Darshan Mehta Ph.D.

Leadership Role

Visiting Scientist — Division of Biochemical Toxicology

Darshan Mehta, Ph.D.
(870) 543-7121
NCTRResearch@fda.hhs.gov

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Background

Dr. Darshan Mehta is a visiting scientist at FDA’s National Center for Toxicological Research (NCTR) in the Division of Biochemical Toxicology. He received his bachelor’s degree in chemical engineering in 2008 from the Institute of Chemical Technology (formerly UDCT) in Mumbai, India. After working at Reliance Industries Limited, he traveled to the United States to pursue graduate studies and received a master’s degree in applied statistics in 2013 and a Ph.D. in chemical engineering in 2016 from Ohio State University. His dissertation research focused on developing novel Quantitative Structure-Activity Relationship approaches for predicting chemically induced toxicity, specifically mutagenicity and skin sensitization. His work was recognized by the American Chemical Society’s Division of Chemical Informatics (CINF) when he was awarded the CINF scholarship for scientific excellence in 2015. Following his graduate studies, he accepted an Oak Ridge Institute for Science and Education (ORISE) postdoctoral fellowship with the Office of Food Additive Safety at FDA’s Center for Food Safety and Applied Nutrition where he helped develop chemically intelligent software platforms for the identification of structural analogs and automated tools for redacting confidential information to share data with external stakeholders. He then joined NCTR as an ORISE fellow in late 2017 to gain experience in bioinformatics, drug labeling, and pharmacogenomics. After a one-year stint, he moved to NCTR’s Division of Biochemical Toxicology to work on developing a multi-pathway physiologically based pharmacokinetic (PBPK) model for nicotine in humans. He was converted to an FDA staff fellow in September 2019 and has since been involved in multiple projects providing modeling, statistical, and pharmacokinetic data analysis support.

Research Interests

Dr. Mehta’s research interests lie in modeling chemical effects in biological systems using computational and statistical modeling methods. He specializes in the development and utilization of PBPK models for predicting the disposition of chemicals in animals and humans. These PBPK models are useful in determining the internal tissue dosimetry for a given exposure scenario as well as in understanding the ADME (absorption, distribution, metabolism, and excretion) profile of chemicals in intact biological organisms. Dr. Mehta is skilled in multiple computer programming languages and in various data analysis, cheminformatics, and PBPK modeling software platforms. He looks forward to collaborating with other FDA product centers to help advance the mission of protecting and promoting public health.

Professional Societies/National and International Groups

American Chemical Society (ACS)
Member
2015 – 2016

Society of Toxicology (SOT)
Member
2016 – 2017

Selected Publications

Challenges in Predicting the Pharmacokinetics of Drugs in Premature and Mature Newborns: Example with Piperacillin and Tazobactam.
Fisher J.W., Mehta D., Li M., and Yang X.
In: Mattison D. and Halbert L., eds.
Clinical Pharmacology During Pregnancy. 2021, 437-456, doi: 10.1016/B978-0-12-818902-3.00019-1

Toxicokinetic and Genotoxicity Study of NNK in Male Sprague-Dawley Rats Following Nose-Only Inhalation Exposure, Intraperitoneal Injection, and Oral Gavage.
Hu S., Bryant M. S., Sepehr E., Kang H., Trbojevich R., Lagaud G., Mehta D., Ding W., Mittelstaedt R.A., Pearce M.G., Bishop M.E., Davis K.J., Lewis S.M., Chemerynski S., Yee S. B., Coraggio M., Rosenfeldt H., Yeager R.P., Howard P.C., and Tang Y.
Toxicol Sci. 2021, 182(1):10-28, doi: 10.1093/toxsci/kfab049.

Study of Pharmacogenomic Information in FDA-approved Drug Labeling to Facilitate Application of Precision Medicine.
Mehta D., Uber R., Ingle T., Li C., Liu Z., Thakkar S., Ning B., Wu L., Yang J., Harris S., Zhou G., Xu J., Tong W., Lesko L., and Fang H.
Drug Discov Today. 2020, 25(5):813-820, doi: 10.1016/j.drudis.2020.01.023 [Epub Feb 04, 2020].

Characterizing Biopersistence Potential of the Metabolite 5:3 Fluorotelomer Carboxylic Acid After Repeated Oral Exposure to the 6:2 Fluorotelomer Alcohol.
Kabadi S.V., Fisher J.W., Doerge D.R., Mehta D., Aungst J., and Rice P.
Toxicol Appl Pharmacol. 2020, 388:114878, doi: 10.1016/j.taap.2020.114878 [Epub Jan 07, 2020].

Fundamentals of Physiologically Based Pharmacokinetic Modeling.
Fisher J.W., Yang X., Mehta D., Housand C., and Lin Z.
In: Fisher J., Gearhart J., and Lin Z., eds.
Physiologically Based Pharmacokinetic (PBPK) Modeling: Methods and Applications in Toxicology and Risk Assessment. 2020: 57-80, doi: 10.1016/B978-0-12-818596-4.00003-5.

Chemical Absorption and Writing Code for Portals of Entry.
Fisher J.W., Gearhart J.M., Campbell J.L. Jr., and Mehta D.
In: Fisher J., Gearhart J., and Lin Z., eds.
Physiologically Based Pharmacokinetic (PBPK) Modeling: Methods and Applications in Toxicology and Risk Assessment. 2020: 127-138, doi: 10.1016/B978-0-12-818596-4.00005-9.

Ontogeny Equations with Probability Distributions for Anthropomorphic Measurements in Preterm and Term Neonates and Infants For Use in a PBPK Model.
Yang X., Wu H., Mehta D., Sullivan M.C., Wang J., Burckart G.J., Troutman J.A., and Fisher J.W.
Comput Toxicol. 2019, 11:101-117, doi: 10.1016/j.comtox.2019.03.007 [Epub Apr 01, 2019].

Study of Serious Adverse Drug Reactions Using FDA-approved Drug Labeling and MedDRA.
Wu L., Ingle T., Liu Z., Zhao-Wong A., Harris S., Thakkar S., Zhou G., Yang J., Xu J., Mehta D., Ge W., Tong W., and Fang H.
BMC Bioinformatics. 2019, 20(Suppl 2):97:129-139, doi: 10.1186/s12859-019-2628-5.

Cheminformatics in Modern Regulatory Science.
Yang C., Rathman J.F., Tarkhov A., Sacher O., Kleinoeder T., Liu J., Magdziarz T., Mostraq A., Marusczyk J., Mehta D., Schwab C., and Bienfait B.
In: Engel T. and Gasteiger J., eds.
Applied Cheminformatics: Achievements and Future Opportunities. 2018: 439-470, doi: 10.1002/9783527806539.ch8.

Contact Information: Darshan Mehta; (870)543-7121