NICHOLAS TATONETTI, Ph.D.Department of Biomedical Informatics,
Columbia Initiative for Systems Biology, &
Department of Medicine
622 West 168th St. VC5
New York, NY 10032
212 305 2055
Columbia University, New York, NY
Assistant Professor of Biomedical Informatics (in the Department of Biomedical Informatics, Columbia Initiative for Systems Biology, and the Department of Medicine), 2012-present
Director, Clinical Informatics, Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, 2013-present
Stanford University, Stanford, CA
Department of Energy Office of Science Graduate Fellow in the Biomedical Informatics Training Program, 2008-2012.
Doctoral Advisor: Russ Altman,
Doctoral Committee: Atul Butte, Trevor Hastie, and Phillip Tsao,
Dissertation Title: "Data-driven Detection, Prediction, and Validation of Drug-Drug Interactions."
Professional Society Memberships
American Medical Informatics Association (2011-)
International Society for Computational Biology (2012-)
American Statistical Association (2013-)
Ferino G, Cadoni E, Matos MJ, Quezada E, Uriarte E, Santana L, Vilar S, Tatonetti NP, Yanez M, Vina D, Picciau C, Serra S, Delogu G, MAO Inhibitory Activity of 2‐Arylbenzofurans versus 3‐Arylcoumarins: Synthesis, in vitro Study, and Docking Calculations. ChemMedChem.
S Vilar, E Uriarte, L Santana, NP Tatonetti, C Friedman. Detection of Drug-Drug Interactions by Modeling Interaction Profile Fingerprints. PLoS One 8 (3), e58321.
White RW, Tatonetti NP, Shah NH, Altman RB, Horvitz E, Web-scale pharmacovigilance: listening to signals from the crowd. J Am Med Inform Assoc (2013).
Matos MJ, Vilar S, Gonzalez-Franco RM, Uriarte E, Santana L, Friedman C, Tatonetti NP, Viña D, Fontenla JA, Novel (coumarin-3-yl)carbamates as selective MAO-B inhibitors: Synthesis, in vitro and in vivo assays, theoretical evaluation of ADME properties and docking study. European Journal of Medicinal Chemistry 63, 151-161 (2013).
Tatonetti NP, Denny JC, Altman RB, Response to "Use of an algorithm for identifying hidden drug-drug interactions in adverse event reports" by Gooden et al, J Am Med Inform Assoc (2013), doi:10.1136/amiajnl-2012-001603.
Vilar S, Uriarte E, Santana L, Tatonetti NP, Friedman C, Detection of drug-drug interactions by modeling interaction profile fingerprints. PLoS ONE 8, e58321 (2013).
Tatonetti NP, Ye PP, Daneshjou R, Altman RB, Data-driven prediction of drug effects and interactions. Science Translational Medicine 4, 125ra31 (2012).
Karczewski, KJ, Tirrell RP, Cordero P, Tatonetti NP, Dudley JT, Salari K, Snyder M, Altman RB, Kim SK. Interpretome: A freely available, modular, and secure personal genome interpretation engine. Pac Symp Biocomput 17:339-350(2012)
Karczewski, K.J. Tatonetti NP, Landt SG, Yang X, Slifer T, Altman RB, Snyder M. Cooperative transcription factor associations discovered using regulatory variation. Proc Natl Acad Sci USA 108, 13353–13358 (2011).
Tatonetti, N.P., Fernald, G.H. & Altman, R.B. A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports. J Am Med Inform Assoc (2011) DOI:10.1136/amiajnl-2011-000214
Tatonetti NP, Denny JC, Murphy SN, Fernald GH, Krishnan G, Castro V, P Yue, PS Tsao, Kohane I, Roden DM, and Altman RB. Detecting Drug Interactions From Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels Clinical Pharmacology & Therapeutics 2011 DOI:10.1038/clpt.2011.83
Tatonetti NP*, Dudley JT*, Sagreiya H, Butte AJ, Altman RB. An integrative method for scoring candidate genes from
association studies: application to warfarin dosing. BMC Bioinformatics 2010 11(Suppl 9):S9.
Garten Y*, Tatonetti NP*, Altman RB. Improving the prediction of pharmacogenes using
text-derived drug-gene relationships. Pac Symp Biocomput (2010) pp. 305-14.
Tatonetti NP, Liu T, Altman RB. Predicting drug side-effects by chemical systems biology. Genome Biol (2009) vol. 10 (9) pp. 238, PMID:19723347
* Denotes equal contribution.
Invited Talks and Panels
Drug-drug interaction detection in Observational Clinical Data.
Institute of Medicine workshop on Learning Health Care Systems, Washington, DC April 2013.
Hypothesis generation in large-scale Observational Data.
Center for Computational Biology and Bioinformatics, IUPUI, Indianapolis, IN March 2013.
Mining for adverse drug-drug interactions in large observational data sets.
Annual Meeting of the Association of Clinical Pharmacology and Therapeutics, Indianapolis, IN March 2013.
Leveraging clinical data for biological discovery.
Living Well Through Data, New York, NY, October 2012.
Mining for adverse drug-drug interactions in large observational data sets.
3rd Annual Pacific Coast Statisticians and Pharmacometricians Innovation Conference, June 2012.
Detecting hidden drug-drug interactions in Adverse Event Reports
Journal of the American Medical Informatics Association Editor's Choice Journal Club. November 2011.
Hypothesis generation in large-scale Observational Data
IBM Healthcare Lecture Series. November 2011.
Observational Analysis in a PetaByte World
SFSU Center for Computing for Life Sciences Panel on Data Mining and Predictive Analysis: Research Applications. October 2011.
Data derived drug effects and interactions.
Stanford University Department of Epidemiology Lecture Series. October 2011.
Popular and Scientific Press
New York Times, January 2013, Mining Electronic Health Records for Revealing Health Data, link
Genome Web, December 2012, "Seventh Annual Young Investigators." link
Science Careers, April 2012, "Computational Biologists: The Next Pharma Scientists?" link
Communications of the ACM, October 2012, "Digging for Drug Facts." link
Nature, March 2012, "Drug data reveal sneaky side effects." link
Gizmodo, March 2012, "Drugs Cause About Five Times More Side Effects Than We Realized." link
GenomeWeb, March 2012, "Good Apart, Bad Together." link
ABC News SLC, March 2012, "Drugs may cause five times more side effects than previously believed." link
DrugTopics, August 2011, "Data-mining uncovers hyperglycemic drug-drug interaction between paroxetine and pravastatin." link
Journal of the American Medical Association, July 2011, "Data Mining Approach Shows Promise in Detecting Unexpected Drug Interactions." link
NewScientist, May 2011, "Common drug combo increases diabetes risk." link
US News, May 25, 2011, "Combo of Paxil, Pravachol May Raise Blood Sugar." link
NPR Shots Health Blog, May 25, 2011, "How A MacBook Pro Found Unexpected Drug Side Effects." link
Novel Statistical Methods for Observational Clinical Studies Innovation awards in population medicine research pilot grant. $25,000. (PI: Altman)
Data-driven discovery of adverse drug effects and interactions.
Late Breaking Research Presentation. Intelligent Systems for Molecular Biology (ISMB), Long Beach, CA, 2012.
Discovering hidden drug-drug interactions from Adverse Event Reports.
American Medical Informatics Association Summit on Translation Bioinformatics, San Francisco, CA, 2011
Detecting drug-drug interactions in spontaneous reporting systems.
Biomedical Computation at Stanford, Stanford, CA 2010.
A Novel Method for Scoring Candidate Genes in Association Studies: Application to Warfarin Response.
American Medical Informatics Association Summit on Translation Bioinformatics, San Francisco, CA, 2010.
MetabolODE: Optimization software for determining kinetic rate
coefficients for biochemical pathways of metabolic isotopomers.
Frontiers in Applied and Computational Mathematics, Newark, NJ, 2007.
Featured by Genome Web in the Seventh Annual Young Investigator Profiles, December 2012
Highlighted Research in the IMIA Yearbook of Medical Informatics, 2012
Top Podium Presentation Award - AMIA Summit on Translational Bioinformatics, March 2011
Best Presentation (Runner Up) - Biomedical Computation at Stanford, November 2010
Outstanding Paper Award - AMIA Summit on Translational Bioinformatics, March 2010
Department of Energy Graduate Fellowship ($150,000), September 2010
National Library of Medicine Training Grant Recipient, September 2008
Phi Beta Kappa Lifetime Member, November 2007
Beckman Scholar Award ($17,600), May 2007 - October 2008
Goldwater Scholar Honorable Mention, April 2007
ASU SOLUR Researcher Award, August 2006 - May 2007
1997 Pinto Horse Association of America National Champion, All Around-Year End Youth High Point Award
1997 Pinto Horse Association of America National Youth Reining Horse Champion
Guest Lecturer, Introduction to Biomedical Informatics, Columbia University, December 2012
Teaching Assistant for Course Design, Methods in Healthcare Informatics (BIOMEDIN215), Stanford University, March 2011
Teaching Assistant, Genomics and Personalized Medicine (GENE210), Stanford University, March 2011 - June 2011
Guest Lecturer, Statistical Genetics (GENE244), Stanford University, February 2011
Teaching Assistant, Representations and Algorithms for Computational Molecular Biology (BIOMEDIN214), Stanford University, March 2010 - June 2010
Teaching Assistant, Modeling biomedical systems: ontology, terminology, problem solving (BIOMEDIN210), Stanford University, September 2009 - December 2009
Related and Professional Experience
Chief Execute Officer, Stimulomics, Inc., Portola Valley, CA 2009-2012
Chief Science Officer, Mophilia, Inc., Mountain View, CA 2009-2010
Co-Founder (volunteer), The CHERUB Foundation, Tempe, AZ 2006-2008
Chief Technical Officier (volunteer), The Triple Helix, Inc., Ithica, NY 2006-2007
Vice President/Co-Founder (volunteer), The Triple Helix at ASU, Tempe, AZ 2006
Founder/Owner, Tatonetti Web_Construction, Tempe, AZ 2003 - 2008
My work focuses on developing rigorous statistical and computational models for addressing these primary shortcomings of observational data analysis in the context of disease risk and drug response.
In my thesis work I developed novel statistical and computational algorithms to analyze large scale clinical databases for drug-drug interaction discovery. I uncovered an unexpected interaction between paroxetine and pravastatin using these methods and validated the interaction in a retrospective analysis of three independent hospital record systems. Finally, I developed tools for uncovering the molecular etiology of adverse events and applied them to mined drug-drug interactions.