Critical Path Initiative: Challenges and Opportunities

1. Critical Path Initiative: Challenges and Opportunities Ajaz S. Hussain, Ph.D. Deputy Director, Office of Pharmaceutical Science, CDER, FDA 19 October 2004 ACPS Meeting

2. CDER Goals: 2005 State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

3. What is Critical Path? • A serious attempt to examine and improve the techniques and methods used to evaluate the safety, efficacy and quality of medical products as they move from product selection and design to mass manufacture. State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

4. Translational Research Critical Path Initiative March 2004: www.fda.gov/oc/initiatives/criticalpath/whitepaper.pdf

5. Critical Path Document (March 2004) • The drug development process – the “critical path,” is becoming a serious bottleneck to delivery of new medical products State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

6. R&D Spending

7. But, New Product Submissions Have Remained Flat * for NMEs submitted prior to 1992, type A and type B applications are counted as Priority review and type C applications are counted as Standard review.

8. Why FDA Concern? • FDA Statutory Mission -- Not only to protect but also to advance public health by improving availability of safe and effective new medical products State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

9. FDA Has Unique Role in Addressing the Problem • FDA scientists are involved in review during product development -- they see the successes, failures, and missed opportunities • FDA not a competitor, can serve a crucial convening and coordinating role for consensus development between industry, academia and government • FDA sets the standards that innovators must meet. New knowledge and applied science tools needed not only by innovators – must also be incorporated into agency review State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

10. How to Proceed: Science-Driven Shared Effort • Drawing on available data, need to target specific, deliverable projects that will improve drug development efficiency • Not just an FDA effort – we can identify problems & propose solutions – solutions themselves require efforts of all stakeholders • CMS, NIH, CDC • Federal Register Notice requesting comments, Well over 100 written responses to date. State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

11. CDER/ FDA Next Steps on Critical Path • HHS Medical Technologies Innovation Taskforce providing broad leadership • Chaired by Dr. Crawford • Includes CDC, CMS, NIH and FDA • Work on addition funding…. • Meetings with external stakeholders to identify opportunities, enlist allies State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

12. Critical Path Summary • Present state of drug development not sustainable • FDA must lead effort to question any assumptions that limit or slow new product development: • Are they justified? • Are there more efficient alternatives? • If so, why are the alternatives not being utilized? State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

13. Three Dimensions of the Critical Path • Assessment of Safety – how to predict if a potential product will be harmful? • Assessing Efficacy -- how to determine if a potential product will have medical benefit? • Industrialization – how to manufacture a product at commercial scale with consistently high quality? State of CDER 2004; Steven Galson & Doug Throckmorton October 6, 2004

14. Applied Science Needed to Better Evaluate and Predict on 3 Key Dimensions on 'Critical Path' of Development

15. OPS Programs & Critical Path Initiative • The discussion today is to seek input and advise from ACPS on: • Aligning and prioritizing current OPS regulatory assessment and research programs • Note that all research and laboratory programs are not intended to be focused on the “Critical Path” • Identify gaps in the current programs • Identify opportunities for addressing the needs identified by the Critical Path Initiative

16. Planned Project in the OPS Immediate Office • An immediate need is to ensure appropriate support • Generic Drugs - the growing volume and complexity of applications • New Drug Chemistry - their new paradigm for review assessment and efforts to support innovation and continuous improvement goals of the CGMP Initiative • Biotechnology Products – complete integration in OPS and the evolving concept of "Follow-on Protein Products • Alignment of research programs in OPS

17. OPS IO: Critical Path Initiative Project Proposal • To develop a common regulatory decision framework for addressing scientific uncertainty in the context of complexity of products and manufacturing processes in Offices of New Drug Chemistry, Biotechnology Products, and Generic Drugs

18. Motivation • Uncertainty (stochastic and epistemic) and complexity are two important elements of risk-based based regulatory decisions • A common scientific framework, irrespective of the regulatory path or process for these products, will provide a basis for efficient and effective policy development and regulatory assessment to ensure timely availability of these products.

19. Approach • There are no good methods available for developing a standard approach for addressing uncertainty; different approaches will be required in different assessment situations. • Therefore, a decision framework for selecting an approach for addressing uncertainty over the life cycle of products is proposed.

20. Project #1 • Create the "As Is" regulatory decision process map for ONDC, OBP, and OGD • a representative sample of product applications will be selected for this mapping process

21. Project #1: Steps • Determine regulatory process efficiency and effectiveness (quality) using metrics similar to that of manufacturing process • Identify and compare: • Critical regulatory review decision points and criteria • Evaluate correlation and/or causal links between review process efficacy metrics and critical decisions criteria, and available information (in submissions), and • Evaluate the role of reviewer training and experience

22. Project #1: Steps (Contd.) • Summarize available information on the selected products • Collect and describe product and manufacturing process complexity, post-approval change history, and compliance history (including AER's) • Describe product and process complexity and uncertainty with respect to • Current scientific knowledge (mechanism of action, critical variables, analytical methods, failure modes, etc.) • Information available in the submissions, • Reviewer expert opinions and perceptions • If feasible/possible, seek similar information from sponsor/company scientists on these same products

23. Project #1: Deliverables • Organize OPS Science Rounds to discuss and debate the "As Is" process map and the knowledge gained • Identify "best regulatory practices" and opportunities for improvement • Opportunities for improvement to include knowledge gaps • Develop a research agenda for OPS laboratories • Develop a common scientific vocabulary to describe uncertainty and complexity • Develop an "ideal" scientific process map for addressing uncertainty and complexity • Adapt the "ideal" scientific process map to different regulatory processes

24. Project #2: Background • Without a systems approach to the entire regulatory process; from IND to NDA (BLA, ANDA) review and approval, to phase IV commitments and CGMP inspections, the broad FDA goals under the CGMP and the Critical Path Initiatives will not be optimally realized.

25. Project #2: Background • The team approach and systems perspective under the CGMP Initiative only addressed a part of the pharmaceutical system. • Quality by design and process understanding to a large extent is achieved in a Research and Development organization. • Pharmaceutical product development is a complex and a creative design process that involves many factors, many unknowns, many disciplines, many decision-makers, and has multiple iterations and long life-cycle

26. Project #2: Background • Significant uncertainty is created when a particular disciplinary design team must try to connect their subsystem to another disciplinary subsystem (e.g., Clinical-CMC-CGMP). • Each subsystem can have its own goals and constraints that must be satisfied along with the system-level goals and constraints. • It is possible that goals of one subsystem may not necessarily be satisfactory from the view of other subsystem and design variables in one subsystem may be controlled by other disciplinary subsystem.

27. Project #2 • Using ICH Q8 as the bridge between the CGMP Initiative and the rest of the regulatory system seek to develop a knowledge management system to ensure appropriate connectivity and synergy between all regulatory disciplines (Pharm/Tox, Clinical, Clinical Pharmacology, Biopharmaceutics, Bioequivalence, CMC, Compliance, CGMP Inspections, Drug Safety,..)

28. Project #2: Approach • ICH Q8 CTD-Q Pharmaceutical Development, P2 Section • Each section within P2 can have an impact on the other P2 sections and similarly other sections of a submission and to CGMP’s • By recognizing this as a complex design system that involves multiple attributes, goals, constraints, multidisciplinary design teams (subsystems), different degrees of uncertainty, risk tolerance, etc., we wish to find opportunities to identify robust designs and design space that provides a sound basis for risk assessment and mitigation

29. Project #2: Approach • A significant body of knowledge exists (e.g., in mechanical engineering - design of aircrafts) that addresses this challenge; for example: • Koor, I., Altus, S., Braun, R., Gage, P., and Sobieski, I. Multidisciplinary Optimization Methods for Aircraft Preliminary Desing. AIAA Paper 94-4325, 5th AIAA/USAF/NASA/ISSMO Symposium, Sept. 1994 • Balling, R.J. and Sobieski, J. An Algorithm for Solving System-Level Problem in Multilevel Optimization.;Structural Optimization 9: 168-177 (1995) • Kalsi, M., Hacker, K., Lewis, K. A Comprehensive Robust Design Approach for Decision Trade-Offs in Complex System Design. J. Mechanical Design. 123 (2001)

30. Project #2: Approach • The applicability of multidisciplinary optimization methods for solving system level problems and decisions trade-offs will be explored for the NDA review process • For example in the CDT-Q P2 section: Critical drug substance variables that need to be considered in section 2.2.1 Formulation Development are described in section (P2.1.1.) • P2.1.1. Drug Substance: “Key physicochemical and biological characteristics of the drug substance that can influence the performance of the drug product and its manufacturability should be identified and discussed.

31. Project #2: Approach • Let f(2.1) be the objective function of section of section P2.2.1.Formulation Development it describes the desired quality and performance attributes to be achieved by formulation development program ( mean of the objective function and  its standard deviation) • Let g(2.1.) be the constraints placed on formulation development • The subsystem optimization problem is then defined as:Find X(2.1.) to achieve the objectives of this subsystem as it relates to the overall system • Minimize [f, f] • Subject to a given constraint g(1.1.,..2.1.,..)

32. API Manufacturing Process or Quality control unit X(1.1) f(1.1) g(1.1) f(2.1) g(2.1) X(2.1) Y(1.1)(2.1) 2.1.1 Drug Substance 2.2.1 Formulation Development Y(2.1)(1.1) Y(1.1.)(*.*) Y(*.*.)(1.1.) Y(2.1.)(*.*) Y(*.*)(2.1) X(2.1) = Design Variables for the P2 section (2.1) Y(1.1)(2.1) = Linking variable that are evaluated in section (1.1) and required in section (2.1) as the input f(2.1) = Objective function addressed by section (2.1) g(2.1) = Constraints in section (2.1) f= Mean of objective function f f= Standard deviation of objective function f X= Deviation range of design solution (a design space boundary)

33. Potential Deliverables • In conjunction with electronic submissions this project can potentially provide a means to • Link multidisciplinary information to improve regulatory decisions (e.g., clinical relevance of CMC specifications) • Creating a means for electronic review template and collaboration between different disciplines • Provide a common vocabulary for interdisciplinary collaboration • Create an objective "institutional memory' and knowledge base • A tool for new reviewer training • A tool for FDA's Quality System • Connect the CGMP Initiative to the Critical Path Initiative

34. Project #3 • Explore the feasibility of a quantitative Bayesian approach for addressing uncertainty over the life cycle of products • The most common tool for quantifying uncertainties is probability. The frequentist's (including classical statisticians) define probability as a limiting frequency, which applies only if one can identify a sample of independent, identically distributed observations of the phenomenon of interest.

35. Project #3 • The Bayesian approach looks upon the concept of probability as a degree of belief and include statistical data, physical models and expert opinions and it also provides methods for updating probabilities when new data are introduced. • The Bayesian approach may provide a more comprehensive approach for regulatory decisions process in dealing with CMC uncertainty over the life cycle of a product. • It may also provide a means to accommodate expert opinions. The evolving CMC "peer review" process may be a means to incorporate expert opinions. • Using the information collected in Project #1 seek to develop quantitative Bayesian approaches for risk-based regulatory CMC decisions in OPS

36. OPS Programs & Critical Path Initiative • Other OPS programs – I/O, OBP, ONDC, OGD, and OTR • The discussion today is to seek input and advise from ACPS on: • Aligning and prioritizing current OPS regulatory assessment and research programs • Note that all research and laboratory programs are not intended to be focused on the “Critical Path” • Identify gaps in the current programs • Identify opportunities for addressing the needs identified by the Critical Path Initiative