CLINICAL PHARMACOLOGY IN DRUG DEVELOPMENT Ramana S. Uppoor, R.Ph., Ph.D. Division of Clinical Pharmacology-1 Office of Clinical Pharmacology, CDER, FDA.

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Presentation transcript:

CLINICAL PHARMACOLOGY IN DRUG DEVELOPMENT Ramana S. Uppoor, R.Ph., Ph.D. Division of Clinical Pharmacology-1 Office of Clinical Pharmacology, CDER, FDA ASENT meeting, March 6, 2008

Disclaimer Views expressed are mine and do not necessarily reflect official FDA Policy.

* 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 Evaluate rational trial designs, endpoints Decrease avoidable trial failures Assess useful Biomarkers e.g. imaging Individualization of dosing 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 Time Concentration Total Free MEC  Absorption  Distribution  Metabolism  Excretion PharmacodynamicsDosePharmacokinetics Effect

Effect (e.g., Survival, % change in seizure frequency Peak conc. (Cmax) Time Serum Drug Concentration PK-PD Measure (e.g., AUC) Emax EC 50 PK-PD MEASURES Relationships Between Exposure & Response 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:  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 Clinical Pharmacology & Biopharmaceutics Studies.. contd.

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 MONITORING PARAMETERS  Peak Concentration: Cmax  Time to Peak Concentration: Tmax  Area Under the Drug Concentration-Time Curve: AUC

Single dose & Multiple dose Bioavailability Cmax and AUC

Food effect study High fat meal:  2 eggs fried in butter  2 strips of bacon  2 slices of toast with butter  4 ounces of hash brown potatoes  8 ounces of whole milk  1000 calories, 50 % derived from fat Evaluate the food effect by comparing the PK parameters obtained in fed vs. fasted state

 SINGLE DOSE AUC 0-Tlast AUC 0-Tinf CmaxTmax BIOEQUIVALENCE MEASUREMENT  MULTIPLE DOSE AUCssCmaxCminTmax PHARMACOKINETIC PARAMETERS

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) STATISTICAL REQUIREMENTS FOR Bioequivalence

Common CPR Encounters Exposure-Response Pater Current Controlled Trials in Cardiovascular Medicine :7

The Right Dose of the Right Drug at the Right Time for the Right Patient GENERAL THOUGHTS/VALUES  OCP:  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 Percentage of Response Efficacy Toxicity ExposureExposure

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?

 Clear concentration-effect relationship  No delay between PK and PD  Nonlinear concentration- effect relationship  FDA performed the analysis during NDA review Cp EC 50 Time, h  Modeling demonstrated inadequacy of once a day regimen X mg daily ER 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)  Avoided lengthening drug development time  Been more economical Value Delivered by the Exposure Response Analysis

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 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.  Facilitate findings 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 Evaluate rational trial designs, endpoints Decrease avoidable trial failures Assess useful Biomarkers e.g. imaging Individualization of dosing Providing solutions for these issues calls for optimal early trials and efficient use of prior knowledge

That’s all folks! That’s all folks! ACKNOWLEDGEMENTS Dr. Mehul Mehta Dr. Patrick Marroum Dr. Robert Kumi