The Rationale for Predictive Drug Metabolism

2. Introduction

3. The Role of Metabolism in the Drug Approval
Process: FDA Perspective

• Use and timing of predictive models to ensure adequate information for drug evaluation
• Metabolism and drug interactions at IND and NDA
• How FDA reviewers look at metabolism studies

4. LC/NMR to Elucidate Drug & Metabolite
Structures

• Hardware and software design to improve coupling of LC and NMR
• The use of LC/NMR in preclinical drug metabolism studies
• Case study: melatonin metabolism

5. Mass Spectrometry for High Throughput
Analysis

• Developing high-throughput analytical methods
• High throughput pharmacokinetics supported by HPLC-API/MS/MS

6. Combining Medicinal Chemistry and Metabolic Data to Alter Drug Metabolism Properties

• The concepts of low stringency and high selectivity in changing a drug's metabolism profile
• Using metabolic drug data to predict drug metabolizing enzymes
• Changing metabolic versus pharmacological properties of drugs

7. Cellular Models to Evaluate Drug Metabolism
and Toxicity

• Developing human hepatocyte in vitro models - advantages over microsomes
• Differential gene expression to predict toxicity, drug metabolism, and drug-drug interactions
• Study Phase I and Phase II drug metabolism, enzyme induction, mechanisms of toxicity and pharmacokinetics

8. Metabolic Profiling, Reaction Phenotyping and Drug Interactions

• Cross-species metabolic profiling
• Reaction phenotyping
• Metabolic inhibition and induction studies
• Case studies of drug-drug interactions

9. Prediction of Metabolic Drug Interactions

• Comparison of in vitro systems for predicting drug interactions
• Correlation with clinical data

10. In Vitro Metabolism Studies to Evaluate
Potential Drug Interactions

• Systematic studies for protein binding and transport
• Inhibition and induction of metabolizing enzymes
• Case study: M100907 as an enzyme inhibitor

11. Assessing Drug Metabolism Using
Miniaturized Assays with High Sensitivity

• Availability of novel, sensitive, miniaturized, human cytochrome P450 assays
• SAR of compound-cytochrome P450 interaction
• Selecting lead compounds with favorable drug metabolism

12. Screening Compounds for Drug Interactions
Using High Throughput In Vitro Assays

• Choosing human P450 isozymes for drug-induced inhibition assays
• Deciding when and how to test drug compounds
• Generating useful data for discovery teams
• Commercial advantage of medications without drug-drug interactions

13. Predicting Drug Metabolism In Vitro and In
Silico

• Choosing a drug metabolizing high-throughput in vitro system
• Automating high-throughput screening assays
• Detecting and analyzing drug metabolites in vitro
• Predicting drug metabolism using computer modeling

14. SAR to Determine Metabolic Vulnerability
of Compounds

• The role of cytochrome P450 substrate structure activity relationships in preclinical studies
• Pharmacophore and protein modeling
• The use of computational models, selective inhibitors and recombinant cytochromes
• Case study: the CYP2C9 substrate Warfarin

15. Applying Computational Pharmacokinetics to Drug Discovery

• Enhancing the physiology of high-throughput in vitro systems using computer simulation
• Modeling clinical outcome based on in vitro PK data (drug absorption and metabolism)
• Developing robust ADME databases using consortia

16. Early Clinical Investigations to Evaluate
Potential Drug Interactions

• Determining timing and design of interaction studies
• Testing accuracy of predictive models during preclinical and Phase I clinical studies
• Selecting compounds for early interaction studies

17. Population-Based Approaches to Study
Drug Interactions and Metabolites

• Retrospective analysis of data from Phase II/III and IV clinical studies
• Prospective integration of a population approach into Phase II and III clinical trial design
• Case studies in Phase II and Phase III clinical trial design

18. Preclinical Evaluation of Drug
Mechanisms using Gene Expression Assays

• High-throughput gene expression assays
• Differential gene expression to classify compounds by mode of action
• Identification of efficacy and toxicity markers for drug compounds

19. Pharmacogenomic Profiling to Design
Safe, Efficient Clinical Trials

• Genotyping assays to assess metabolism and efficacy of drugs
• Pharmacogenetic testing in clinical trial design
• Regulatory and other issues associated with pharmacogenetic testing

20. Bringing Pharmacogenomics to Drug
Development 

• Genetic variation in drug response
• The use of pharmacogenomics in ADME testing, drug dosing and clinical trials
• Prospective pharmacogenomic clinical studies

21. Cost-Effective Clinical Development of
Protein Drugs

• Unique challenges in managing risk for protein drugs
• Effective use of pharmacology and toxicology data during clinical development
• Case studies of rational go/no-go decisions during drug development

22. Conclusions