to hwell as meand mobileAfter the scrphases, a feify the in ssoftware (esimulate chfaster, greemethod optnal databassimilar comdine methocombined aprediction tefcient HPFurther, thesive high-thdevelopmeand simularequire limimplement

2. Experim

2.1. HPLC in

All expe(Agilent, Saquaternarymum operasoftware (Wsystem and

2.2. HPLC c

XBridgechased from

2.3. Materials and reagents

Acetonitrile (HPLC grade), water (HPLC grade), sodium hydrox-ide solution (10 N) and triethylamine (HPLC grade) were purchased

isher, 99.9

fromties wJ, US

rom

ailedcapti

ults

arch

improratoultipults d deast

he porouevelts) s

orgae besh labequigingenic

is thed innsigh

acro wah sc

live senteb Le seses ippli

resny. Af estle to1. A new strategy for efcient HPLC method development.

we propose an integrated workow for HPLC methodnt shown in Fig. 1. First, we integrated existingesults, method information, and vendor applicationsre-searchable databases. Knowledge and informationd and re-used to expedite method development. Byructure similarity, one can quickly identify a good start-ch as column, pH, and mobile phase) for target analytes.

hat, we further leveraged software tools to predict com-ico-chemical properties such as pKa/log P/log D beforeual experiments. Such information serves as a rule ofelp select appropriate chromatographic techniques asthod conditions such as stationary phase, buffer pH,

phase additives for targeted and focused screening.eening experiments to dene the stationary and mobilew scouting runs are performed to experimentally ver-ilico selectivity predictions, and separation modeling.g. ACD/Labs, LC simulator, DryLab, etc.) was used toromatographic separations for rapid development ofner, and more robust methods. With the completion ofimization, the new method is introduced to the inter-e to assist future method development for a structurallypound. In this article, we will use an example of Lorata-d development to illustrate how we have successfully

structure-searchable database tool, physico-chemicalool, and LC simulator to create a holistic workow forLC method development and lifecycle management.

workow presented also supports a shift from exten-roughput laboratory screening as the basis of method

nt, to a model where knowledge retrieval, prediction,tion suggest optimal analysis conditions which onlyited experimental verication in the laboratory beforeation.

ental

from Fin H2Ochasedimpuriway, N

2.4. Ch

Detgure

3. Res

3.1. Se

To cal laband mtal resmethoaging pusing thigh-thoften dreagenenticand thin eacoften rchallenmutagciencycapturthese iaccess

Oneresearcbiningthe preACD/Wthat ardatabafrom aeraturecompatage oare abstrumentation

riments were conducted on Agilent HPLC 1100 systemsnta Clara, CA, USA) equipped with an autosampler, a

pump and a variable wavelength detector. The maxi-ting pressure of the system was 400 bar. Empower IIaters, Milford, MA, USA) was used to control the HPLC

for data acquisition and analysis.

olumns

C18 columns (100 mm 4.6 mm I.D., 3.5 m) were pur- Waters, Milford, MA, USA.

feasible byturally simfor methodis not availa

As a molaboratory,Loratadine tial LoratadcompoundsEP), or idenand its relaeral key USexisting puseparating Scientic (Pittsburgh, PA, USA). Phosphoric acid (85 wt%9% trace metal basis) and boric acid (99.99%) were pur-

SigmaAldrich (St. Louis, MO, USA). Loratadine andere synthesized by Merck Sharp & Dohme Corp. (Rah-

A).

atographic conditions

chromatographic conditions are provided in specicons.

and discussion

databases for starting point of method development

ove productivity and reduce R&D costs in an analyti-ry, signicant emphasis is placed on high-throughputlexed analyses aimed at generating many experimen-in a short period of time. However, one aspect of thevelopment process that is often overlooked is lever-experiments to inform current experiments, or simplywer of knowledge management and prediction to assist

ghput experimentation. As an example, methods areoped for commonly observed analytes (e.g. solvents andimultaneously within individual groups of a large sci-nization, resulting in signicant duplication of effort,t methods available are not always being implementedoratory. Development of optimal analytical methodsres a high level of technical expertise, particularly for

low level quantitative analyses such as those used forimpurities [17]. For many organizations, a major inef-e one-and-done data life cycle where insights are only

the heads of individual scientists and not shared, orts are stored in an electronic repository with limited

ss the organization.y to address this problem is to provide a platform forientists to capture and share their knowledge by com-analytical data with chemical and structural context. In

research, we have leveraged the commercially availableibrarian software to establish web-accessible databasesarchable by structure. Our current analytical methodnclude achiral and chiral separation methods obtainedcation notes provided by column manufacturers, lit-ources, and analytical methods generated within thell databases are updated regularly. One major advan-

ablishing structure searchable databases is that users search by chemical structure similarity, which is not

text-based searches. Analytical methods for a struc-ilar compound can provide a promising starting point

development when a method for the exact compoundble.del system to evaluate the integrated workow in our

development of an impurity/degradate HPLC prole forwas selected. Shown in Fig. 2 are the structures of poten-ine related impurities or degradation products. These

are either listed in compendial monograph (e.g. USP,tied in the synthetic process. Separation of Loratadineted compounds has been reported [18]. However, sev-P and EP specied impurities were not included in theblications. Therefore, a new method that is capable ofall impurities listed in Fig. 2 is desired.

L. Wang et al. / Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954 51

Fig. 2. StructuF is a pseudoe

Initiatinstructure sino records However, wpounds witamitriptylin

Fig. 3. Structudesipramine, tres of Loratadine (compound J) and its related compounds. Compound P is pseudoephedriphedrine related compound.

g the proposed workow, databases were searched formilarity (both Markush and simple structure). There arefor the separation of exact compounds in the database.e found multiple records for the separation of com-

h similar structures such as protriptyline, nortriptyline,e, doxepin, imipramine, desipramine, trimipramine,

and nordoxapplicationuse either Cfor methodis critical fofrom 2.7 to

res of compounds with similar structures to Loratadine found in the databases includrimipramine, and nordoxepin.ne that is commonly used in combination with Loratadine. Compound

epin as shown in Fig. 3. The results from several keys were summarized in Table 1. Most of these methods18 or Cyano stationary phase. We chose C18 over Cyano

development due to its superior column stability, whichr a commercial supply lab. Buffers with a wide pH range

12.0 have been used as shown in Table 1. Therefore, a

ing protriptyline, nortriptyline, amitriptyline, doxepin, imipramine,

52 L. Wang et al. / Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954

Table 1Summary of methods for similar structures from application database.

Compounds Column Mobile phase Comments

Protriptyline, nortriptyline,doxepin, imipramine,amitriptyline

Purospher STAR RP-18 Water/MeOH/potassium phosphate, pH 7.6 Good resolution. Peak tailing

Protriptyline, nortriptyline,doxepine, imipramine,amitriptyline, trimipramine

NUCLEOSIL 100-5 C18 HD Water/acetonitrile/TEA-

Doxepine, trimipramine,amitriptyline, imipramine,nordoxepin, nortriptyline,desipramine, protriptyline

Ascentis ES Cyano Acetonitrile, methanol, p

Doxepine, protriptyline,imipramine, nortriptyline,amitriptyline, trimipramine

Hypersil Gold Acetonitrile/water/0.1%

Nordoxepin, protriptyline,nortriptyline, imipramine,amitriptyline

ZirChrom-PBD Acetonitrile/water/potas

Desmethyldoxepin, protriptyline,esipramine, nortriptyline,doxepine, imipramine,amitriptyline, timipramine

Pursuit C18 Water/methanol/acetonpH 7.0

Doxepine, imipramine,nortriptyltrimipram

Zorbax Extend C18 Water/MeOH pyrrolidin

Nortriptylinamitriptyl

nol/s

column thaXbridge C18shape and sa wide pH rseveral dataphase modibaseline nocompendiaand its rela

From prmobile phashown in Fisample soluble root cauionized anaa result, th

Fig. 4. Overla0.5 mg/mL, (bC18, 3.5 m, 1H3PO4 and (B)UV absorbance

n tog/m

tenti (reaceu

of a higho-cheter ine, amitriptyline,ine

e, imipramine,ine, clomipramine

XBridge C18 Acetonitrile/metha

t is stable across a wide pH range is preferred. A Waters column was selected because it shows excellent peakeparation for similar compounds, and it is stable acrossange due to its unique ethylene bridged hybrid silica. Inbase applications, 0.1% formic acid was used as mobileer. We replaced it with 0.1% phosphoric acid to reduceise. Acetonitrile was selected because it was used in thel method and a relevant literature [18] for Loratadineted compounds.eliminary injections using the selected stationary and

solutio0.005 mthe reby RRTpharmchoiceshape,physicparamvalue.ses, severe tailing of Loratadine peak was observed asg. 4. The tailing factors range from 1.11 for 0.005 mg/mLtion to 3.54 for 0.5 mg/mL sample solution. One possi-se is the overloading of protonated Loratadine becauselyte usually has much less loading capacity [19]. Ase retention time shifted from 5.56 min for 0.5 mg/mL

id chromatograms of Loratadine API at different concentrations: (a)) 0.05 mg/mL, and (c) 0.005 mg/mL. HPLC column: Waters XBridge00 mm 4.6 mm; injection volume: 5 L. Mobile phases: (A) 0.1%

acetonitrile. Flow rate: 1.5 mL/min; temperature: 35 C; detection: at 270 nm; gradient: 010 min, 2550%B.

3.2. Select s

For the pH is criticshould be cnents if posthe functionrate due tosoftware, hof 0.3 or b

Employidine is calcstated abovamine (TEAto replace tin Fig. 5, ex1.05) and c8.19 min toits concentnicantly imthis physicoter positionusing the soptimize thphosphate, pH 6.9 Peak tailing of early elutingpeaks

otassium phosphate, pH 7 Good peak shape andseparation

formic acid, pH 2.7 Weak retention. Peak tailing

sium phosphate, pH 12.0 Good peak shape andseparation

itrile/potassium phosphate, Good peak shape

e buffer, pH 11.5 Good separation and peakshape

odium phosphate, pH 7.0 Excellent peak shape andseparation

5.74 min for 0.05 mg/mL solution, and 5.81 min forL solution (the lower the concentration, the longeron time). Therefore, it is difcult to identify peakslative retention time) as the retention time of activetical ingredient (API) varies with concentration. Clearly,ppropriate buffer pH is critical to achieve a good peaklighting the value of rst understanding basic analyteemical properties prior to conducting generalized, broadscreens to avoid collection of extensive data of limiteduitable buffer pH

separation of ionic analytes, controlling mobile phaseal to the performance of the method. Typically, the pHhosen at least 1.5 unit away from pKas of all compo-sible [20]. Although pKa could be estimated by checkingal groups in molecules, this approach is not very accu-

electronic and/or steric effects. Using pKa calculationowever, pKa values can be calculated with an accuracyetter in most cases.ng the proposed integrated workow, the pKa of Lorata-ulated to be 4.27 by ACD software. Based on the rulee, a basic buffer (20 mM boric acid with 0.02% triethyl-), pH adjusted to 9.5 with sodium hydroxide) was usedhe 0.1% phosphoric acid as mobile phase A. As showncellent peak shape (tailing factor ranging from 1.03 toonstant retention time (retention time ranging from

8.21 min) were observed for Loratadine even thoughration varies from 0.005 mg/mL to 0.5 mg/mL, thus sig-

proving the consistency of peak identication. With-chemical property prediction in hand, we are now bet-ed to conduct focused experimental verication runselected chromatographic mobile phase and column toe method more efciently.

L. Wang et al. / Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954 53

Fig. 5. Overlaid chromatograms of Loratadine API at different concentrations: (a)0.5 mg/mL, (b) 0.05 mg/mL, and (c) 0.005 mg/mL. HPLC column: Waters XBridge C18,3.5 m, 100 mm 4.6 mm; injection volume: 5 L. Mobile phases: (A) 20 mM boricacid + 0.02% triethylamine (TEA), pH adjusted to 9.5 with sodium hydroxide and (B)acetonitrile. Flow rate: 1.5 mL/min; temperature: 35 C; detection: UV absorbanceat 270 nm; gradient: 010 min, 3565%B.

3.3. Optimi

After selnext step isand-error enot be ablesamples as tion can heminutes, wdevelop a rosoftware assince the lagrams are cUSA), ChromUSA), and Aand there asuch softwgradient oracquired inResolution ration of a of the critia given varguidance focedure is reThe chroma

Fig. 6. ChromXBridge C18, 3triethylamine Temperature: injection volum

Fig. 7. ChromWaters XBridgacid + 0.02% tracetonitrile. T1.5 mL/min; in

atadther ore, tatadatadi

anag

meas la, syrtiontent

e APIties f

sizele ve

for esage ore, r th

quicom ownelatewhicze separation

ection of stationary phase, pH, and organic modier, the to optimize gradient and temperature. Traditional trial-xperimentation is usually time-consuming, and may

to yield the optimal method, especially for complexthe one used in this study. Computer software simula-lp us evaluate separation under new conditions withinhich improves the efciency and makes it possible tobust method within a reasonable time frame. Computersisted HPLC method development has been reportedte 1970s [1,21]. Currently, a number of software pro-ommercially available such as DryLab (LC Resources,Sword (Merck KGaA, Germany), Fusion AE (S-Matrix,

CD/Labs (Advanced Chemistry Development, Canada),re many reports on fast method development usingare [2226]. Typically, scouting runs (e.g. 2 runs for

4 runs for gradient/temperature modeling) are rst the laboratory and used to build a retention model.maps show the effect of a given variable on the sepa-set of compounds and clearly describe the resolutioncal pair (least-resolved components) as a function ofiable. The computational results are then utilized asr further experimental work in the laboratory. This pro-peated until satisfactory chromatography is achieved.togram of the optimized method was shown in Fig. 6.

All Loreach oThereffor Lorfor Lor

3.4. M

Theand wtabletsdissoluthe conrate thimpurisamplemultippointsthe doTherefbuilt foable todine frwas shother rof 2.0, atogram of Loratadine and its related compounds. Column: Waters.5 m, 100 mm 4.6 mm. Mobile phases: (A) 20 mM boric acid + 0.02%(TEA), pH adjusted to 9.5 with sodium hydroxide and (B) acetonitrile.35 C; detection: UV absorbance at 270 nm; ow rate: 1.5 mL/min;e: 5 L. Gradient: 015 min, 2535%B; 1535 min, 3565%B.

4. Conclus

We havopment emexperimentknowledgewe establissearched byexisting knSecond, weproperties bpriate methworth notinof stationarimpurities was found are lots of essary to atogram for assay and content uniformity of Loratadine. Column:e C18, 3.5 m, 100 mm 4.6 mm. Mobile phases: (A) 20 mM boric

iethylamine (TEA), pH adjusted to 9.5 with sodium hydroxide and (B)emperature: 35 C; detection: UV absorbance at 270 nm; ow rate:jection volume: 5 L. Isocratic at 59%B. Run time: 5 min.

ine related compounds were baseline separated fromand from Loratadine with a minimum resolution of 1.5.his method can be used as an impurity proling methodine drug substance, or as a stability indicating methodne drug product.

e and reuse knowledge

thod shown in Fig. 6 was uploaded to the database,ter applied to several different formulations includingup and for different purposes such as stability testing,, and content uniformity with minor modications. For

uniformity and dissolution testing, the goal is to sepa- from other impurities, but it is not necessary to separaterom each other. The challenge, however, lies in the large. For example, a dissolution test is typically conducted inssels (e.g. n = 624) with samples taken at multiple timeach batch [27]. To determine the content uniformity ofform, about 1030 samples are analyzed per batch [28].fast separation is desired. Using the retention modele impurity proling method shown in Fig. 6, we werekly simulate a fast isocratic method to separate Lorata-all other impurities. The experimental chromatogram

in Fig. 7. Loratadine was baseline separated from alld compounds within 5 min with a minimum resolutionh signicantly improved the throughput.

ionse presented an effective workow for method devel-ploying a combination of hardware, software, focusedation, and application of personal and organizational. The new workow consists of three parts. First,hed ACD-based HPLC method databases that can be

chemical structure similarity to take advantage of theowledge of HPLC methods archived in the databases.

used software to predict compound physico-chemicalefore running actual experiments to help select appro-od conditions for targeted screening experiments. It isg that for Loratadine method development, screeningy phase and mobile phases were not performed as allwere well characterized, and a good starting conditionfrom the database. For complex samples where thereunknown impurities, targeted screening may be nec-nd a promising starting condition. Finally, we use the

54 L. Wang et al. / Journal of Pharmaceutical and Biomedical Analysis 104 (2015) 4954

modeling software to simulate chromatographic separations, fol-lowed by targeted experimental verication in the laboratory, torapidly develop fast and robust HPLC methods. The optimized newmethod was then added to the databases to assist future methoddevelopment. Such workow brings the benet of reduction in thenumber of experiments required for method development. Faster,greener and more robust methods are developed in a system-atic and efcient manner, leading to productivity gains in overallmethod development.

Acknowledgements

The authors would like to thank Thom Loughlin, Yong Liu,Xiaodong Bu, and Patrick Chin for their support on Merck inter-nal structure-searchable databases; and thank Mary Rogowski andKarim Kassam from ACD/Labs for their support.

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Efficient HPLC method development using structure-based database search, physico-chemical prediction and chromatographic s...1 Introduction2 Experimental2.1 HPLC instrumentation2.2 HPLC columns2.3 Materials and reagents2.4 Chromatographic conditions

3 Results and discussion3.1 Search databases for starting point of method development3.2 Select suitable buffer pH3.3 Optimize separation3.4 Manage and reuse knowledge

4 ConclusionsAcknowledgementsReferences