Bioinformatics Applications

1. BioinformaticsApplications Drug Discovery Pharmacogenomics Chuck Staben

2. Pharmaceutical Industry • $100,000,000,000 worldwide yearly • 78% prescription • 20% over-the-counter • 2% diagnostics • R&D expenditure • ??>10 billion Chuck Staben

3. Compounds Targets Drug Candidates Target Candidates Drug Discovery Refine Chuck Staben

4. Genomics, BioInfo Drug Approval Discovery 5 years Pre-clinical 1 year Clinical 6 years Review 2 years Chuck Staben

5. Drugs-Therapeutic Categories • Inflammatory/Immunological ($50B) • Cardiovascular ($20B) • Metabolic/endocrine ($15B) • Anti-infectives ($20B) • Oncology ($7B) • Neurological • Pain Viagra! Chuck Staben

6. Anti-infectives • Anti-bacterial, for example • Non-toxic to humans Target-driven Compound-driven Chuck Staben

7. Present in all target pathogens Expressed growing vs non-growing? Essential growth vs survival Absent in humans Not expressed in target tissue? Target Paradigm-Bioinformatics Other Criteria? Target Validation Chuck Staben

8. Target Refinement • Known drug target in this class? • Known structure in class? • Develop assay/high throughput screen • refine “differential” screens? • Determine target properties • structure, binding/catalytic properties • STRUCTURE BASED DESIGN Chuck Staben

9. Oncogenic Target • Normal vs transformed cells • process found in cancer, not normal • rapid DNA replication, eg. • process unique to normal, not cancer • loss of differentiated characteristic • receptor response, etc. Chuck Staben

10. Anti-inflammatory Sketch Pad -Class input Chuck Staben

11. Compound Paradigm • HTS to find active compounds • whole cell assays? • Bioinformatics and genomics to find targets! • refine targets/compounds Expression screening Overexpression protection Chuck Staben

12. Combinatorial Chemistry • “Arrayed” chemistries (~1992) • parallel automated syntheses • permuted chemical libraries • Can be “biased” by lead compounds, selected chemistries Millions of compounds Chuck Staben

13. High Throughput Screens • 100,000 assays/day per system • Require microminiaturization Microfluidics Lab-on-a-chip Chuck Staben

14. HTS/Preclinical Issues • Pharmacokinetic issues • bulk transport, uptake, efflux, metabolism • Tissue specificity • Genetic/environmental variability Chuck Staben

15. Clinical Trials • Phase I: 50-100 subjects for toxicology • Phase II: 100-300 patients for efficacy, dose, safety • Phase III: 1000-3000 patients for efficacy, safety MAJOR Expense Chuck Staben

16. Pharmacogenomics • Pharmacogenomics is the science of understanding the correlation of an individual's genetic make-up to his or her response to drug treatment. • Understanding the genetic cause of differences in response will be useful in stratifying patient populations for clinical trials, accelerating timelines and reducing costs during clinical development. Chuck Staben

17. FDA Gold Mine "Identifying metabolic differences in patient groups based on genetic polymorphisms, or on other readily identifiable factors such as age, race, and gender, could help guide the design of dosimetry studies for such populations groups. This kind of information also will provide improved dosing recommendations in product labeling, facilitating the safe and effective use of a drug by allowing prescribers to anticipate necessary dose adjustments. Indeed, in some cases, understanding how to adjust dose to avoid toxicity may allow the marketing of a drug that would have an unacceptable level of toxicity were its toxicity unpredictable and unpreventable." Chuck Staben

18. Side Effects • 90% of drug candidates fail in pre-clinicals • 90% of remainder fail in clinical-many due to side effects • Estimates of NSAID ulcers • more deaths/year than due to melanoma, cervical cancer combined! Chuck Staben

19. Pharmacogenomic Loci • Metabolism Variation • Drug Target Variants • Disease Pathway Chuck Staben

20. Metabolism Variants • Cytochrome P450s • CYP2D6, (~10% Caucasian) • 3A4,2C19 • N-acetyltransferases (NAT1, NAT2) • 40-60%!, isoniazid toxicity Chuck Staben

21. CYP2D6 • Substrates • Antidepressants* • Amitriptyline (Elavil) • Doxepin (Adapin, Sinequan) • Fluoxetine (Prozac) • Paroxetine (Paxil) …. • Antipsychotics • Haloperidol (Haldol) • ... • Beta blockers • Propranolol (Inderal)* • Timolol (Blocadren) • Narcotics • Codeine, tramadol (Ultram) • Inhibitors • Antidepressants • sertraline (Zoloft) • Cimetidine (Tagamet) • Fluphenazine (Prolixin) • Antipsychotics • Haloperidol • Perphenazine ~25% all drugs ~10 population Chuck Staben

22. Target/ Disease Pathway Variation • 5-HT2A Receptor [clozapine (antipsychotic)] • 5-HTT (serotonin uptake) • variant associated with anxiety • need for/success with Prozac? • Apo4E •  risk, Alzheimers AND  effect ACE inhibitors • CETP, LPL, -fibrinogen(cholesteryl ester transfer protein, lipoprotein lipase) •  response to HMG-CoA inhibitors (parvastatin) AND  risk of atherosclerosis Chuck Staben

23. Pharmacogenomic Loci • Association Studies • 100,000 SNP markers, 1000 individuals • QTL traits! • Other Strategies?? Medical Informatics?? Chuck Staben

24. Bioinformatics-GenomicsTherapy Evaluation • Gene Expression correlate with clinical progress/toxicity • transcriptome level • proteome level Chuck Staben

25. $$ Drugs Costs Improved Drug Development Model Drugs $$ Costs Chuck Staben