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

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

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. NMEs Filed by Fiscal Year
0
10
20
30
40
50
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
NumberFiled
Priority Standard
* 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.
But, New Product Submissions
Have Remained Flat

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. 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)
2.1.1 Drug Substance
2.2.1 Formulation
Development
X(1.1) f(1.1) g(1.1)
Y(1.1)(2.1)
X(2.1) f(2.1) g(2.1)
Y(1.1.)(*.*)
Y(*.*.)(1.1.)
Y(2.1)(1.1)
Y(*.*)(2.1)Y(2.1.)(*.*)
API Manufacturing Process
or Quality control unit

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