1. Sean Ekins, M.Sc, Ph.D., D.Sc. Collaborations in Chemistry, Fuquay-Varina, NC. Collaborative Drug Discovery, Burlingame, CA. School of Pharmacy, Department of Pharmaceutical Sciences, University of Maryland. 215-687-1320 [email_address] Computational Approaches to Toxicology
2. … mathematical learning will be the distinguishing mark of a physician from a quack… Richard Mead A mechanical account of poisons in several essays 2nd Edition, London, 1708.
5. Consider Absorption, Distribution, Metabolism, Excretion and Toxicology properties earlier in Drug Discovery Combine in silico, in vitro and in vivo data - Approach equally applicable to consumer products and getting information on chemicals. Ekins et al., Trends Pharm Sci 26: 202-209 (2005)
7. Why Use Computational Models For Toxicology ? Goal of a model – Alert you to potential toxicity, enable you to focus efforts on best molecules – reduce risk Selection of model – trade off between interpretability, insights for modifying molecules, speed of calculation and coverage of chemistry space – applicability domain Models can be built with proprietary, open and commercial tools software (descriptors + algorithms) + data = model/s Human operator decides whether a model is acceptable
10. Key enablers: Hardware is getting smaller 1930’s 1980s 1990s Room size Desktop size Not to scale and not equivalent computing power – illustrates mobility Laptop Netbook Phone Watch
15. L. Carlsson,et al., BMC Bioinformatics 2010, 11: 362 MetaPrint 2D in Bioclipse- free metabolism site predictor Uses fingerprint descriptors and metabolite database to learn frequencies of metabolites in various substructures
20. * * Maximum likelihood NHR phylogeny Ekins et al., BMC Evol Biol. 8(1):103 (2008) * * * * *
22. Human r=0.7 Zebrafish r=0.8 Mouse r=0.8 Rabbit r=0.8 Chicken r=0.7 TCDD (green) and 5 -pregnane-3,20-dione (grey) Ekins et al., BMC Evol Biol 8(1):103 (2008) Pharmacophores show PXR evolution Rat r=0.7
31. Fingolimod (Gilenya) for MS (EMEA and FDA) Paliperidone for schizophrenia Pirfenidone for Idiopathic pulmonary fibrosis Roflumilast for pulmonary disease Predictions for newly approved EMEA compounds Can we get DILI data for these?
34. Diao, Ekins, and Polli, Pharm Res, 26, 1890, (2009) +ve -ve hOCTN2 quantitative pharmacophore and Bayesian model Diao et al., Mol Pharm, 7: 2120-2131, 2010 r = 0.89 vinblastine cetirizine emetine
35. hOCTN2 quantitative pharmacophore and Bayesian model Bayesian Model - Leaving 50% out 97 times external ROC 0.90 internal ROC 0.79 concordance 73.4%; specificity 88.2%; sensitivity 64.2%. Lab test set (N = 27) Bayesian model has better correct predictions (> 80%) and lower false positives and negatives than pharmacophore (> 70%) Predictions for literature test set (N=32) not as good as in house – mean max Tanimoto similarity were ~ 0.6 Diao et al., Mol Pharm, 7: 2120-2131, 2010 PCA used to assess training and test set overlap
36. Among the 21 drugs associated with rhabdomyolysis or carnitine deficiency, 14 (66.7%) provided a C max/ K i ratio higher than 0.0025. Among 25 drugs that were not associated with rhabdomyolysis or carnitine deficiency, only 9 (36.0%) showed a C max / K i ratio higher than 0.0025. Rhabdomyolysis or carnitine deficiency was associated with a C max / K i value above 0.0025 (Pearson’s chi-square test p = 0.0382). limitations of C max / K i serving as a predictor for rhabdomyolysis -- C max / K i does not consider the effects of drug tissue distribution or plasma protein binding. hOCTN2 association with rhabdomyolysis
37. Could all pharmas share their data as models with each other? Increasing Data & Model Access Ekins and Williams, Lab On A Chip, 10: 13-22, 2010.
42. Merck KGaA Combining models may give greater coverage of ADME/ Tox chemistry space and improve predictions? Model coverage of chemistry space Lundbeck Pfizer Merck GSK Novartis Lilly BMS Allergan Bayer AZ Roche BI Merk KGaA
44. PathwayStudio Pathway / Network/ Database Software Available Ekins et al., in High Content Screening , Eds. Giuliano, Taylor & Haskin (2006)
47. Measure Xu JJ, Ekins S, McGlashen M and Lauffenburger D, in Ekins S and Xu JJ, Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools, P351-379, 2009. 4M Systems Biology Manipulate Model Mine
53. How Could Green Chemistry Benefit From These Models? Chem Rev. 2010 Oct 13;110(10):5845-82 … Nature 469, 6 Jan 2011
Hinweis der Redaktion
The process of ADME/tox can now be viewed as an iterative process were molecules may be assessed against many properties early on before selecting molecules for clinical trials. These endpoints may be complex like toxicity.
CDD Experienced Team Innovates and Executes Barry Bunin, PhD (Pres. & Cofounder as first Eli Lilly EIR) Libraria (CEO, Pres.-CSO), Arris Pharmaceuticals (Sr. Scientist), Genentech, UC Berkeley (Ellman), Columbia University, author. Moses Hohman, PhD (Director Software Engineering) Northwestern Assoc. Director of Bioinformatics, Thoughtworks, Inc., U of Chicago (PhD), Harvard ( magna cum laude, Physics) Sylvia Ernst, PhD (Director Community Growth & Sales) Left 800-lb Gorillas: Accelrys-Scitegic, MDL-Elsevier-Beilstein Peter Cohan (BOD & Overall Sales Strategy) Symyx (VP Bus Dev & President-Discovery Tools), MDL (VP Customer Marketing), www.secondderivative.com, author. Omidyar Network, Founders Fund, & Lilly (BOD observers) WSGR (Corporate Counsel), Rina Accountancy (GAAP compliance) Partners: Hub Consortium Members, ChemAxon, DNDi, MMV, Sandler Center… CDD SAB: Christopher Lipinski PhD, James McKerrow, MD PhD, David Roos PhD, Adam Renslo PhD, Wes Van Voorhis, MD PhD
We are seeing a convergence of HT-techniques, with databases, ADME/Tox modeling and systems modeling – we believe we are embarking on a new field - systems-ADME/Tox modeling.
Figure Legend. Systems Biology aims to integrate Mining, Modeling, Manipulation, and Measurements.