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Indications discovery and drug repurposing


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Slides for meeting to be held March 14th in Philadelphia - indications discovery and drug repurposing

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Indications discovery and drug repurposing

  1. 1. In silico repositioning of approved drugs and collaboration for rare and neglected diseases Sean Ekins Collaborations in Chemistry, Fuquay Varina, NC. Collaborative Drug Discovery, Burlingame, CA. Department of Pharmacology, University of Medicine & Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, NJ. School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland, Baltimore, MD.
  2. 2. Abigail Alliance for Better Access to Developmental Drugs Addi & Cassi Fund American Behcet's Disease Association Amschwand Sarcoma Cancer Foundation BDSRA (Batten Disease Support and Research Association) Beyond Batten Disease Foundation Blake’s Purpose Foundation Breakthrough Cancer Coalition Canadian PKU & Allied Disorders Center for Orphan Disease Research and Therapy, University of Pennsylvania Children’s Cardiomyopathy Foundation Cooley's Anemia Foundation Dani’s Foundation Drew’s Hope Research Foundation EveryLife Foundation for Rare Diseases GIST Cancer Awareness Foundation Hannah's Hope Fund Hope4Bridget Foundation Hypertrophic Cardiomyopathy Association - HCMA I Have IIH ISRMD (International Society for Mannosidosis and Related Diseases) Jacob’s Cure Jain Foundation Jonah's Just Begun-Foundation to Cure Sanfilippo Inc. Kids V Cancer Kurt+Peter Foundation LGMD2I Research Fund Lymphangiomatosis & Gorham's Disease Alliance MAGIC Foundation Manton Center for Orphan Disease Research MarbleRoad Mary Payton's Miracle Foundation Midwest Asian Health Association (MAHA) MPD Support National Gaucher Foundation National MPS Society National Organization Against Rare Cancers National PKU Alliance National Tay-Sachs & Allied Diseases Association New Hope Research Foundation NextGEN Policy Noah's Hope - Batten disease research fund Our Promise to Nicholas Foundation Oxalosis and Hyperoxaluria Foundation Partnership for Cures Periodic Paralysis Association RARE Project Ryan Foundation for MPS Children Sanfilippo Foundation for Children Sarcoma Foundation of America Solving Kids' Cancer Taylor's Tale: Fighting Batten Disease Team Sanfilippo Foundation The Alliance Against Alveolar Soft Part Sarcoma The Life Raft Group The NOMID Alliance The Transverse Myelitis Association The XLH Network, Inc. United Pompe Foundation Many of these groups are doing R&D on a shoestring how can we help? Just some of the many rare disease groups
  3. 3. Jonah has Sanfilippo Syndrome Jonah’s mum, Jill Wood started a foundation, raises money, awareness, funds ground breaking research happening globally. Willing to sell her house to fund research to save Jonah. She is in a race against time – what can we do to translate ideas from bench to patient faster? How do we get more ideas tested, who funds the research How can we help parents and families ? One example of why Pharmaceutical R&D needs disrupting
  4. 4. How to do it better? What can we do with software to facilitate it ? The future is more collaborative We have tools but need integration <ul><li>Groups involved traverse the spectrum from pharma, academia, not for profit and government </li></ul><ul><li>More free, open technologies to enable biomedical research </li></ul><ul><li>Precompetitive organizations, consortia.. </li></ul><ul><li>How can it help orphan and rare diseases? </li></ul>A starting point is collaboration; software may help A core root of the current inefficiencies in drug discovery are due to organizations’ and individual’s barriers to collaborate effectively Bunin & Ekins DDT 16: 643-645, 2011
  5. 5. Example ; Collaborative Drug Discovery Platform <ul><ul><li>CDD Vault – Secure web-based place for private data – private by default </li></ul></ul><ul><ul><li>CDD Collaborate – Selectively share subsets of data </li></ul></ul><ul><ul><li>CDD Public – public data sets - Over 3 Million compounds, with molecular properties, similarity and substructure searching, data plotting etc </li></ul></ul><ul><ul><ul><li>will host datasets from companies, foundations etc </li></ul></ul></ul><ul><ul><ul><li>vendor libraries (Asinex, TimTec, ChemBridge) </li></ul></ul></ul><ul><ul><li>Unique to CDD – simultaneously query your private data, collaborators’ data, & public data, Easy GUI </li></ul></ul>
  6. 6. <ul><li>3 Academia/ Govt lab – Industry screening partnerships </li></ul><ul><li>CDD used for data sharing / collaboration – along with cheminformatics expertise </li></ul><ul><li>Previously supported larger groups of labs – many continued as customers </li></ul>How CDD software has been used: BMGF CDD is a partner on a 5 year project supporting >20 labs and proving cheminformatics support More Medicines for Tuberculosis
  7. 7. Ekins et al, Trends in Microbiology 19: 65-74, 2011 Fitting into the drug discovery process Insert your disease here…
  8. 8. Searching for TB molecular mimics; collaboration Lamichhane G, et al Mbio, 2: e00301-10, 2011 Modeling – CDD Biology – Johns Hopkins Chemistry – Texas A&M
  9. 9. <ul><li>Combining cheminformatics methods and pathway analysis </li></ul><ul><li>Identified essential TB targets that had not been exploited </li></ul><ul><li>Used resources available to both to identify targets and molecules that mimic substrates </li></ul><ul><li>Computationally searched >80,000 molecules - tested 23 compounds in vitro (3 picked as inactives), lead to 2 proposed as mimics of D-fructose 1,6 bisphosphate, (MIC of 20 and 40 ug/ml) </li></ul><ul><li>POC took < 6mths - - Submitted phase II STTR, Submitted manuscript </li></ul><ul><li>Still need to test vs target - verify hits vs suggested target </li></ul>Ekins et al, Trends in Microbiology Feb 2011 Phase I STTR - NIAID funded collaboration with Stanford Research International Sarker et al, submitted 2011
  10. 10. Finding Promiscuous Old Drugs for New Uses <ul><li>Research published in the last six years - 34 studies - Screened libraries of FDA approved drugs against various whole cell or target assays in vitro. </li></ul><ul><li>1 or more compounds with a suggested new bioactivity </li></ul><ul><li>13 drugs were active against more than one additional disease in vitro </li></ul><ul><li>Perhaps screen these first? </li></ul>Ekins and Williams, Pharm Res 28(8):1785-91, 2011
  11. 11. Finding Promiscuous Old Drugs for New Uses <ul><li>109 molecules were identified by screening in vitro </li></ul><ul><li>Statistically more hydrophobic (log P) and higher MWT than orphan-designated products with at least one marketing approval for a common disease indication or one marketing approval for a rare disease from the FDA’s rare disease research database. </li></ul><ul><li>Created multiple structure searchable databases in CDD </li></ul><ul><li>This work was unfunded </li></ul><ul><li>Data for repurposing in publications is increasing but who is tracking it? </li></ul><ul><li>FDA databases for rare disease research are XL files!! </li></ul><ul><li>After this paper published NCGC released NPC browser….but </li></ul>
  12. 12. Ekins and Williams, Pharm Res 28(8):1785-91, 2011 Analysis of datasets <ul><li>Promiscuous repurposed compounds are more hydrophobic </li></ul><ul><li>orphan repurposed hits are less hydrophobic </li></ul>Dataset ALogP Molecular Weight Number of Rotatable Bonds Number of Rings Number of Aromatic Rings Number of Hydrogen bond Acceptors Number of Hydrogen bond Donors Molecular Polar Surface Area Compounds identified in vitro with new activities (N = 109) * 3.1 ± 2.6 428.4 ± 202.8 5.4 ± 3.8 3.8 ± 1.9 2.0 ± 1.4 5.6 ± 4.2 2.0 ± 1.9 89.6 ± 69.3 Compounds identified in vitro with multiple new activities (N = 13) 3.6 ± 2.7 442.8 ± 150.0 5.1 ± 3.1 4.2 ± 1.5 1.8 ± 1.2 5.5 ± 4.6 2.2 ± 3.3 79.5 ± 78.8 Orphan designated products with at least one marketing approval for a common disease indication (N = 79) # 1.4 ± 3.0 b 353.2 ± 218.8 a 5.3 ± 6.4 2.8 ± 1.7 a 1.2 ± 1.3 b 5.3 ± 6.0 2.5 ± 3.0 99.2 ± 110.7 Orphan designated products with at least one marketing approval for a rare disease indication (N = 52) # 0.9 ± 3.3 b 344.4 ± 233.5 a 5.3 ± 5.3 2.4 ± 1.9 b 1.3 ± 1.4 a 6.2 ± 4.2 2.7 ± 2.8 114.2 ± 85.3
  13. 13. Dataset Intersection Orphan + Common Use Orphan + Rare use In vitro hits 0 5 3 0 Do these represent frequent actives or promiscuous compounds?
  14. 14. Government Databases Should Come With a Health Warning Openness Can Bring Serious Quality Issues NPC Browser Database released and within days 100’s of errors found in structures Williams and Ekins, DDT, 16: 747-750 (2011) Science Translational Medicine 2011 This work was unfunded Science Translational Medicine 2011
  15. 15. Towards a Gold Standard: Regarding Quality in Public Domain Chemistry Databases and Approaches to Improving the Situation Antony J. Williams, Sean Ekins and Valery Tkachenko , Drug Discovery Today, In Press 2012 Data Errors in the NPC Browser: Analysis of Steroids Substructure # of Hits # of Correct Hits No stereochemistry Incomplete Stereochemistry Complete but incorrect stereochemistry Gonane 34 5 8 21 0 Gon-4-ene 55 12 3 33 7 Gon-1,4-diene 60 17 10 23 10
  16. 16. Ekins S and Williams AJ, MedChemComm, 1: 325-330, 2010. Need to learn from neglected disease research Do we really need to screen massive libraries of compounds as we have for TB and malaria? And groups are screening compounds already screened by others!
  17. 17. 2D Similarity search with “hit” from screening Export database and use for 3D searching with a pharmacophore or other model Suggest approved drugs for testing - may also indicate other uses if it is present in more than one database Suggest in silico hits for in vitro screening Key databases of structures and bioactivity data FDA drugs database Repurpose FDA drugs in silico Ekins S, Williams AJ, Krasowski MD and Freundlich JS, Drug Disc Today, 16: 298-310, 2011
  18. 18. PXR antagonist drug discovery <ul><li>Cancer drugs act as PXR agonists, increasing own metabolism and transport out of cells </li></ul><ul><li>How could we block this? </li></ul><ul><li>Preferably find a clinically used drug? </li></ul>
  19. 19. PXR Antagonist Pharmacophore <ul><li>Compounds can “switch off” PXR </li></ul><ul><li>3 azoles shown to antagonize PXR ~ equipotent (10-20  M) mutagenesis data indicates they bind outer surface of PXR – AF-2 binding pocket </li></ul><ul><li>Can a pharmacophore infer features needed to antagonize hPXR? </li></ul>Ekins et al., Mol Pharmacol 72:592–603, (2007) Huang et al., Oncogene 26: 258-268 (2007), Wang et al., Clin Cancer Res 13: 2488-2495 Hydrophobe / ring aromatic H-bond acceptors Antagonists require a balance between hydrophobic and hydrogen bonding features.
  20. 20. PXR Antagonist Binding Site/s - Docking Ekins et al., Mol Pharmacol 72:592–603, (2007) 2 separate binding sites on either side of Lys277- identified with GOLD rigid docking in 1NRL chain A azoles would interfere with SRC-1 binding in the AF-2 site. One site is predominantly hydrophobic -15 amino acids. Lys277 most likely serves as a “charge clamp” for interaction between the co-activator SRC1 (His687) and PXR Azoles compete with SRC-1 for AF-2 Piperazine etc may not be necessary - Solvent exposed
  21. 21. <ul><li>Screened four databases – known drugs and commercially available molecules, N = 3533 </li></ul><ul><li>67 hits retrieved </li></ul><ul><li>We tested in vitro a small number based on their pharmacophore fit values and mapping to the pharmacophore features </li></ul><ul><li>Followed up hits with similarity searching using, </li></ul>PXR Antagonist Database Searching Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
  22. 22. PXR Antagonist Database Searching Finds New Hits SPB00574 2.14 24.8 SPB03255 2.22 6.3 Catalyst fit IC 50 (  M) Further similarity searching retrieved 4 active analogs of SPB03255 Also tested leflunomide – FDA approved drug 6.8  M Ekins et al., Mol Pharmacol, 74(3):662-72 , (2008)
  23. 23. We can do the same for rare diseases: Searching for Potential Chaperones for Sanfilippo Syndrome <ul><li>Pshezhetsky et al showed Glucosamine rescues HGSNAT mutants </li></ul><ul><li>Glucosamine used to create a 3D common features pharmacophore using Discovery Studio. </li></ul><ul><li>The pharmacophore + ligand van der Waals shape was used to search multiple 3D databases </li></ul><ul><li>FDA drugs, natural products, orphan drugs, KEGG, CSF metabolome etc. </li></ul><ul><li>The pharmacophore consists of a positive ionizable (red) and 3 hydrogen bond donor groups (purple). </li></ul><ul><li>Selected hits for experimental testing </li></ul><ul><li>Collaboration ongoing! </li></ul>e.g. Isofagomine maps pharmacophore
  24. 24. Crowdsourcing Project “Off the Shelf R&D” All pharmas have assets on shelf that reached clinic “ Off the Shelf R&D” Get the crowd to help in repurposing / repositioning these assets How can software help? - Create communities to test - Provide informatics tools that are accessible to the crowd - enlarge user base - Data storage on cloud – integration with public data - Crowd becomes virtual pharma-CROs and the “customer” for enabling services
  25. 25. Massive models – using open tools Gupta RR, et al., Drug Metab Dispos, 38: 2083-2090, 2010 Can we get pharmas to share models rather than data – precompetitive? What can be developed with very large training and test sets? training 194,000 and testing 39,000 Open molecular descriptors / models vs commercial descriptors Potential to share models selectively with collaborators e.g. academics, rare & neglected disease researchers Lundbeck Pfizer Merck GSK Novartis Lilly BMS Allergan Bayer AZ Roche BI Merk KGaA
  26. 26. Future Drug Discovery Pharma R&D already looking like this – a big network I think we are seeing something like this with all the orphan disease networks too Massive collaboration networks – software enabled. We are in “Generation App” Crowdsourcing will have a role in R&D. Drug discovery possible by anyone with “app access” Ekins & Williams, Pharm Res, 27: 393-395, 2010.
  27. 27. <ul><li>Make science more accessible = >communication </li></ul><ul><li>Mobile – take a phone into field /lab and do science more readily than on a laptop </li></ul><ul><li>MolSync + DropBox + MMDS = Share molecules as SDF files on the cloud = collaborate </li></ul><ul><li>How could orphan disease research leverage apps? </li></ul>Mobile Apps for Drug Discovery Williams et al DDT 16:928-939, 2011
  28. 28. Apps for collaboration ODDT – Open drug discovery teams Flipboard-like app for aggregating social media for diseases etc Create virtual drug discovery teams link to open notebook science Alex Clark, Molecular Materials Informatics, Inc Williams et al DDT 16:928-939, 2011 Clark et al submitted 2012 Ekins et al submitted 2012
  29. 29. The Evolving Pfizer R&D Ecosystem <ul><li>Evolving paradigm for the discovery of medicines (Collaborative) </li></ul><ul><ul><li>A vision that points towards open innovation and collaborations </li></ul></ul><ul><ul><li>Open research model to collectively share scientific expertise </li></ul></ul><ul><li>Enhance speed of drug discovery beyond individual resource capabilities (Speed) </li></ul><ul><ul><li>Limited research budgets and capabilities driving greater shared resources </li></ul></ul><ul><ul><li>Goal to see all partners succeed by accelerating the SCIENCE </li></ul></ul><ul><ul><li>Synergize Pfizer’s strengths with Research Partners (Knowledge) </li></ul></ul><ul><ul><ul><li>Pair Pfizer’s design, cutting edge tools, synthetic excellence with research partners (academics, not-for-profits, venture capitalists, or biotechs) to develop break through science, novel targets, and indications of unmet medical need </li></ul></ul></ul><ul><ul><li>Current example of academic and not-for-profits partners (Discover and Publish) </li></ul></ul><ul><ul><ul><li>Drive to publish in top journal with science receiving high visibility and interest </li></ul></ul></ul><ul><ul><li>Contacts: </li></ul></ul><ul><ul><ul><li>Travis Wager ( [email_address] ) </li></ul></ul></ul><ul><ul><ul><li>Paul Galatsis ( [email_address] ) </li></ul></ul></ul>a few months ago we entered into a collaboration with the giant pharmaceutical industry Pfizer to test some of their leading molecules for potential relevance to HD. Found on the internet Body clock mouse study suggests new drug potential Mon, Aug 23 2010 By Kate Kelland LONDON (Reuters) - Scientists have used experimental drugs being developed by Pfizer to reset and restart the body clock of mice in a lab and say their work may offer clues on a range of human disorders, from jetlag to bipolar disorder.
  30. 30. The newest drug discovery reality Gone full circle Pharma now becoming more like rare disease groups Working on a shoestring, limited resources, leverages academics, partners with disease foundations, funded by them – open innovation Collaboration is a core element If Jill Wood or others can become a virtual pharma, if they have enough domain knowledge and drive Pfizer and other pharmas can be more like Jill, smaller, leaner, working on many more diseases as collaborators In silico approaches and collaboration = central to rare disease drug discovery
  31. 31. Acknowledgments <ul><li>Jill Wood </li></ul><ul><li>Antony J. Williams (RSC) </li></ul><ul><li>Rishi Gupta, Eric Gifford, Ted Liston, Chris Waller (Pfizer) </li></ul><ul><li>Joel Freundlich (Texas A&M), Gyanu Lamichhane (Johns Hopkins) </li></ul><ul><li>Carolyn Talcott, Malabika Sarker , Peter Madrid, Sidharth Chopra (SRI International) </li></ul><ul><li>MM4TB colleagues </li></ul><ul><li>Matthew D. Krasowski (University of Iowa) </li></ul><ul><li>Sridhar Mani (Albert Einstein College of Medicine) </li></ul><ul><li>Alex Clark (Molecular Materials Informatics, Inc) </li></ul><ul><li>Vladyslav Kholodovych, Ni Ai, Dima Chekmarev, Sandhya Kortagere, Chia-Wei Li, J Don Chen, William J. Welsh (UMDNJ) </li></ul><ul><li>Accelrys </li></ul><ul><li>CDD – Barry Bunin </li></ul><ul><li>Funding BMGF, NIAID. </li></ul><ul><li>Everyone that has shared data in CDD.. </li></ul><ul><li>Email: </li></ul><ul><li>Slideshare: </li></ul><ul><li>Twitter: collabchem </li></ul><ul><li>Blog: </li></ul><ul><li>Website: </li></ul>