Impurity Lifecycle Management:Visualising a vast array of analytical data

Steve CoombesAstraZeneca, Macclesfield, UK.

20th April 2016

Knowledge Management – what does it mean?

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Pharmaceutical DevelopmentInformation overload

• The drug development process takes years, with huge amounts of information being generated

• Thousands of individual experiments/tests• Hundreds of reports, Tbytes of data• Most concise summary is the marketing application but typically still

runs to hundreds of pages to describe impurity control strategy

• There will be dozens of analytical chemists working on a project supporting medicinal and process chemists as the project moves through development

• Also need to communicate this information to multiple stakeholders• Process Chemists• Formulators• Toxicology / QA• Operations

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LaunchPhase 1Toxicological testingFirst into man

Phase 2Early clinical trials

Phase 3 / Technology TransferFull clinical trialsPrepare for launch

Discovery

Why is impurity profile important?

Limited knowledge Known impurity

• Name• Structure• Amount

• Formation• Removal

• Specification

The challenge?• A large amount of complex data is generated• Information stored in multiple computer systems• Many people work on our projects in different groups

and locations

Why?• To ensure our medicines are safe

by controlling our process• To meet regulatory requirements

Information overloadPassing it on

• In a global workplace, project transfers are inevitable and managing this transition poses multiple problems

• Trying to share data or pass on project understanding to a new team is difficult

• Methods / Specifications• Knowledge transfers

• So, can we make this transfer of knowledge more manageable / efficient?

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?

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What questions do we want to answer and how might we view the information?

What is the current route? Route (Commercial)Route (Development)

How are they formed and controlled?

Fate of impurity BFate of impurity A

What impurities do we see and how much?

Impurities in PhenolImpurities in MethylImpurities in AcetateImpurities in Asprin

0.12

Batch 123

<0.050.080.20

Have we seen this impurity before and where does it elute?

What is this other peak?

Where has it come from and is it a concern?

What is this new peak?

What does the spectrum look like?Pharmaceutical Technology & Development

Information and data capture toolsWhat’s already used?

• ELN• Excellent repository for experimental detail and observations• Difficult to browse/find data unless you have specific identifiers

• LIMS• Great for tracking analysis, batches and numerical results, but difficult to

extract knowledge• Spreadsheets – everyone loves a spreadsheet

• Record batch details & analytical results (imps, assay, water, solvents, etc)• Doesn’t link stages/batches together, not particularly visual, difficult to

understand rejection• Access Databases

• Like spreadsheets but better...• Ability to link data together (eg batch history)• Limited searching & no overview

• Global Document Management Systems• Normally only generated at key time points in development (not living

documents) summarising established knowledge

Discrete results

Grouped / linked results

Summary results

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In reality…

ELN / LIMSOther

GDMS Excel

dil. H2SO4

NaNO3

NaBH4

?

Data to Knowledge – building your control strategy

Quality controlProcess understanding

Data

Knowledge

InstrumentLC, MS, NMR, IR, TGA

Samples containing impurities Sample preparation

Lab PC or CDSChromatogram, UV spectra, Mass

spectra, NMR, IR, TGA

ELNExperimental details, method,

sample prep, results, discussion, conclusions

LIMSExperimental details, method, sample prep

GDMSCMC modules, methods, process descriptions,

reports, data summaries, justifications

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In reality we will need multiple elements

• This starts to throw up some more questions…….• How do we find what we want?• If searching doesn’t always make sense then we will need to browse

(knowledge sharing vs answering a specific question)• How do we view the data?• How do we manage multiple techniques and multiple vendors?• IT infrastructure?

• User access / licensing• Where do we store data? (network issues!) • Oracle v’s local databases?

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Routes, spectra, results, chromatograms...

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Accurate MassMSMSMass spectrum

NMR (2D)NMR (Cabon)NMR (Proton)

Route (Commercial)Route (Development)

Fate of impurity BFate of impurity A

ELSDPDAChromatogram (UV at 254nm)

SST

Name Structure Mol Wt Formula

We need the flexibility to easily navigate around our data and view the results

ACD/Labs SpectrusDB EnterpriseImpurity Resolution Management• The result of cross industry development has been the

creation of “IRM”, a customisable integrated multi database SpectrusDB Enterprise platform

• The 4 individual, but linked databases are:• IRM Reactions - Synthetic routes• IRM Molecules - Individual structures (+ chromatograms & spectra)• IRM Impurities - Impurity structures (+ chromatograms & spectra)• IRM Impurity reactions - Impurity formation and onward reaction

• Enables collation of analytical data, but now with the associated chemical context

Searchable by browsing or by:• Structure or substructure• Any user defined fields, eg compound name• Spectra• MH+, molecular weight or NMR chemical shift• Project name / therapeutic target

•Also has the ability to build links between other IT systems

IRM Impurities Reaction database

IRM Reaction database IRM Molecule database

IRM Impurity database

ACD/Labs IRM - 4 interlinked databases

IRM Impurities Reaction database

IRM Reaction database IRM Molecule database

IRM Impurity database

Workflow optimisation – database population

1. Script imports main reaction scheme from .sk2 file

2. Script creates individual molecules from main route

3. User creates impurities for each stage

4. User creates Reaction scheme for each impurity

IRM Reactions - Customised view

IRM Molecules databaseTabbed view for analytical

reference data

IRM Molecules database

IRM Molecules database

IRM Molecules database

IRM Impurities database

IRM Impurities Reaction database

IRM Reactions - Customised view

Critical importance – connectivity to other systems

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Critical importance – connectivity to other systems

AZ has been using structural databases for yearsBut now we’re fully integrated

Where does this database fit in?

• There isn’t (and won’t be) a single solution to knowledge capture

• ELN/LIMS will be driven by the business as primary repositories for laboratory information

• GDMS will contain the summary information and documentation required for formal submission & approval for regulatory authorities

• The IRM database is a living / working tool that can grow over the development lifecycle from Discovery to LCM

• Enables the visualisation of many separate and discrete elements• Eg synthetic routes, spectra, chromatograms, impurity structures & levels and

fate/purge profiles• The ability to link between our different IT systems is critical for optimal operational performance

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Acknowledgements

Thanks to:• John Nightingale• Kevin Sutcliffe• Martin Hayes

• Albert Van Wyk• Peter Russell• Dimitris Argyropoulos• Stephane Albrecht

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