ISPE Annual Meeting 29 October 1 November 2017 San Diego, CA. FDA Perspective on the Use of Process Capability

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1 FDA Perspective on the Use of Process Capability Chunsheng Cai, Ph.D. Office of Process and Facilities Office of Pharmaceutical Quality, CDER, FDA 2017 ISPE Annual Meeting & Expo Disclaimer This presentation reflects the views of the presenter and should not be construed to represent FDA s views or policies

2 Process Capability vs. Process Robustness A robust process results in high process capability Inputs Full variability explored Robust process Product: low variability (High capability) BUT A less robust process may also result in apparently high capability Inputs (limited sources) Full extent of variability not considered Limited variability explored Less robust process Product: appears low variability (High capability) 3 Challenges in Process Review We would like to see consistent product quality over lifecycle A robust process is desired Data is limited (not much production) Development and stability batches (mostly pilot scale) Possibly even fewer data are submitted limited scope to evaluate batch to batch variation Process capability not yet established To evaluate if the proposed commercial process is adequate, we gather the information on Prior experience Input variability considered during development Process understanding Scale up 4 2

3 Process Design Expectation in pharmaceutical development Adequate knowledge and understanding is demonstrated Functionality and limitations of commercial manufacturing equipment should be considered in the process design Predicted contributions to variability (different component lots, production operators, environmental conditions, and measurement systems) QbD is encouraged: Design of Experiment (DOE) can help develop process knowledge by revealing relationships, including multivariate interactions Strategy for control (based on your learning) Reduce input variation Adjust for input variation during manufacturing 5 Source of Variability Raw Chemicals Raw materials Operating conditions Process equipment Environmental conditions Human factors Drug Synthesis Suboptimal API Properties Formulation Unknown Manufacturability Process Development Unknown Scalability Scale/up Tech Transfer Unknown Robustness Manufacturing Lifecycle Management 6 Courtesy: A. Khairuzzaman 3

4 Process Design Considerations Goal: to develop a robust process Conduct study during process development / optimization Establish PAR, NOR for process parameters Include variability in materials and process parameters Materials (chemical, physical) Reasonable variability included in design Different lots might not be sufficient, may consider different suppliers Identify the process parameters that the process is sensitive to The variability of such parameters should be controlled during production 7 Process Design Considerations (cont.) DOE considerations Process and product development are usually together Process development should cover the component variation range One common approach is material amount adjustment based on assay (e.g., for material dispensing or capsule filling) OK for small adjustment. If the adjustment is large, the variation should be evaluated as part of DOE Too large adjustment might represent different formulation 8 4

5 Screening DOE first Example 1: DOE 11 variables (After initial risk assessment), 13 runs High drug load, uniformity is not a concern Response: dissolution 9 Example 1: DOE (cont.) Screening DOE identified 4 critical factors Another DOE for further optimization 4 factors, 24 runs PAR established

6 Process Capability Analysis Cpk uses Sigma estimator (Ppk uses standard deviation), a common way is Specifications (LSL, USL) are from user requirements 11 Example 2: Process Capability Use in Unit Process Development CPK used in a compression process

7 Example 2: Process Capability Use in Unit Process Development (cont.) CPK used for evaluation of tablet WHT Very high CPKs Appropriate specification? 13 Process Qualification Expectation Scale up / Transfer: Maintain the process capability Process Performance Qualification (PPQ) Commercial process setting, milestone in the product lifecycle Higher level of sampling, additional testing, and greater scrutiny of process performance Statistical methods to be used in analyzing all collected data (e.g., statistical metrics defining both intra batch and inter batch variability)

8 After Commercialization Continued Process Verification After establishing and confirming the process, manufacturers must maintain the process in a state of control over the life of the process, even as materials, equipment, production environment, personnel, and manufacturing procedures change. We recommend that the manufacturer use quantitative, statistical methods whenever appropriate and feasible Thoughts to Improve Process Capability For some high risk processes, consider PAT to monitor and control Data may be available in the existing processes what is needed is the data analysis Data mining allows process improvement Data modeling for process end point detection and control Long bioprocess Comparing process trajectory with historical production Multivariate data analysis (MVA) to identify parameters that need further control Many processes are data rich MVA model to generate a single outcome for trending MSPC (PCA based)

9 Summary We encourage a QbD approach DOE for process understanding and for a robust process, to improve process capability Robust process would benefit both company and agency, eventually patients Process capability analysis is a good statistical approach to measure process robustness Based on well controlled variability and with appropriate specifications Can be used for unit operations, and batch to batch consistency assessment Use with caution Reasonable variability and specification 17 Reference FDA Guidance for Industry Q8(R2) Pharmaceutical Development (Nov 2009) FDA Guidance for Industry Q10 Pharmaceutical Quality System (Apr 2009) FDA Guidance for Industry Process Validation: General Principles and Practices (Jan 2011) L.X. Yu, M. Kopcha: The future of pharmaceutical quality and the path to get there, International Journal of Pharmaceutics 528 (2017)

10 Acknowledgement Akm Khairuzzaman, Ph.D. Rapti D. Madurawe, Ph.D. Questions?