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Новая парадигма разработки лекарств: как мы и хотели это делать в 1999 году Виталий Пруцкий, Глава по информационному обеспечению R&D, «АстраЗенека Россия»

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Presentation on theme: "Новая парадигма разработки лекарств: как мы и хотели это делать в 1999 году Виталий Пруцкий, Глава по информационному обеспечению R&D, «АстраЗенека Россия»"— Presentation transcript:

1 Новая парадигма разработки лекарств: как мы и хотели это делать в 1999 году Виталий Пруцкий, Глава по информационному обеспечению R&D, «АстраЗенека Россия» Диалектика - или назад в будущее

2 What prompted the topic? With DeCode Deal, Amgen Aims To Discover Drugs Like We Meant To In discover-drugs-like-we-meant-to-1999/http://www.forbes.com/sites/matthewherper/2012/12/10/with-decode-deal-amgen-aims-to- discover-drugs-like-we-meant-to-1999/ “It certainly wasn’t the deal Amgen investors were expecting from their new executive team: This morning, the Thousand Oaks, Calif., biotechnology giant dropped $415 million on DeCode Genetics, a genomics firm that Wall Streeters associate with the hype-filled days of the 2000s genomics boom and a company they probably hadn’t thought about since it went bankrupt in 2010.”Amgen

3 Brief History of DeCode 1996 Founded 1997 Drug discovery collaboration with Roche - $200M 2000 IPO - raised $173M Price > $25 /share Market cap = $1.2B 2009 Price $0.23/share Assets – $69M Liabilities - $313M Chapter Re-launched as private; $14M invested Dec 2012 Acquired by Amgen for $415M in cash Genotyped about 140,000 volunteers — nearly half of the Iceland's inhabitants Sequenced the genomes of about 2,600 of these Created a database of Health / phenotypic records for the last 100 years, and Genealogical records for ~1000 years Has had considerable success in identifying genetic markers associated with complex disease "Decode Genetics will provide Amgen with an industry-leading ability to identify and validate disease targets in human populations. This will enable Amgen to focus resources on programs that reach the right human disease targets, thus avoiding investments in programs based on less well- validated targets.“

4 Drug Targets and Target Discovery in Drug Discovery Process Target is where usually a good drug begins: Relevant Selective Druggable

5 Drug Targets – How many are there? 1997 – Drews & Reiser:483 drug targets Drews, J. & Ryser, S. Classic drug targets. Nature Biotechnol. 15, 1318–1319 (1997) 2002 – Hopkins&Groom:120 drug targets (rule-of-five compliant drugs only) Hopkins, A. L. & Groom, C. R. The druggable genome. Nature Rev. Drug Discov. 1, 727–730 (2002) 2003 – Golden:273 (protein) targets for approved then drugs Golden, J. B. Prioritizing the human genome: knowledge management for drug discovery. Curr. Opin. Drug Discov. Dev. 6, 310–316 (2003) 2006 – Wishart:14000 (6000) targets for all approved and experimental drugs Wishart, D. S. et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 43, D668–D672 (2006) 2006 – Imming:218 molecular targets for approved drug substances Imming, P., Sinning, C. & Meyer, A. Drugs, their targets and the nature and number of drug targets. Nature Rev. Drug Discov. 5, 821–834 (2006) 2006 – Zheng:268 'successful' targets in the Therapeutic Targets Database Zheng, C., Han, L., Yap, C. W., Xie, B. & Chen, Y. Progress and problems in the exploration of therapeutic targets. Drug Discov. Today 11, 412–420 (2006) 2006 – Overington:324 drug targets for all classes of approved therapeutic drugs (1,357 unique drugs: 1,204 'small-molecule drugs' and 166 'biological' drugs) John P. Overington, Bissan Al-Lazikani and Andrew L. Hopkins. How many drug targets are there? Nature Rev. Drug Discov. 5, (December 2006)

6 Drug Targets – How many are there? John P. Overington, Bissan Al-Lazikani and Andrew L. Hopkins. How many drug targets are there? Nature Rev. Drug Discov. 5, (December 2006) NB: Approximately 130 'privileged druggable domains' cover all current drug targets, compared to the projected number of protein families (16,000) and folds (10,000).

7 Drug Targets – slow rate of innovation Of the 361 new molecular entities approved by the FDA between 1989 and 2000, only 6% targeted a previously undrugged protein domain Between 1983 and 2005:  The rate of new 'drugged' targets per year  The rate of new protein families per year

8 Drug Targets – what are they? 50% of drugs 60% of drug targets are located at the cell surface, compared with only 22% of all proteins in the human genome.

9 Drug Targets – how many could be there? Drug Target “has” to be “druggable”, i.e. have drug*-binding domains (* Lipinski rule-of-five compliant orally bioavailable compounds) DRUG-CENTRIC VIEW: ~3000 (10-15%) proteins encoded by HG predicted as “druggable”.

10 Druggable does not equal drug target: Drug target “has” to be “disease related”, ideally disease-modifying Drug Targets – how many could be there? DISEASE-CENTRIC VIEW: ~1620 human protein sequences are linked directly to a disease (OMIM 2006) ~7-10% ( ) of human genes are disease modifying Druggability HG = ~20000 Disease mod. Drug Targets NB: only ~50% of current targets would be classified as disease-related by OMIM

11 So, Why DeCode?  DeCode is a Genetics Powerhouse  Access to genetic data, genealogies and medical records from Icelanders (population with strong founder effect).  Ability to find rare disease variants that can unmask unrecognised biological pathways containing new therapeutic targets.  Examples of DeCode’s recent work  Nonsense mutation in the LGR4 gene is associated with several human diseases and other traits Nature May 23;497(7450): (http://www.ncbi.nlm.nih.gov/pubmed/ ) Rare nonsense mutation within the leucine-rich-repeat-containing G-protein-coupled receptor 4 (LGR4) gene (c.376C>T) that is strongly associated with low BMD, and with osteoporotic fractures.  Variant of TREM2 associated with the risk of Alzheimer's disease N Engl J Med Jan 10;368(2): (http://www.ncbi.nlm.nih.gov/pubmed/ )http://www.ncbi.nlm.nih.gov/pubmed/ A rare missense mutation (rs T) in the gene encoding the triggering receptor expressed on myeloid cells 2 (TREM2), which was predicted to result in an R47H substitution, was found to confer a significant risk of Alzheimer's disease.  A mutation in APP protects against Alzheimer's disease and age-related cognitive decline Nature Aug 2;488(7409):96-99 (http://www.ncbi.nlm.nih.gov/pubmed/ )http://www.ncbi.nlm.nih.gov/pubmed/ The strong protective effect of the A673T substitution against Alzheimer's disease provides proof of principle for the hypothesis that reducing the β-cleavage of APP (amyloid-β precursor protein) may protect against the disease. (Supports the use beta-site APP cleaving enzyme 1 (BACE1) inhibitors in Alzheimer's therapy)

12 Why Pharma? Genetics (when it works) may be the only ethical way to discover and validate drug targets relevant in human disease as opposed to relying on (animal) models Example: PCSK9 (proprotein convertase subtilisin/kexin type 9) – a new ideal of a drug target  PCSK9 degrades the receptors responsible for cellular uptake of low-density lipoprotein cholesterol (LDL-c)  Mutations that turn up the volume on the gene result in high cholesterol and larger risk of heart attacks; those that make it stop working lower cholesterol and lifetime cholesterol risk.  Elucidated by French researchers studying a family with a rare autosomal dominant form of hypercholesterolemia (Abifadel et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat. Genet. 34, 154–156, 2003).  The idea is that genetics can start to prove a drug will work before there is even a drug.

13 Why 1999 ? Bayer's Millennium deal signals shift in R&D $465 million agreement … with Millennium Pharmaceuticals to discover 225 new drug targets in 7 disease areas including osteoporosis and cancer. Industry analysts think the deal signals Bayer's realization that the future lies with genomics. Nature Biotechnology 16, 1005 (1998) (http://www.nature.com/nbt/journal/v16/n11/full/nbt1198_1005b.html)

14 What Now? At present, genetics can offer only a partial and fragmented picture of the biological processes underlying many diseases  Problems with scale (cohort size)  Problems with populations (mixed vs. homogeneous)  Problems with technologies (only now becoming cost-effective)  Problems with (analytical) methodologies  Problems with ethics. “a substantial portion of missing heritability” may be overestimated and can actually be explained by interactions among loci that have already been identified… Eric Lander, Broad Institute (Proc.Natl.Acad.Sci. USA 109, 1193–1198, 2012). “The problem with that is nobody has been able to show these interactions” Kári Stefánsson, CEO and Founder of DeCode The Promise Remains: to use genetic data to benefit patients

15 Back-up slides

16 Opportunities in Russia – population with strong founder effect  BRCA1 inherited mutations are common in Russia and demonstrate very pronounced founder effect.  A single BRCA1 allele, BRCA1 5382insC, may explain up to 4% of breast and 15% of ovarian cancer incidence.  BRCA1 hereditary lesions may also contribute to a substantial proportion of “non-canonical” cancer types; for instance the 5382insC mutation is detected in 4% of stomach cancers in Russia.  CHEK-2 mutations may be accountable for up to 4% of breast cancers in Russia.  BRCA2 mutations are very rare in breast and ovarian cancers in Russia.

17 Drug Targets – slow rate of innovation Of the 361 new molecular entities approved by the FDA between 1989 and 2000, only 6% targeted a previously undrugged protein domain Between 1982 and 2005:  The rate of new 'drugged' targets per year  The rate of new protein families per year


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