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Drug Discovery and Genomics

B i o p h a r m a c e u t i c a l s L t d. Drug Discovery and Genomics. How the Sequencing of the Human Genome and Related Developments has Impacted Drug Discovery. B i o p h a r m a c e u t i c a l s L t d. “ Fortunes will be won and lost in the genome grab. The race to secure the

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Drug Discovery and Genomics

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  1. B i o p h a r m a c e u t i c a l s L t d. Drug Discovery and Genomics How the Sequencing of the Human Genome and Related Developments has Impacted Drug Discovery

  2. B i o p h a r m a c e u t i c a l s L t d. “Fortunes will be won and lost in the genome grab. The race to secure the sequence patents will be over in five Years.” The World in 2001. The New Economist on pharma- ceuticals.

  3. The Promise

  4. The Concern

  5. B i o p h a r m a c e u t i c a l s L t d. Bottom Line The Human Genome Project and related technologies has generated thousands of novel potential drug targets. Validating those targets and their drugability and generating therapeutic options are now the rate limiting steps in drug development.

  6. B i o p h a r m a c e u t i c a l s L t d. Topics • What is Genomics ? • What is the relationship between genes and disease? • What are the steps in developing a drug? • What impact has genomics had on the process of drug development?

  7. B i o p h a r m a c e u t i c a l s L t d. What is Genomics ? • Study of information stored in the genome • structural and functional information • Structural genomics — the sequence • Information is encoded linearly and digitally in four coding molecules-bases • Three bases = codon = amino acid • A number of codons strung together code for a gene which codes for a protein • Functional genomics — what the genes do

  8. B i o p h a r m a c e u t i c a l s L t d.

  9. B i o p h a r m a c e u t i c a l s L t d.

  10. Comparative Sequence Sizes (Bases) (yeast chromosome 3) 350 Thousand Escherichia coli (bacterium) genome 4.6 Million Largest yeast chromosome now mapped 5.8 Million Entire yeast genome 15 Million Smallest human chromosome (Y) 50 Million B i o p h a r m a c e u t i c a l s L t d. Largest human chromosome (1) 250 Million Entire human genome 3 Billion Return to text

  11. B i o p h a r m a c e u t i c a l s L t d. Structural Genomics: The Human Genome • Three billion bases long (=800 Tanachim) • Codes for 30,000 to 80,000 genes • 23 chromosome pairs (24 in chimp) • 97% of genome does not code for translatable protein products • June 26, 2000: Clinton and Blair announce rough draft

  12. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics • Sequence/structural motifs in proteins ie functional class of protein • Homology to model organisms/gene knockouts: worms, flies, mice, fish, etc. • Antisense in cell culture • Microarrays of gene expression • Proteomics • Pharmacogenomics

  13. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Motifs • Gene families • Super families of related activities such as dehydrogenases, glucocorticoid receptor-like etc. • Bioinformatic tools; data mining

  14. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Microarrays of Gene Expression Normal tissue normal Diseased cDNA Diseased associated

  15. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Model Organisms “Genes are just chunks of software that can Run on any system: they use the same code And do the same jobs.” Matt Ridley in Genome 1999 Perennial Example: Homeotic genes which determine macro form of animal Fly mouse

  16. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Proteomics Differential display of protein expression in diseased and normal tissue May be a better approach to target identification than microarrays of gene expression Not all expressed genes produce proteins

  17. B i o p h a r m a c e u t i c a l s L t d. Functional Genomics: Pharmacogenomics Genetic differences between individuals (SNP) can cause large differences in drug effects both agonist and antagonist and toxic Stratification of patients into genotypes may increase the probability of drug efficacy/therapeutic window eg: drug metabolizing enzymes, transporters and drug receptors

  18. B i o p h a r m a c e u t i c a l s L t d. Relationship between Genes & Disease • Genes do not cause disease, defective genes cause disease • One gene one enzyme (Beadle and Tatum 1940s) • Mendelian inherited diseases • Polygenic diseases

  19. B i o p h a r m a c e u t i c a l s L t d. Relationship between Genes & Disease • A gene is missing or defective • Replace protein • Replace activity • Gene is overexpressed • Develop inhibitors of synthesis or activity • Poly-genic disease • eg asthma where up to 15 genes may be involved

  20. B i o p h a r m a c e u t i c a l s L t d. Relationship between Genes & Disease • As of February 2, 2001 in GenBank • 12265 human gene entries • 8912 established gene locus • 845 multi loci disease associations

  21. B i o p h a r m a c e u t i c a l s L t d. Thesis Genomics New Drug Targets More Rapid Drug Development

  22. “Is Genomics Delivering?”“Yes but slower than Expected.”Lehman Brothers B i o p h a r m a c e u t i c a l s L t d. Use of genomics to discover new drug targets began in 1993 Today, percent of research projects based on genomics in pharma: 10-25% average Only handful of drugs currently in the clinic utilizing genomic information Expect percent of genomic based drugs to increase considerably in the next 5-10 years

  23. B i o p h a r m a c e u t i c a l s L t d. The Drug Development Process Gene Sequences Genome Targets Validated Targets Drug Screening Drug Leads Validated Candidate Clinical Trials Market

  24. B i o p h a r m a c e u t i c a l s L t d. The Drug Development Process Gene Sequences Genome Targets Validated Targets Drug Screening Drug Leads Validated Candidate Clinical Trials Market

  25. B i o p h a r m a c e u t i c a l s L t d. Reality One 90 80 70 60 50 40 30 20 10 0 Market Gene Targets Drug Candidate Assay Development Data from Biocentury (Jan 29, 2001) CuraGen/Bayer

  26. B i o p h a r m a c e u t i c a l s L t d. Reality Two • Millenium: 44% targets to leads • Vertex: 85% targets into phase 1 • Bayer: 25% targets into phase 1

  27. B i o p h a r m a c e u t i c a l s L t d. Genomic Based Drug Development: What Next? • Improvement of bio-validation tools • Cell based • In-vivo based • Better understanding of physiologic pathways and networks and their control • Model organisms • Better bio-informatic tools for protein structure and better chemo-informatic tools for medicinal chemistry

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