Learning from the Application of Real-Time Analytics for Process Understanding, Control and Real-Time Release Testing

Transcription

1 Learning from the Application of Real-Time Analytics for Process Understanding, Control and Real-Time Release Testing Ruben Lozano, Douglas Both and Ambarish Singh Bristol-Myers Squibb Biopharmaceutics Process Analytical Sciences New Brunswick, NJ April 23, 2013

2 Outline QbD, PAT, RTR and Control Strategies Application of NIR method at tablet pre-blending step Feedback from Health Authorities Application of NIR at tablet compression step, and acceptance criteria based on Large-N test approach Feedback from Health Authorities General feedback from HAs on QbD/PAT prior to filing CMC filing strategy in support of PAT/RTRt(Real-Time Release testing)

3 QbD-Based Development 1. Based on initial assessment, develop a Target Product Profile (TPP):the desirable quality attributes of the product from patient s perspective (safety and efficacy) 2. Determine Critical Quality Attributes (CQA) of drug product, which assure safety and efficacy 3. DevelopProcess Understanding / Knowledge on how CQAs are impacted by variations in raw material attributes (excipients, drug substance) and manufacturing process parameters 4. Conduct Risk Assessment on input materials and manufacturing process parameters: identify Critical Process Parameters (CPP)

4 QbD-Based Development 5. Design and implement a Control Strategy: process controls, PAT, operating parameters, specifications, etc. 6. Design Space: multidimensional combination and interaction of input variables (e.g. material attributes) and critical process parameter that assures product quality 7. Continual Improvement: product life-cycle management through product and process knowledge and quality risk management

5 Control Strategy A control strategy is based on a quality risk assessment of product and process. CQAs are identified and tested, then critical parameters are controlled (or monitored). Results: Greater understanding of sources of variability and their impact on CPPs that could impact product quality. Elimination or minimization of that variability. In-line monitoring and holistic risk-based control strategy have the potential to reduce end-product testing.

6 Real-Time Release (RTR) Strategy RTR is a system of release that gives assurance that the product is of intended quality based on in-process data, enhanced process understanding, and a control strategy Allows for a comprehensive set of in-process controls, RTR testing, RTRt) that provide greater assurance of product quality than end-product testing

7 PAT Opportunities in Manufacturing of Oral Solid Dosage Drug Products Drug Substance and Excipients Input material control: API particle size, bulk density, flow, impurities, ID (NIR) Pre-Blending Blending end point (NIR) Drying end point for wet granulation (NIR) Roller Compaction/Granulation Final Blending Tableting (core) End point (NIR) Potency, Content Uniformity (NIR) Appearance (NIR Imaging) ID (NIR) Finished Product(coated) ID (NIR, Raman)

8 PAT Application: NIR Control of Pre-Blend Real-time in-line measurement of the drug concentration provides a profile as the drug blends with the other tablet ingredients. Blending step will operate within the verified ranges Algorithm runs in real time and determines end point The blender stops when the blend uniformity is reached as per the pre-set criteria Monitor blend uniformity Initialize algorithm START BLENDER Blend until blend endpoint is achieved

9 In-Line NIR for Pre-Blend Feedback and Control API % Concentration Blender Rotations Operator: - Executes spectrometer suitability test - Executes spectrometer blend software - Starts blender - Observes computer display for end of blend - Stops blender - Executes spectrometer suitability test

10 NIR Blend Control: High-Level Decision Tree NIR preblend-1 blend endpoint criteria met? No Go to 600 revolutions Yes Investigate Go to next manufacturing step Go to next manufacturing step Yes Root cause identified and no impact to quality Based on outcome of investigation, go to next manufacturing step or reject batch No

11 HA Feedback on NIR Pre-Blend Control (1/2) Acceptable to HAs after satisfactorily responding to the queries during HA review and PAI. Queries on method development, validation and site-implementation Queries on BMS way of preparing the calibration/validation standards (gravimetric vs. HPLC reference) Queries on why NIR method was NOTdeveloped and validated by comparing it with the thief sampling data During the PAI, further discussion on the merits of thief sampling of the commercial blend as confirmatory test BMS justified that thief sampling was not appropriate for pre-blend step due to technical feasibility and potential segregation during thief sampling..but, committed to providing thief sampling data (after NIRbased blending end-point reached) on the first commercial batches

12 HA Feedback on NIR Pre-Blend Control (2/2) Confirm 600-revolution limit at scale; done during validation Some HAs questioned the accuracy of the method and did not appreciate the fact that a pre-blend method need not be as accurate as a tablet NIR method to be fit for purpose : Uniformity vs. absolute concentration..while some other HAs were more understanding and appreciated that a process control was in-place as opposed to blindly going to a fixed number of revolutions

13 PAT Application: Tablet Potency and Content Uniformity by NIR Allows for testing of large number of tablets (>100) collected throughout the compression run compared to the pharmacopeialnorm of testing 30 (10 + additional 20) tablets for potency and content uniformity Providesa better assessment of the batch qualitydue to the larger number of samples tested Allows for effective trending of inter/intra-batch variation and continued process verification

14 Large N Test: Modifed PhRMA Approach Bergum, Vukovinsky (Pharm.Tech., Nov 2010, 72-79) Collect N Dosage Units One-stage counting test Count number of results (C) outside 85% to 115% LC Express Result as % LC Criteria: C 0.03*N C s for Selected N s: # Tablets outside (85,115) %LC C? N C No Reject Batch Yes Pass Batch

15 Tablet NIR Method Development: Risk Analysis

16 HA Feedback on Tablet NIR Method and Large-N Approach Acceptable to several HAs after satisfactorily responding to the queries during HA review and PAI: Queries on method development, validation, method transfer and site-implementation. Queries on method robustness: Were all the parameters that could potentially impact the NIR method taken into account during method development/validation? In-depth review of decision trees during the PAI. Queries on when the alternate HPLC method would be used. Large-N approach: Queries on sampling intervals.

17 General CMC Feedback on QbD/PAT Prior to Filing: Major-Market HAs Health Authority Interactions: CMC specific face-to-face meetings with major health authorities are critical to the success of introducing NIR/RTRt HA Feedback: QbD-based filing and application of PAT is encouraged Include alternate traditional testing methods as back-up Acceptance of NIR/RTRtin the initial filing with limited commercial-scale experience could be challenging Mitigation: Include multiple batch data in the dossier Demonstrate correlation between NIR and traditional methods Continue with parallel testing to build the experience base Large-N acceptance criteria for content uniformity will be a review item

18 General CMC Feedback on QbD/PAT Prior to Filing: Emerging-Market HAs Limited opportunity for face-to-face meetings with HAs of emerging markets. Feedback is based on the advice from the local country office. Feedback Most of the emerging-market countries do not require full Mod 3 as the NDA or MAA Inclusion of PAT/RTRt can significantly increase the review time The concept of QbD/PAT is relatively new Mitigation: Present QbD/PAT information and overall control strategy that supported the RTRt Local testing requirement diminishes the value of RTRt(HPLC testing needed)

19 CMC Filing Strategy in Support of PAT/RTRt In the Pharmaceutical Development Section, provide a clear link between the development work, risk assessment, control strategy, and specifications to support RTRt. Provide adequate information regarding the NIR instrument and the method including data demonstrating robustness of the NIR method. Demonstrate correlation between NIR and the alternate (HPLC) results and include the details of the alternate method. Include information on when the NIR will be used to support RTRt and when traditional method will be used to support investigation/local release/market-life stability.

20 Conclusions Face-to-Face discussion with HAs is critical to the success of PAT/RTRt acceptance Educate the local country personnel on new concepts Major markets and several emerging markets are receptive to QbD/PAT-based applications

21 Acknowledgements Analytical & Bioanalytical Development - Biopharmaceutics Process Analytical Sciences Group Douglas Both Pankaj Shah John Bobiak Dongsheng Bu Claudia Corredor Gary McGeorge Dimuthu Jayawickrama Ruben Lozano Kevin Macias Tim Stevens Boyong Wan Yan Zhang Pharmaceutical Development Yolanda Caringal Alby Irizarry Jingpin Jia Scott Miller Prakash Parab Jatin Patel Omar Sprockel Elena Zour (James Bergum) Global Manufacturing & Supply Carmen Lopez Amir Razaghi (Frances Montes) Global Regulatory Sciences- CMC Mark Rosolowsky Ambarish Singh Chandra Vema-Varapu (David Ziering)