QbD PAT Pharmaceutical Equivalence Therapeutic Equivalence by mikeholy

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									ACPS Meeting, May 2005


 Basis of the Proposed Tactical Plan for
 a QbD approach for Quality Control
 and Assurance of Dissolution Rate

        Ajaz S. Hussain, Ph.D.
        Deputy Director, Office of
        Pharmaceutical Science, CDER, FDA


                                            1
Topic #1 ACPS Discussion Goals
   Seek ACPS recommendations on a proposed regulatory
    tactical plan
       QbD based regulatory decision system for quality assurance and
        control of optimal drug dissolution rate over the life cycle of a
        product
            Are the tactical steps outlined consistent with the QbD goals we
             seek to achieve?
            What additional steps and/or changes would you recommend to
             improve this plan?
            What additional scientific evidence is necessary to support the
             development and implementation of this plan?
            General considerations for identifying and developing statistical
             procedures
            Any other specific recommendations?
                Prioritization?




                                                                                 2
Proposed Steps
   Alternate regulatory approach – suitability of
    dissolution measurement system
   Gauge Reproducibility and Repeatability Study Using
    Pivotal Clinical or Bio Lot
   Systems-based decision tree or establishing
    dissolution rate specification
   Opportunities for utilizing the PAT approach for
    controlling dissolution rate and development of real
    time quality assurance strategies
   Decision tree for “design space” concept articulated in
    the draft ICH Q8
   Develop a side-by-side comparison New and Generic
    Drugs and explain why the level of QA/QC confidence
    in the proposed approach should be higher than what
    is achieved under the current system

                                                              3
Proposed Steps
   Seek ACPS recommendation at the May 2005
    meeting on general considerations for identifying
    and developing statistical procedures

   Develop a detailed proposal for a subsequent
    meeting of the ACPS

   Seek harmonization on the approach with other
    regulatory authorities (starting with ICH Q8 Part
    2)


                                                        4
What do we intend to accomplish?
   Improve our ability to identify sources and
    types of variability and ensure QbD
       Obtain robust estimates for use in regulatory
        decisions
           Regulatory specifications and in-process controls
           For assessment of adequacy of proposed material and
            manufacturing process control strategies
           Facilitate assessment and communication of
            technology/knowledge transfer and assurance of “state
            of control” in production operations
           Provide regulatory flexibility for continuous improvement


                                                                        5
Inspiration for the proposal ….




                 http://www.ge.com/sixsigma/SixSigma.pdf
                                                           6
The Pharmaceutical Quality: Challenges
and Opportunities

                                                                   Quality – Clinical Gap!

                                                            CMC & CGMP Commitments*

                                                                       CMC – CGMP Gap*

                                                                        “Market Failure”!

                                                           “Corrective Actions” the only *
                                                    leverage for continuous improvement

                                                          Specification – Capability Gap*

http://www.ge.com/sixsigma/SixSigma.pdf

                                          *Opportunity for continuous improvement*
                                                           Challenges to overcome!


                                                                                      7
 Tactical Step #1
                           Measurement System Suitability
                            Alternate Suitability Method
                        Focusing on Mechanical and Media Factors


 Step# 2 Gauge R&R (pivotal clinical or bio lot)
                                                         Information collected
Analysis of Variance        Pivotal Clinical Lot for
                                                           should facilitate a
                            GR&R* Considerations
     Apparatus                                          shift from deterministic
                               Pharmaceutical          to a probabilistic design
    Disso. Media                                                 culture
                                Development
      Operator
                                   Stability
 Pivotal Clinical Lot
                                   Sampling
Design of Experiment
                             [Currently Marketed
                                 Products?]

                                                                                   8
Tactical Step #2: Gauge Reproducibility and
Repeatability Study Using Pivotal Clinical or
Bio Lot
     Gauge R&R (pivotal clinical or bio lot)

 Analysis of Variance       Pivotal Clinical Lot for
                            GR&R Considerations
     Apparatus
                               Pharmaceutical
    Disso. Media
                                Development
      Operator
                                   Stability
 Pivotal Clinical Lot
                                   Sampling
Design of Experiment                                     Information collected
                              Currently Marketed           should facilitate a
                                  Products?             shift from deterministic
                                                       to a probabilistic design
                                                                 culture


                                                                                   9
Considerations for Decision Trees: Steps
# 3-5
   Ask the “right questions”
   Begin with end in mind – Intended use
   System based (connecting the key disciplines and
    regulatory submission sections)
   Facilitate structured product development process,
    yet not dictate a specific process
   Leverage pre-approval changes & “bridging studies”
   Cumulative – and support use prior knowledge
   Scientific hypothesis format
       For example …….the following several slides are for
        illustration purposes

                                                              10
Quality – Clinical Gap: Uncertainty
Leslie Z. Benet, Ph.D. ACPS Meeting April 14, 2004

    “The Current U.S. Procrustean Bioequivalence (BE) Guidelines”
      The manufacturer of the test product must show using two
        one-sided tests that a 90% confidence interval for the ratio
        of the mean response (usually AUC and C max) of its product
        to that of the reference product is within the limits of 0.8
        and 1.25 using log transformed data.
           (Procrustean  marked by an arbitrary, often ruthless disregard for individual
            differences or special circumstances.)
           Note: BCS is a non-Procrustean advance
           We should consider other non-Procrustean advances


                                                                 “Most discriminating”
                                                                   (Risk Mitigated)

        Product specifications based on mechanistic understanding
    of how formulation and process factors impact product performance
                                                                    11
Additional Challenge: Uncertainty Management
Without Pharmaceutical Development Knowledge

   Focus on “discriminating” test
       Often a “shot gun” approach (e.g., 3-5 different
        dissolution media focus on pH)
           Considered necessary to find the “most discriminating”
            pH (often could be predicted from physico-chemical
            properties and formulation design)
       In practice, a frequent tendency is to utilize 0.1 N
        HCl
           From “in vivo” relevance perspective
       Quality assurance Vs. In vivo relevance debates

                                                                     12
Mechanistic Understanding? Build on
ICHQ6A Concept
   For example – “Particle size distribution testing may
    also be proposed in place of dissolution testing
    when development studies demonstrate that particle
    size is the primary factor influencing dissolution;
    justification should be provided.”
           ICHQ6A 3.3.2.3 Parenteral Drug Products
   Mechanistic understanding – identification and
    scientific justification of causal physical or chemical
    relationships between pharmaceutical materials
    and/or process factors
       Note – establishment of “correlation” between two
        characteristics may not always be causal

                                                              13
Specifications, Standards and Control
Limits                    If, Specification = Standards
                                       (no room for risk based decision)
   Specification =
    Standard
       Non-conformance
        rejection or recall
   Control limit
       Target value
       Common cause
        variability
   Alert limit
       Potential “Special
        cause” – investigate, if
        take necessary action to
        prevent OOS
                                   Control Limit
                                                         Alert Limit

                                                                           14
Step # 6: General Considerations for Identifying
and Developing Statistical Procedures
   Routine production
       Control charts of variables (not attributes)
           Target value +/- Upper and Lower Limits
       Process capability analysis
       Not “hypothesis testing” on every lot
   Validation, Specification and Standard
       Hypothesis testing
       Parametric or non parametric tolerance interval
           For example: To assure the dissolution quality by controlling
            the percentage P of the lot with dissolution greater than Q can
            be set up by testing the following hypotheses
               H0: Pr(X  Q)  P vs. Ha: Pr(X  Q) > P
                  Yi Tsong and Meiyu Shen, Office of Biostatistics, CDER, FDA
                   (FDA Science Forum 2005)


                                                                                 15
Topic #1: Questions to ACPS

   Are the tactical steps outlined consistent with the
    QbD goals we seek to achieve?
   What additional steps and/or changes would you
    recommend to improve this plan?
   What additional scientific evidence is necessary to
    support the development and implementation of this
    plan?
   General considerations for identifying and
    developing statistical procedures
   Any other specific recommendations?
         Prioritization?

                                                      16
Why have we not used it in our decision
process?
   The challenge of “destructive test” – i.e., test sample is
    destroyed

   Hesitancy - variability of units in a pivotal clinical batch
    to be used – assuming or declaring this as
    “acceptable”?

   Organizational gaps – awareness of these issues

   A potential paradoxical scenario when dissolution test
    is the only basis of demonstrating stability of a process

                                                               17
Addressing the hesitancy and the potential
paradox
   Structured development information and robust
    estimates of variability

   For this approach the pivotal clinical trial lot(s) must be
    “stable” (and capable) and its variation understood to the
    extent that units may be sampled (e.g., stratified plan) for
    a “destructive” Gauge R&R study

   Contribution to an improved assurance of quality over
    what we achieve today


                                                               18
Is this a stable process? Non-homogeneous
Distribution of Magnesium Stearate




        Ajaz Hussain. Blend Uniformity: Update. 19 July 2001, ACPS Meeting

                                                                             19
Need to debate Engineering control Vs.
Statistical process control?
   Preferred State: “Statistical Process Control”
   Some processes never reach a state of Shewharts’
    statistical control despite heroic efforts.
   But, often the average level and the variability of the data are
    so far inside the specification limits that acceptable product
    is being made and distributed.




      Lynn Torbeck. The Sector Chart: A new engineering graph for pharmaceutical
      processes. Pharmaceutical Technology. April 2005                             20

								
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