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The most difficult chromatographic methoddevelopment scenarios are encountered in thedevelopment of stability indicating methods,or forced degradation studies in drugdevelopment. In these projects thechromatographer has to keep track of multipleimpurities/degradants over manyexperimental conditions and chromatographicparameters. Tens, or even hundreds, ofchromatograms can be generated in a fairlysimple method screen.

The comprehensive approach to methoddevelopment would be a thoroughinvestigation of the design space for any givenmixture or sample including buffer, column,solvent, time, temperature, etc. Given the timeconstraints and limited resources in any R&Dlaboratory, however, this type of broad scopeinvestigation is unrealistic.

In order to provide a starting method within areasonable timeframe, therefore, experiencedseparations laboratories will usually leveragecorporate knowledge by employing aselection of well characterised standardmethods as a starting point for new projects.These ‘default’ methods usually cover a large‘chromatographic space’ including orthogonalcolumns, buffers, and solvent.

Even when past knowledge is used to limit thenumber of variables investigated in a newmethod development project, however, thereis still a vast amount of data to process,analyse, review and make decisions on. It isrisky to depend on a single human brain todeal with these large amounts of information.Furthermore, the question remains, does thisapproach help the analyst reach optimaldesign space for each sample, or would amore comprehensive investigation provide abetter starting point?

The Holy Trinity of Effective Method Development

With the ‘perfect storm’ of technology at thechromatographer’s disposal today, it ispossible for multi-dimensional optimisation ofparameters to be carried out withoutexcessively burdening the chromatographer.

Efficient and thorough method developmentfirst requires a strategic approach. Acombination of an understanding of thecurrent project and the ability to applyorganisational knowledge in context isimportant in helping to select a suitablestarting point. Suitableinstrumentation/hardware will enable a widearray of chromatographic conditions to beexamined in parallel, and with minimal manualintervention (overnight, for example), ifdesired. Software is an ideal tool to streamlinedata collection, control, process, and interpretinjections, and reduce transcription errors thatmight occur in manual review of large amountsof data. Finally, software can also help managethe knowledge gained in a project so that itcan be re-applied in another iterative cycle forfurther refinement, or in future projects (asillustrated in Figure 1).

Context from Personal and OrganisationalKnowledge

Chromatographers apply their expertise andexperience in every method developmentproblem. In a perfect scenario, however, everyproject would start and finish at aknowledgebase where personal experiencecould be enhanced with organisationalknowledge to provide a head-start.

Since chromatography is used throughoutorganisations across a wide variety ofchemistry-related endeavours it is rare that acentral repository of information is available.Results collected from different instrumentsare typically segmented and contribute little toorganisational learning and intelligence.Chromatographic intelligence is typicallyscattered across a number of discrete silosincluding data files, Registry DBs, ELNs, labnotebooks, and reports. The multi-disciplinarynature of the information required at thebeginning of a project (methods used in otherparts of the organisation for the same/similarcompounds; degradation patterns; saltscreening data; solubility; stability;physicochemical properties—pKa, logP, logD)further contributes to the difficulty of onecentral system.

How Software Can Aid Decision-Makingin Chromatographic Method Developmentby David C. Adams (Senior Application Scientist, ACD/Labs), Sanjivanjit K. Bhal (Manager, Marketing Communications, ACD/Labs)

February / March 2013

Traditional trial and error experimentation is still often used in many analytical laboratories for method development, and while

chromatographers will rely on their experience and intuition to select a starting point for method development, this approach is not

reliably the most effective or efficient. Whereas in the case of simple samples the educated trial and error approach might be a

reasonable strategy, it is increasingly less effective as the system becomes more complex.

Figure 1: The holy trinity of effective method development—Knowledge, Software, and Hardware.

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Hardware

Chromatography hardware has beendeveloping at a rapid rate over the lastdecade and has seen a move to smallercolumn packing materials and much higherpump pressures, so-called ‘Ultra HighPerformance Liquid Chromatography(UHPLC)’ systems. The use of these higherefficiency systems, along with traditional HPLCinstruments, coupled to multiple detectors(DAD/PDA, MS, ELSD, etc.) is a great aid tothe method development scientist. Thesedevelopments in hardware have greatlyimproved chromatographic performance andhave potentially allowed for the easier trackingof components between injections.

Software

While instrument vendors provide software to run experiments and manageinjections, there is little method developmentsoftware available.

Ideally software for method selection andoptimisation would treat the process in thesame way as a chromatographer. It shouldprocess data so that this onerous task couldbe removed from the analyst, and track peaksacross injections to facilitate faster decision-making. Built-in intelligence about the processwould enable the software to make decisionsbased on specific requirements and criteriainput by the chromatographer to achieveoptimal design space. Optimisation should bean interactive process that allows thechromatographer to apply their experienceand expertise to arrive at an acceptablemethod. Finally, the software should provide asingle button click capability to save theknowledge gained from this process in asearchable database that could be accessed

by colleagues to provide a head-start forfuture projects.

A chromatographic knowledgebase must notonly include chromatographic data, but also itschemical context. This may include samplenames, spectral peak assignments, orstructures linked to elution data with methods.Furthermore, accumulation of the knowledgemust require little manual effort on the part ofthe chromatographer and ideally be part of anapproach to increase accuracy and efficiency.

Ideally at the conclusion of every methoddevelopment all the knowledge gained fromthe project would be stored in a format that isaccessible and searchable. Preferably thissystem would also integrate with a centralknowledge management system to offeraccess to the wealth of intelligence gatheredthroughout the enterprise. Other than theability to quiz a colleague face-to-face, digitalinformation is ideal for preservation ofintelligence and access to chromatographicknowledge.

Real-World Applications

Industry-leaders in chromatographic methoddevelopment have adopted strategies thatcombine hardware, software, and knowledge,as a means to improve the productivity of theirlaboratories for higher return on investment.

Rudy Sneyers is a senior scientist in the small molecule method developmentdepartment at Janssen Pharmaceuticals Inc(Belgium). For over a decade, he has made aconcerted effort to improve the return oninvestment on (U)HPLC method developmentsystems in their laboratories. Over the yearshis strategy for method development hasevolved to one aligned with the holy trinitysystem, internally referred to as the

‘AutoChrom UPLC-Twins [LC-UV-MS]’approach developed in the COSMOS project(Computer Organized Screening and MethodOptimization System).

Through a combination of hardwareimprovements, the ability to learn fromexperimentation and re-use intelligence, andthe appropriate application of software fororganising, visualising, and tracking data,Sneyers’ lab realised a significant reduction indevelopment time, substantial reduction inFTE cost, and extensive improvements in thequality of methods (Figure 2 shows theprogress of improvements).

Figure 2. Progress of process output andreturn realised from refinement of methoddevelopment—R. Sneyers (JanssenPharmaceuticals Inc).

The Janssen method development project isbased on three principles:

• The use of scientific strategy (DoE)

• Introduction of a single quadrupole mass spectrometer alongside a PDA detector (LC-MS)

• Software designed for automated peak tracking and evaluation—ACD/AutoChrom MDS

ACD/AutoChrom MDS (Method DevelopmentSuite) is software developed by AdvancedChemistry Development, Inc (ACD/Labs). Itwas designed with the expert separationsscientist in mind and closely tracks theworkflow that chromatographers follow.

ACD/AutoChrom MDS enables the scientist toset up a method development strategy,whether that is a column/buffer/solvent screenfollowed by a gradient/temperatureoptimisation, or any combination of theseparameters (and others). Once the method

Figure 2: Progress of process output and return realised from refinement of method development—R. Sneyers (Janssen Pharmaceuticals Inc).

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development strategy has been decided, thesoftware interacts directly with the instrument(Agilent ChemStation or Waters® Empower™software) to acquire the data and import itback into the project. Automated peak pickingand peak tracking routines using DAD/PDAand MS spectra greatly reduce the data reviewtime for the scientist.

“The cycle time for data analysis has beenreduced from more than a week to within aday with ACD/Labs’ method developmentsoftware,” agrees John Stafford (Eli Lilly,Indianapolis, USA) a long-term user ofACD/AutoChrom MDS.

Decision making tools within ACD/AutoChromMDS allow the best experimental conditionsfrom the Screening Wave to be quicklyidentified and moved to the OptimizationWave. Once experiments are acquired duringOptimization, the software employs easy touse but powerful chromatographic modellingtools (ACD/LC Simulator) to interpret andresolve the system and determine the nextbest injection. This iterative approach tomethod development, between scientist andsoftware, is not only intuitive to thechromatographer but also results in a vastreduction in the number of injections requiredto solve the task.

Tom van Wijk who works in the methoddevelopment and validation department atAbbott Healthcare Products BV (Netherlands)also uses a combination of information,hardware, and software for effective methoddevelopment and has found that “thedevelopment of a high quality stabilityindicating method within two weeks isfeasible” when using this system. Van Wijk’slab employs a variety of software tools to aid

method development. Among these isACD/Labs’ physicochemical propertyprediction software used to estimateproperties for known and potential impurities(pKa, logP, logD) to provide ‘context’. Theyalso use ACD/AutoChrom MDS, which allowsthem to automate HPLC method screening. Inorder to leverage legacy knowledge adatabase is maintained to help select startingpoints for new projects.

ACD/Labs uniquely provides a multi-vendor,multi-technique knowledge managementplatform (ACD/Spectrus) to help homogenisethe knowledge gathered daily by scientistsalong with its chemical context and humaninterpretation. A number of knowledgemanagement solutions are provided forseparations laboratories that can help withcolumn selection, chiral or achiral methodselection, and impurity tracking. Thecomprehensive AutoChrom product will saveall the data from initial screening proceduresthrough to labelling individualchromatographic peaks of the optimisedmethod. With the single click of a buttondecisions made in the project are preserved ina homogenous environment that offers accessto the wealth of knowledge. This collaborativeSpectrus environment offers thechromatographer a central repository fromwhich to gather the information produced bydisparate labs at the beginning of a methoddevelopment project. The data may besearched by a variety of structural,chromatographic, spectroscopic, and textualparameters.

“Reliability, robustness, and lifetimes ofmethods have improved, and at the same timewe have reduced the loss of interpretation

information and expensive retesting ofsamples…the QbD approach to methoddevelopment aided by ACD/AutoChrom MDS(important for method quality) will providereturn on investment within a short time,”Rudy Sneyers (Janssen Pharmaceuticals Inc.).

Conclusion

The most effective strategy for methoddevelopment should be a combination ofhardware, software, and application ofpersonal and organisational knowledge. Thedemand for greater efficiency and productivityin all chemical R&D enterprises can only bemet by using all the available tools.

Chromatography software tools in theseparations laboratory make it possible todistil data in a highly automated fashion andaid data analysis and visualisation. This helpsthe analyst to arrive at decisions faster andwith greater confidence. Software systemsdesigned for creation of chromatographicknowledgebases and preservation ofintelligence, as an extension of everydayscientific activities, help to streamlinechromatographic method development,method selection, and data interpretation.

While there are not many vendors of methoddevelopment software, the benefit ofincluding such software is a reduction in thenumber of injections/experiments required fornew samples and ultimately, greater efficiency.Furthermore, organisations that are able toprovide a central resource of unified laboratoryintelligence to their scientists will benefit fromthe re-use of legacy knowledge with improvedproductivity and better allocation of resources.

Acknowledgements

We would like to express our gratitude toRudy Sneyers, Tom van Wijk, and JohnStafford for agreeing to discuss their projects.

References

1. R. Sneyers, J. Peeters, L. Van Grieken, andG. Torok, Return of Investment in (U)HPLCMethod Development Systems, ACD/LabsEUM 2011.http://www.acdlabs.com/download/publ/2011/eum11_sneyers.pdf

2. T. van Wijk, The Role of Assessments inMethod Development—A Knowledge-BasedApproach, ACD/Labs EUM 2010.http://www.acdlabs.com/download/publ/2010/eum10_vanwijk.pdf

3. J. Stafford, Challenges of Peak Tracking inInformation-Rich HPLC Experiments,ACD/Labs EUM 2008.http://www.acdlabs.com/download/publ/2008/asms08_stafford.pdf

Figure 3: Automated workflow of QbD method development with ACD/AutoChrom MDS.

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Shimadzu has launched the HS-20 gas

chromatography headspace sampler for accurate

analysis of an even wider range of volatile com-pounds

with boiling points ranging from low to high. The HS-

20 heats liquid or solid samples sealed in a container

to a specific temperature, and injects the volatile

compounds diffusing into the gaseous phase into a GC

or a GCMS. These systems are widely used in the fields

of environmental and pharmaceutical applications as

well as in materials and food products analysis and

forensics. The HS-20 will support the-se analyses

particularly in testing and inspection organizations.

The unique configuration of flow lines and the oven

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Headspace samplers enable easy analysis of volatile compounds. They are used in various fields

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For more information www.shimadzu.eu

New Headspace Sampler for GC and GCMS New HILICColumn forUHPLC

Nacalai Tesque (Japan) introduces

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