Quality by Design The Challenge for Regulators

1. Quality by DesignThe Challenge for Regulators Summary of New Thinking Path for Development of Review Considerations Not yet FDA policy Jon Clark Associate Director for Policy Development Office of Pharmaceutical Science Center for Drug Evaluation and Research, FDA

2. Overview • The traditional system of approval and change control seems burdensome • There should be a way to protect the public without slowing innovation • Methods and standards for this are available • Need to train ourselves into a new way of thinking and working

3. Shared Concerns • The pharmaceutical industry has one of the most technically advanced discovery organizations, but remains more conservative when it comes to using "cutting edge" technology in manufacturing. • Concern over how regulatory agencies will react to technology. • Agency study of potentially inconsequential impact on the product can result in delay.

4. Potential for Contradiction • Commitment to high quality products • with • Commitment to most rapid introduction to market • Inclusion of development data helps, but can not equal knowledge obtained during routine production

5. When to Optimize the Process • Optimization before approval • Greatest cost may be time • No baseline for measuring return on investment • Provides immediate benefit to patient • Continuous improvement • Time element minimized • Enables measured improvement • Feed forward data and scope protocols

6. Points to Consider • Raw Materials • Process • Measurement • Steering the Process • Variability

7. Raw Materials • Pharmaceutical raw materials are variable. • Cannot assume that holding the inputs constant will always produce a constant product. • Ergo: Attempting process control through raw material control is futile.

8. Process • Discovery and Design suggest a process. • You need to measure and model the process then steer it. • The model should be designed so that we can measure the parameters used in the model to control the process. • As the model evolves measurement strategy evolves with it. • There is a lack of process models in applications

9. Measurement • Measurement is most effective when used to control the process in “real time”. • Traditional approach has been to sample the process and product, then test for compliance with criteria.

10. Steering the Process • Change times, speeds, temperatures based on measurement to achieve target value for a product parameter. • Discarding batches or portions of batches reveals failure to steer the process.

11. Variability • Variability reduction adds value • increases process capability • minimizes the risk of OOS

12. Situation Spectrum High Process Understanding and Control No Need for End Product Testing Extensive Product Testing Little Process Understanding Increasing Desirability

13. Therefore • FDA focus on Laboratory Testing is not ideal for controlling a process • Need to encourage Process Understanding and Engineering • Focus resources on the manufacturing process instead of lab tests and criteria • Avoid heuristic trap • Don’t measure it just because you can

14. Need for Generic Rules Based Regulatory Control Increasing Process Understanding and Control Need for Generic Rules Based Control

15. Growth of Knowledge and Process Understanding Putative Post Approval Regulation Increasing Continuous Improvement

16. Manufacturing Process Locked Process Variables Current Paradigm Variability Raw Material Product

17. Dynamic System Manufacturing Process Raw Material Product Endpoint Response Input Response Measurement Dependant Process Variables

18. P A TProcess Analytical Technology Manufacturing Process Raw Material Product Feedback Feed Forward Critical Process Parameter (CPP) adjusted by measurement of Critical Quality Attributes (CQA)

19. We are not AloneMIL-STD-1916 dated 1996 • “Process controls and statistical control methods are the preferable means of preventing nonconformances, controlling quality, and generating information for improvement.” • “Sampling inspection by itself is an inefficient industrial practice for demonstrating conformance to the requirements of a contract and its technical data package.” • “To the extent that such practices are employed and are effective, risk is controlled and, consequently, inspection and testing can be reduced.”

20. More • “The objective is to create an atmosphere where every noncompliance is an opportunity for corrective action and improvement rather than one where acceptable quality levels are the ... goals.” • “The goal is to support the movement away from a [product] inspection strategy to … effective prevention-based strategies including a comprehensive quality system, continuous improvement and partnership with Government.”

21. And More • Process focus of quality system • Consistently producing conforming product. • Controlled as far upstream as possible. • Robust to variation…. • Operated to constantly reduce variation. • Utilization of equipment in a way that minimizes variability around target values • Managed for continuous improvement • Designed and controlled using a combination of practices and methods in order to ensure defect prevention and process improvement.

22. Product Sampling and QualityDr. W. Edwards Deming • "Cease dependence on inspection to achieve quality. Eliminate the need for inspection on a mass basis by building quality into the product in the first place." • "Depending on inspection is like treating a symptom while the disease is killing you. The need for inspection results from excessive variability in the process. The disease is variability.” • "Ceasing dependence on inspection means you must understand your processes so well that you can predict the quality of their output from upstream activities and measurements."

23. Target Critical Quality Attributes CQA Range Process Designed to Limit Product Variability Range of Raw Material and Facility Attributes

24. What Might FDA Reviewer See?Anna Thornton “Variation Risk Management” • Identification • Key Characteristics (KC) • Variation “Flowdown” • Assessment • Which variations put CQA at risk • Mitigation • Eliminate source • Reduce impact

25. Key CharacteristicsInjection Delivery Device • Leaks • Contamination in fluid path • Contamination outside fluid path

26. Variation FlowdownContamination IN Path • Tube • Luer lock • Needle • Common Sources • Supplier • Handling • Adhesive

27. Variation FlowdownContamination Outside Fluid Path • Needle • Tube • Luer lock • Roller clamp • “Wings” or other handles

28. Variation FlowdownLeaks • Cracked needle base • Cracked luer lock • Unsealable luer lock • Flash • Diameter • More...

29. Variation FlowdownMore Leaks • Leak in Joints • Needle tube connection • Tube luer lock connection • UV cure time • Adhesive application • Correct diameters

30. Examples of evidence regarding process improvement • Process flow charts showing the key control points for action to prevent defective product • Identification of process improvement techniques… • Identification of measures used, e.g., trend analysis • Results of improvements from using these… • Results of experiments that led to reduced variability...

31. Examples of evidence regarding process control • Identification of the scope of use of process control techniques… • Process control plans, including improvement goals… • Approaches and supporting data used to determine if suppliers have adequate controls… • Descriptions of the required training … • Identification of departmental interrelations • Rationale for establishing subgroups • Identification of key parameters used in lieu of specified characteristics • More...

32. Examples of evidence regarding process control :continued: • Identification of personnel responsible for process related corrective action. • Proper gage measurement studies showing measurement variations relative to total variation. • Traceability of the product and process corrective action(s) taken when the process went out of control, showing how the root cause was identified and eliminated.

33. Examples of evidence regarding product conformance • Control chart showing the process in statistical control in accordance with the criteria… • Records of product and process corrective action(s) taken when nonconformances occur. • Process capability studies consisting of correct calculation and interpolation of [attribute measures] • History of product inspection results reinforced by statistical data and analysis. • Results from in-process control methods, such as [automation applications]

34. Experience and Quality System • Institutionalization of Knowledge is a Quality Concern • Need to apply “solutions” wherever they provide improvement • Prior regulatory approval for every improvement defeats this goal

35. Research Data • Agency acknowledges concern that process research data may indicate a problem when the product still meets its approved release methods. • FDA began using a "research data exemption" concept in several guidance documents. • Doesn’t protect one that knowingly does harm without attempting mitigation. • This is designed to place research information outside the scope of a “normal” inspection. • Shouldn’t impact on the ability to release products that meet all aspects of the company's current registered quality control strategy.

36. Organization of CMC Staff • Current attachment to Clinical Staff doesn’t seem ideal • We are studying the best way to organize them • Training specific to new technologies and philosophies is needed • Supplement change control process needs work

37. Situation Spectrum High Process Understanding and Control No Need for End Product Testing Extensive Product Testing Little Process Understanding Increasing Desirability

38. End Thank you