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Bioinformatics Applications. Drug Discovery Pharmacogenomics. Pharmaceutical Industry. $100,000,000,000 worldwide yearly 78% prescription 20% over-the-counter 2% diagnostics R&D expenditure ??>10 billion. Compounds. Targets. Drug Candidates. Target Candidates. Drug Discovery. Refine.

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bioinformatics applications

BioinformaticsApplications

Drug Discovery

Pharmacogenomics

Chuck Staben

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

Chuck Staben

drug discovery

Compounds

Targets

Drug Candidates

Target Candidates

Drug Discovery

Refine

Chuck Staben

drug approval

Genomics, BioInfo

Drug Approval

Discovery

5 years

Pre-clinical

1 year

Clinical

6 years

Review

2 years

Chuck Staben

drugs therapeutic categories
Drugs-Therapeutic Categories
  • Inflammatory/Immunological ($50B)
  • Cardiovascular ($20B)
  • Metabolic/endocrine ($15B)
  • Anti-infectives ($20B)
  • Oncology ($7B)
  • Neurological
  • Pain

Viagra!

Chuck Staben

anti infectives
Anti-infectives
  • Anti-bacterial, for example
  • Non-toxic to humans

Target-driven

Compound-driven

Chuck Staben

target paradigm bioinformatics
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

target refinement
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

oncogenic target
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

anti inflammatory
Anti-inflammatory

Sketch Pad

-Class input

Chuck Staben

compound paradigm
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

combinatorial chemistry
Combinatorial Chemistry
  • “Arrayed” chemistries (~1992)
    • parallel automated syntheses
    • permuted chemical libraries
  • Can be “biased” by lead compounds, selected chemistries

Millions of compounds

Chuck Staben

high throughput screens
High Throughput Screens
  • 100,000 assays/day per system
  • Require microminiaturization

Microfluidics

Lab-on-a-chip

Chuck Staben

hts preclinical issues
HTS/Preclinical Issues
  • Pharmacokinetic issues
    • bulk transport, uptake, efflux, metabolism
  • Tissue specificity
  • Genetic/environmental variability

Chuck Staben

clinical trials
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

pharmacogenomics
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

fda gold mine
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

side effects
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

pharmacogenomic loci
Pharmacogenomic Loci
  • Metabolism Variation
  • Drug Target Variants
  • Disease Pathway

Chuck Staben

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

Chuck Staben

cyp2d6
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

target disease pathway variation
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

pharmacogenomic loci23
Pharmacogenomic Loci
  • Association Studies
    • 100,000 SNP markers, 1000 individuals
    • QTL traits!
  • Other Strategies??

Medical Informatics??

Chuck Staben

bioinformatics genomics therapy evaluation
Bioinformatics-GenomicsTherapy Evaluation
  • Gene Expression correlate with clinical progress/toxicity
    • transcriptome level
    • proteome level

Chuck Staben

improved drug development model

$$

Drugs

Costs

Improved Drug Development Model

Drugs

$$

Costs

Chuck Staben