1. Using Spotfire DecisionSite to Realize the Full Value of High-Throughput Screening ADME Data Eric Milgram Pfizer Global Research & Development – La Jolla Spotfire Users’ Group Meeting Wednesday October 15, 2003 San Francisco, California Eric Milgram Pfizer Global Research & Development – La Jolla Spotfire Users’ Group Meeting Wednesday October 15, 2003 San Francisco, California

2. Challenge faced by Pharmaceutical Industry  Reduce Attrition  Increase Productivity  No growth  Budgetary Pressure  Reduce Attrition  Increase Productivity  No growth  Budgetary Pressure Source: PhRMA annual survey, 2000 Cost and Number of NDAs per year

3. Why Do Candidates Fail? Drug Discovery Today 2:436, 1997 198 NCEs Pharmacokinetics 39% 30% 11% 10% 5% Lack of Efficacy Animal Toxicity Adverse effects in man Miscellaneous Commercial Reasons

4. The Fate of a Medication after Administration ADME Absorption The movement of drugs into the bloodstream or lymphatic system from the site of administration Distribution The distribution of absorbed drugs from the absorption site to all areas of the body Metabolism The biotransformation of drugs to more polar forms (hydrolysis, oxidation, conjugation, etc.) Excretion The elimination of “unwanted” substances

5. Drug Metabolism in Drug Discovery Early assessment is critical, since the duration of action is dependent on structural modifications induced by in vivo metabolizing systems. Early knowledge of metabolic products permits metabolism guided structure modification schemes, such as modification of metabolic “soft spots” to achieve prolonged drug action. Identify pharmacologically or toxicologically active metabolites.

6. Physicochemical & Biochemical In- Vitro Assays Solution Properties Solubility Log D Protein Binding pKa Absorption PAMPA Caco-2, MDCK P gp transport IAM Metabolism Metabolic stability Liver microsomes, S-9, hepatocytes Metabolic profile CYP450 enzyme inhibition Safety Assessment Cell viability Mutagenesis (Ames) Glutathione level Dofetilide binding Predictive of In-Vivo Absorption, Distribution, Metabolism, Excretion

7. Pritchard, et al., “Making Better Drugs: Decision Gates in Non-Clinical Drug Development” Nature Reviews: Drug Discovery, 2003, vol 2(7), pp. 542-553. (http://www.nature.com/reviews/)

8. Advances in Laboratory Robotics and Instrumentation Have Been Swift

9. Difficulties Resulting from HTS  The rate at which we can collect data far exceeds our capacity to transform this data into information that can be used most effectively to drive important business decisions  Relevance of data?  Number of data dimensions?  What do we do when two different dimensions are in conflict?  Unmasking subtleties (ie “data-mining”)  The rate at which we can collect data far exceeds our capacity to transform this data into information that can be used most effectively to drive important business decisions  Relevance of data?  Number of data dimensions?  What do we do when two different dimensions are in conflict?  Unmasking subtleties (ie “data-mining”)

10. Visualization is a Powerful Tool For Data Analysis

11. Spotfire can be used to find trends related to how samples are formatted on plates.

13. How do we use Spotfire DecisionSite to Allocate Resources Efficiently?  Quality Control and Quality Assurance  Results Analysis and Trending  Quality Control and Quality Assurance  Results Analysis and Trending

14. When combined with chemometrics techniques, such as principal components analysis (PCA), Spotfire enables viewing of interesting trends in large, multidimensional data sets. STABLE HLM STABLE RHEP STABLE RLM UNSTABLE RHEP UNSTABLE RLM UNSTABLE HLM

15. Spotfire enables viewing of trends that would be difficult to spot otherwise

16. Summary  Spotfire DecisionSite enables powerful interrogation of large data sets  Ability to generate quickly new views of the same dataset is essential in a high-throughput discovery environment  Sometimes, weaknesses in experiment design are uncovered  Having a collection of “standard” visualizations greatly facilitates QA  Integration of chemometrics tools (e.g. clustering, PCA, etc) enables researchers to “gain a deeper understanding of their data” (Data  Information)  Spotfire DecisionSite enables powerful interrogation of large data sets  Ability to generate quickly new views of the same dataset is essential in a high-throughput discovery environment  Sometimes, weaknesses in experiment design are uncovered  Having a collection of “standard” visualizations greatly facilitates QA  Integration of chemometrics tools (e.g. clustering, PCA, etc) enables researchers to “gain a deeper understanding of their data” (Data  Information)