No photo available
Shraddha Thakkar, MSc, MS, PhD
Dr. Shraddha Thakkar received a master’s degree and Ph.D. in bioinformatics from the University of Arkansas at Little Rock/University of Arkansas Medical Sciences, Joint Bioinformatics program. She specialized in macromolecular crystallography, cheminformatics, and structural biology. Prior to that Dr. Thakkar received an MSc. in biotechnology from Bangalore University, India. She holds 14 international patents and multiple publications in area of drug development for radiation protection, predictive toxicology, leukemia, and atherosclerosis. Her current area of research includes development of methods and classifications to enhance the understanding and prediction of drug-induced liver injury (DILI).
Dr. Thakkar has adjunct appointments at both the University of Arkansas for Medical Sciences and the University Arkansas at Little Rock (Assistant Professor). She was elected as board member of the Mid-South Computational Biology and Bioinformatics Society (MCBIOS) in 2014 and served as president of MCBIOS from 2016-2017. She also served as the chair of 1) Pharmacogenomics Group of the American Association of Pharmaceutical Scientist (AAPS) and 2) Personalized Medicine community at AAPS. Dr. Thakkar has received multiple research and leadership awards regionally and nationally and within FDA including the AAPS “Genentech Innovation in Biotechnology Award,” the American Crystallography Association’s “Margret C. Etter Student Lecturer Award,” and FDA’s “Outstanding Service Award.”
Dr. Thakkar’s research interests are in applying bioinformatics and cheminformatics for study of toxicity and drug development with specific interest in DILI. Dr. Thakkar has working in drug development, drug safety, pharmacogenomics/toxicogenomics, personalized medicine, predictive toxicity, and DILI. Her current research includes:
Managing and further developing the cheminformatics infrastructure for Liver Toxicity Knowledge Base (LTKB) for study of DILI.
Developing predictive toxicological models for DILI for preclinical toxicology.
Benchmarking and comparing computational and genomic predictive methods for toxicity.
Professional Societies/National and International Groups
Global Coalition for Regulatory Science and Research (GCRSR)
FDA Representative on the Cross-Training Working Group
2017 – Present
Executive secretary for Bioinformatics Working Group
2018 – Present
MidSouth Computational Biology and Bioinformatics Society
2014 – 2017
2016 – 2018
American Association of Pharmaceutical Scientists
2015 – 2017
2018 – 2019
2018 – 2019
AAPS Pharmacogenomics Focus Group
2013 – 2015
2015 – 2016
2016 – 2017
2017 – 2018
Publication titles are linked to text abstracts on PubMed.
Antioxidant Tocols as Radiation Countermeasures (Challenges to be Addressed to use Tocols as Radiation Countermeasures in Humans).
Nukala U., Thakkar S., Krager K.J., Breen P.J., Compadre C.M. and Aykin-Burns N.
Antioxidants. 2018, 7(2) p.33.
Drug-Induced Liver Injury (DILI) Classification and Its Application on Human DILI Risk Prediction. In Drug-Induced Liver Toxicity.
Thakkar S., Chen M., Hong H., Liu Z., Fang H. and Tong W.
Humana Press, New York. 2018, (pp. 45-59).
5. 21 Computational Toxicology
Thakkar S., Perkins R., Hong H., and Tong W.
Comprehensive Toxicology (Third Edition). 2018, Pages 327-350, ISBN 9780081006016.
The Liver Toxicity Knowledge Base (LKTB) and Drug-Induced Liver Injury (DILI) Classification for Assessment of Human Liver Injury.
Thakkar S., Chen M., Fang H., Liu Z., Roberts R. and Tong W.
Gastroenterology & Hepatology. 2018, 12(1), pp.31-38.
Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-Approved Drugs.
Hong H., Thakkar S., Chen M. and Tong W.
Scientific Reports. 2017, 7(1), p.17311.
Comprehensive Assessments of RNA-Seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.
Xu J., Gong B., Wu L., Thakkar S., Hong H. and Tong W.
Pharmaceutics. 2016, 8(1), p.8.
The FDA’s Experience with Emerging Genomics Technologies—Past, Present, and Future.
Xu J., Thakkar S., Gong B., and Tong W.
The AAPS Journal. 2016, 18(4), pp.814-818.
PEGylation of a High-Affinity Anti-(+) Methamphetamine Single Chain Antibody Fragment Extends Functional Half-Life by Reducing Clearance.
Reichard E.E., Nanaware-Kharade N., Gonzalez G.A., Thakkar S., Owens S.M., and Peterson E.C.
Pharmaceutical Research. 2016, 33(12), pp.2954-2966.
DILIrank: The Largest Reference Drug List Ranked by the Risk for Developing Drug-Induced Liver Injury in Humans.
Chen M., Suzuki A., Thakkar S., Yu K., Hu C., and Tong W.
Drug Discov Today. 2016, 21(4), pp.648-653.
Structure-Based Design Targeted at LOX-1, A Receptor for Oxidized Low-Density Lipoprotein.
Thakkar S., Wang X., Khaidakov M., Dai Y., Gokulan K., Mehta J.L. and Varughese K.I.
Scientific Reports. 2015, 5 p.16740.
A Nanotechnology-Based Platform for Extending the Pharmacokinetic and Binding Properties of Anti-Methamphetamine Antibody Fragments.
Nanaware-Kharade N., Thakkar S., Gonzalez III G.A. and Peterson E.C.
Scientific Reports. 2015, 5 p.12060.
Affinity Improvement of a Therapeutic Antibody to Methamphetamine and Amphetamine Through Structure-Based Antibody Engineering.
Thakkar S., Nanaware-Kharade N., Celikel R., Peterson E.C. and Varughese K.I.
Scientific Reports. 2014, 4 p.3673.
Exploring Hydrophobic Binding Surfaces Using Comfa and Flexible Hydrophobic Ligands.
Thakkar S., Sanchez R.I., Bhuveneswaran C. and Compadre C.M.
AIP Conference Proceedings. 2011, June (Vol. 1326, No. 1, pp. 106-111).
Contact information for all lab members:
Cord M. Carter
- Contact Information
- Shraddha Thakkar
- (870) 543-7391
ExpertiseApproachDomainTechnology & DisciplineToxicology