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					    CLINICAL PHARMACOLOGY IN
       DRUG DEVELOPMENT



                                              70



                              CONCENTRATION
                                              60
                                              50
                                              40
                                              30
                                              20
                                              10
                                               0
                                                   0   5   10   15    20   25   30

                                                           TIME IN HOURS



Ramana S. Uppoor, R.Ph., Ph.D.
Division of Clinical Pharmacology-1      ASENT meeting, March 6, 2008
Office of Clinical Pharmacology, CDER, FDA
Disclaimer

Views expressed are mine and
do not necessarily reflect
official FDA Policy.
                                    New Molecular Entity Approvals by Fiscal Year

                    50

                    45
                                                         28 44         44
                                                                  34
                    40                                                           39
                                                   40
                                                                            21             37   27
                    35
  Number Approved




                                         31                                                                    32
                    30        28                                                                     30
                    25                                                                 8
                                                                                                                               25
                         13                   17                                                                         22
                                    11
                    20
                                                                                                                    14        13
                                                        18                            19
                    15                                                      17
                                                                                                          10
                    10   13         13                                                          12
                                               9                  10
                    5                                                                                                8         8
                                                                                                           5
                    0
                         1993      1994       1995      1996     1997       1998      1999      2000      2001      2002      2003
                                                                 Fiscal Year of Approval
                              Priority NME Approvals             Standard NME Approvals                Number of NMEs Filed
* as of 30-Sep-2003
        High attrition rate even in late
        development




Kola I, Landis J.Can the pharmaceutical industry reduce attrition rates?
Nat.Rev.Drug.Disc. Aug 2004.
      Need/Opportunities for Innovative Methods in
                 Drug Development

                                Assess
  Decrease
                                useful
  avoidable
                              Biomarkers
 trial failures
                              e.g. imaging
                   Evaluate                  Individualization
                   rational                         of
                     trial                        dosing
                  designs,
                  endpoints

Providing solutions for these issues calls
for optimal early trials and efficient use of prior knowledge
  OUTLINE

 Definitions
 Clinical Pharmacology domain
 Clinical Pharmacology studies
 Biopharmaceutics studies
 Value
 Case examples
 Conclusions
   Clinical Pharmacology is…

 Translational  science in which basic
  information about the relationship between
  dose, exposure and response (efficacy or
  safety) is applied in the context of patient care
 Major contribution of Clinical Pharmacology:
  Knowledge of E-R relationship (key to
  successful therapeutics) and how it is altered
  by intrinsic (age, gender, renal function etc.)
  and extrinsic (diet, drugs, life-style) factors of
  an individual patient
    Definitions

   Clinical Pharmacology:
     Pharmacokinetics (PK): What the body does to the
      drug (Absorption, Distribution, Metabolism,
      Excretion). For drug review purpose, PK also covers
      extrinsic and intrinsic factors like drug interactions,
      effect of age, gender, race, organ dysfunction, etc. PK
      gives you Exposure.
     Pharmacodynamics (PM): What the drug does to the
      body. PD covers desirable and undesirable effects, from
      biomarkers to surrogates to clinical endpoints. PD gives
      you Response.
              FIRST PRINCIPLES
              Why Drugs Work In Vivo

Dose   Pharmacokinetics              Pharmacodynamics   Effect

          Absorption
          Distribution
          Metabolism
          Excretion
              Concentration




                                            MEC
                              Free          Total

                                     Time
      PK-PD MEASURES
      Relationships Between Exposure & Response




                                                Effect (e.g., Survival, % change in seizure
Serum Drug Concentration                                                                                         Emax

                            Peak conc. (Cmax)




                                                                                          frequency
            AUC
                                                                                                      EC50



                                                                                                       PK-PD Measure
                           Time                                                                          (e.g., AUC)
  Clinical Trials Spectrum

 Phase I, II,III and IV clinical trials
 Early and Late phase clinical trials
 Learn and Confirm trials
 Clinical Pharmacology (= Learn; phase 1
  and 2) including dose response trials and
  Efficacy (= Confirm; phase 3) trials
 Safety Trials: All phases
 Bioequivalence Trials
Clinical Pharmacology Domain
  PK (ADME)       PD




    PM           PG
       Clinical Pharmacology &
       Biopharmaceutics Studies
Pharmacokinetics/Biopharmaceutics:
   Mass  Balance studies with radiolabelled drug
   Single and multiple dose pharmacokinetics
   Absolute bioavailability
   Dose proportionality
   Food effects studies
   Bioequivalence studies to establish the link
    between the market and clinical formulations
   Metabolism and drug interactions
      Clinical Pharmacology &
      Biopharmaceutics Studies .. contd.
Clinical Pharmacology:
  Pharmacokinetics in the target population
  Special population studies
     Age, Gender, Race, etc.
     Disease states such as renal and liver impairment
  Establishment of pharmacokinetic
   pharmacodynamic correlations
     Bioavailability and Bioequivalence -
                  Definitions
Bioavailability means the rate and extent to which the
  active ingredient or active moiety is absorbed from a
  drug product and becomes available at the site of
  action.

Bioequivalence means the absence of a significant
  difference in the rate and extent to which the active
  ingredient or active moiety in pharmaceutical
  equivalents or pharmaceutical alternatives becomes
  available at the site of drug action when administered
  at the same molar dose under similar conditions in an
  appropriately designed study.
     BIOAVAILABILITY
      MEASUREMENT

    MONITORING PARAMETERS

   Peak Concentration: Cmax
   Time to Peak Concentration:
    Tmax
   Area Under the Drug
    Concentration-Time Curve:
    AUC
                   Single dose & Multiple dose
                   Bioavailability

         70                                                  120

         60                                                  100
         50
CONCN.




                                                              80




                                                    CONCN.
         40                                                   60
         30
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              0     5   10    15     20   25   30
                                                                            TIME IN HOURS
                         TIME IN HOURS




                  Cmax and AUC
    Food effect study
High fat meal:                                        70
 2 eggs fried in butter




                                      CONCENTRATION
                                                      60
 2 strips of bacon                                   50                           fed
                                                                                   fasting
 2 slices of toast with butter                       40
 4 ounces of hash brown                              30
   potatoes                                           20
 8 ounces of whole milk                              10
 1000 calories, 50 % derived                          0
   from fat                                                0   5   10   15    20       25    30

                                                                   TIME IN HOURS
Evaluate the food effect by
   comparing the PK parameters
   obtained in fed vs. fasted state
    BIOEQUIVALENCE MEASUREMENT

PHARMACOKINETIC PARAMETERS

                     MULTIPLE
   SINGLE DOSE       DOSE
    AUC0-Tlast        AUCss
    AUC 0-Tinf        Cmax
    Cmax              Cmin
    Tmax              Tmax
         STATISTICAL REQUIREMENTS
              FOR Bioequivalence

Current Decision Rule:
Two one-sided test procedure:
(ALSO CALLED THE 90% CONFIDENCE INTERVAL APPROACH)
    •   Recognizes that there will be a difference in mean values
        between treatments
    •   Provides reasonable assurance that mean
        treatment differences are acceptable


General Requirement:
90% confidence intervals for AUC and Cmax have to be within
the range of: 80 – 125% (based on log transformed data)
  Common CPR Encounters
                 Exposure-Response




Pater Current Controlled Trials in Cardiovascular Medicine 2004 5:7
    GENERAL THOUGHTS/VALUES

 OCP:



  The Right Dose of the Right Drug at the Right Time
                 for the Right Patient


 Optimal bioavailability
 Dose selection
 Dosing regimen selection
 Dose adjustment for special populations
 Dose adjustment in presence of intrinsic and extrinsic factors
 GOAL: To develop good drugs/drug
products with adequate information to
improve therapeutics (with an ultimate
goal of optimal treatment for a patient)
  Exposure Response Relationship
     Selection of appropriate dose/regimen


                                Efficacy

Percentage
    of
Response                            Toxicity




                    Exposure
Selection of optimal release profile
   Case example 1 – Dosing regimen


FDA’s proactive model-based analysis
identified that the proposed dosing is sub-
optimal. Simulations suggested alternatives.
Development cycle extended.
            Regulatory Issue

 Short t1/2 drug for lowering BP
 Sustained effect desired
 Proposed dosing - QD
 Very large trial conducted
     Typically   pivotal trials are not large for hypertension
 Exposure-Response         analyses conducted
     Effectiveness   and Safety
   Is this really a once-day-drug?
                                    s-Lercanidipine Steady-Stat
                                                                  6.0                    6.
                         ER Analysis
                               3.0                                                       3.
                                                                  0.0      X mg daily    0.
                                                                            ID: 101
Clear concentration-effect                                  3.6                         4.
 relationship                                                                    EC50    3.
                                                             2.4
   No delay between PK and                               Cp
    PD                                                       1.2                         1.
   Nonlinear concentration-                                 0.0                         0.
    effect relationship
      FDA performed the analysis                                          6 12
                                                                        0 Time, h18 24
       during NDA review

     Modeling demonstrated inadequacy of once a
    day regimen
     Value Delivered by the Exposure
           Response Analysis

 Supported  evidence for effectiveness
 Aided in judging that QD dosing is sub-
  optimal
 Provided alternatives for future development
 Prospective modeling of early PK/PD data
  could have (and an EOP2A meeting)
   Avoidedlengthening drug development time
   Been more economical
      Case example 2 - Use of exposure
       response for pediatric approval

FDA’s proactive model-based analysis alleviated
the need to conduct additional clinical trial for the
approval of Trileptal monotherapy in pediatrics
                    Regulatory Issue

              Adjunctive        Monotherapy
Adults        Clinical trials   Clinical trials

Children    Clinical trial      “Model Based Bridging”
(4-16 years                     approach proposed by
of age)                         FDA


FDA/Sponsor pursued approaches to best utilize
  knowledge from the positive trials to assess if
  monotherapy in pediatrics can be approved without new
  controlled trials
                   Motivation

   Monotherapy of anticonvulsants is important
     Better safety, Ease of Rx mgmt
     Avoid unnecessary costs

 Monotherapy trials are challenging
 Reasonable ER knowledge available
       Integration of knowledge across trials and populations
        is needed
   Law supports model based thinking
        Value of this type of analysis

 Modeling   and simulation aided in utilizing all
  previous data to justify approval without
  additional controlled clinical trials
 Allowed selection of dosing guidelines in
  pediatrics
 The presented approach has a greater global
  impact
   Precedent   was set
               Conclusions

 PK and Exposure-Response analysis can help select
  suitable dose/dosing regimen and identify optimal drug
  products.
 PK from early trials will help optimize the dosing
  conditions for pivotal trials.
 Facilitate dosing in special populations and also provide
  dose adjustment guidelines in the presence of intrinsic
  (age, gender, renal function etc.) or extrinsic factors
  (concomitant drugs, food etc.).
  Conclusions …. contd.

 Facilitatefindings of effectiveness as well
  as help resolve safety concerns.
 E-R frame created in the approved setting
  can be a powerful source for approval
  consideration for additional settings (e.g.
  pediatrics).
      Need/Opportunities for Innovative Methods in
                 Drug Development

                                Assess
  Decrease
                                useful
  avoidable
                              Biomarkers
 trial failures
                              e.g. imaging
                   Evaluate                  Individualization
                   rational                         of
                     trial                        dosing
                  designs,
                  endpoints

Providing solutions for these issues calls
for optimal early trials and efficient use of prior knowledge
ACKNOWLEDGEMENTS

Dr. Mehul Mehta
Dr. Patrick Marroum
Dr. Robert Kumi




                      That’s all folks!

				
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