Knowledge Management Examples in CMC Development

Transcription

1 Knowledge Management Examples in CMC Development Kristopher Barnthouse, Ph.D. API Large Molecule Development PDMS (Pharmaceutical Development and Manufacturing Science) Janssen R&D, Johnson & Johnson Malvern, PA, USA

2 Many kinds of data & knowledge must be managed (for the CMC development and CMC support of biological products) Product Business es Analytical Methods Materials Facility and Equipment Structure Function MOA CQAs Failure modes Stability Development data Platform information Product impact/cpps Manufacturing Performance Development Know-how Tech Transfer PV Dossier Development Regulatory Interactions Capabilities Performance etc. Origin Test results Variability Failure modes etc. Design Controls Performance etc.

3 Good KM practices have many potential benefits KM Benefits: Powerful: Optimized KM within single program Bridging development and manufacturing data for a product Connecting end-to-end data (materials, process, product quality measures and patient experience for a product end-to-end) Very Powerful: Generalized knowledge leveraged across multiple programs Build platform data and use across multiple products Identify trends and fundamental understandings and reapply them That is, change the way you work based on new learnings KM Investments: People,, Technology

4 General Knowledge Management Acquire Data Data or other information are acquired Could be technology heavy Sometimes enormous quantities of data People Technology (Re)Apply the Learnings Learnings / Knowledge is actively applied or reapplied People and process heavy Business benefits are realized / Quality improved, time/risk/cost reduced KM Cycle Incorporate/Learn Applicable knowledge is derived from data and there is organization learning People and process heavy Analysis, synthesis, identify the most valuable information

5 Example 1: Lab-to-Patient Initiative Issue: knowledge inefficiently managed from development through commercial product lifetime. Challenges: Document-based knowledge (nearly 100%) Lack of consistency in organization of data (e.g. many names for same thing) Electronic data in many disconnected systems with different formats Understanding Data Information Understanding Relationships Knowledge Understanding Patterns Wisdom Understanding Principles Analysis Tools Data Warehouse S88 Connectedness

6 Improved KM : What is going on in there? Operational Source Systems Current Management Tools Data Access Tools ELN LES LIMS PIMS Extract Extract Extract Extract Automated Data Integration Strategy Access Ad Hoc Query Tools Report Writers Analytic Applications MES ERP ETS Extract Extract Extract Homo sapiens based data integration Access Modelling: Forecasting Scoring Data mining

7 Example: Interactive Control Panel Raw Materials Pre Formulated Bulk Oligo Results (PFB) In In Bioreactor In Measures (BX) In Direct Product Capture In Measures (DPC)

8 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

9 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

10 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

11 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

12 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

13 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

14 Interactive Control Panel BSA QC - 2 QC - 3 QC 1 QA Y Intermediate X

15 Interactive Control Panel BSA QC - 2 We can go in Reverse! QC - 3 QC 1 QA Y Intermediate X

16 Knowledge Management: Lab to Patient People: 5 FTE/2 yr to build, 2 FTE to maintain, culture change needed throughout organization : Fewer documents, compliance to recipes and platforms requires ongoing diligence Technology: Systems (ELN, MES, PIMS, etc.) Sizable investment: $$$$ Acquire Data People Technology (Re)Apply the Learnings KM Cycle Incorporate/Learn People and : Localized knowledge. Use is primarily driven by investigations; still working on harnessing data to more proactively provide understanding and then to apply it Technology: Data warehouse with reports and querying tools; Adding Criticality Analysis, CPV, and looking into multivariate real time trending in manufacturing

17 Example 2: KM for Regulatory Dossiers (CTD Template Improvement) Issue: Desire to continually improve regulatory dossiers (e.g. IMPD/IND/MAA/BLA) to reduce effort and risk during the review process. Challenges/Drivers: HA feedback can sometimes vary greatly region-to-region and product-toproduct within a region Some feedback is review-specific, or unique to a regulatory reviewer, or climate (i.e. hot topics ) Dossiers are written by different development teams, each having individuals with different experiences Learning cycle must become shorter i.e. no longer have years between new product marketing applications to make adjustments

18 Improved KM : CTD Template Write Product CTD Submit / Manage Review Questions Dossier Approval Changes in Regulatory Environment, Guidance, Expectations Update Template Shared best practices from within the company through (electronic suggestion box) Update Needed Template errors, clarifications Missing content that we should add Improve Development Approach Categorize HA Questions No Update Needed Reviewer specific or very product specific questions Topics we consider inspectable

19 Business Benefit Examples Improved control strategy content/smoother reviews More integrated approach to control of CQAs Parametric, testing, materials controls, etc. Establish certain CQAs/CPPs based on regulatory expectation Criticality analysis performed on all attributes/parameters But, some parameters are always promoted to CQA or CPP and included formally in control strategy regulatory commitments Subtracted a large amount of redundancy (reduced number of pages)

20 Thank You! Acknowledgements Adam Fermier Strategic Operations Gene Schaefer Large Molecule Development Brandy Pyrcz Dossier Development Chuck Goochee Large Molecule Development

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22 BACKUP SLIDES

23 Recipe Structure: S Bioreactor Stage1 - Setup Operation1 Inoculation - Action1 Materials Equipment Reference Documents Parameters Batch Record - Affinity Chrom Stage2 - - Harvest Operation2 Daily Measures Bind Operation Action2 Action1 Action2 Target Actual (source) Ranges of operation Units Type Comments Version Control + rationale Criticality Assessment Severity Probability Detection Elute - Action1 ANSI/ISA Batch Control Part 1: Models & terminology

24 But what does it look like to Bench Scientist?

25 Interactive Control Panel BSA QC - 2 Missing Data! QC - 3 QC 1 QA Y Intermediate X