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  1. NCTR Publications

NCTR Research Highlights

Periodic report on research activities and special events at NCTR

2023 Research Highlights

January 31, 2023

Retired NCTR Research Chemist Presented Distinguished Scientist Award by The Toxicology Forum

Daniel R. Doerge, Ph.D., retired research chemist from FDA’s National Center for Toxicological Research (NCTR), was presented the Philippe Shubik Distinguished Scientist Award at the Toxicology Forum Winter Meeting held January 24, 2023. He was nominated for the award by NCTR leadership for his role in the development of toxicology concepts that significantly impacted the field of regulatory science research.

The Philippe Shubik Distinguished Scientist Award is named in honor of The Toxicology Forum's founding president. According to the Tox Forum website, this annual award recognizes an individual who has led a long and productive career in toxicology and has made significant and noteworthy contributions to the field, including all aspects of traditional and regulatory toxicology. 

Dr. Doerge’s areas of research specialization included chemical and biochemical mechanisms of toxicity, thyroid toxicology, toxicology of soy isoflavones, acrylamide, bisphenol A (BPA), and inorganic arsenic. Dr. Doerge played a leading role in the development of novel highly sensitive and specific mass spectral-based analytical methodologies to quantify DNA damage induced by chemical carcinogens. Dr. Doerge was also responsible for the design and implementation of several comprehensive pharmacokinetic assays to address regulatory data gaps for the FDA, including on BPA, an industrial chemical found in some plastics. This work enabled the development of a physiologically-based pharmacokinetic model for BPA, which was the object of the prestigious FDA Chief Scientist Publication Award in 2017. Dr. Doerge served on chemical risk-assessment advisory committees for the European Food Safety Authority, World Health Organization, and U.S. Environmental Protection Agency. He also served as editor-in-chief for Archives of Environmental Contamination and Toxicology. His research publications are highly cited—one of the top 10 most-cited FDA scientists—based on statistics available through Google Scholar.

During his 50-year career, Dr. Doerge mentored and developed future generations of toxicologists, contributing positively to the research community. He provided leadership, guidance, and training to countless research fellows and junior staff members—mentoring postdoctoral fellows, supervising researchers, and informally advising many NCTR colleagues.

Dr. Doerge retired from NCTR in December 2020 after a long, distinguished career developing and adapting important toxicology concepts while also serving as a leader of and role model for future scientists. 
 

January 18, 2023

NCTR Artificial Intelligence Initiatives Selected as Winners in the 2022 EMGS Bioinformatics Challenge

Two NCTR scientists—Drs. Ting Li and Xi Chen—have been selected the first- and second-place winners, respectively, for the annual 2022 Environmental Mutagenesis and Genomics Society’s (EMGS) Bioinformatics Challenge! This EMGS Challenge encourages participants to develop novel tools and approaches that use publicly available data to identify signatures of genotoxic hazards or provide insight into their mechanisms of action.

Drs. Li and Chen are working on two of the NCTR-developed AI4TOX four initiatives, SafetAI and AnimalGAN. AI4TOX is an FDA artificial intelligence (AI) program for toxicology under the leadership of Dr. Weida Tong, Director of NCTR’s Division of Bioinformatics and Biostatistics (DBB). The program aims to apply the most advanced AI methods to develop new tools to support FDA regulatory science and strengthen the safety review of FDA-regulated products. 

Dr. Li presented her work on drug-induced liver injury (DILI) “DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation” for the EMGS Challenge. Developed by Dr. Li, DeepDILI is an AI drug-safety model within the SafetAI suite that uses a deep learning-powered prediction model designed to use chemical structure information to identify drugs with the potential to cause DILI in humans. The SafetAI initiative aims to develop AI models for toxicological endpoints that are critical to assessing drug safety and may add value to the review of drug candidates prior to human testing.

Dr. Chen presented “AnimalGAN: A Generative AI Alternative to Animal Clinical Pathology Testing” for the EMGS Challenge. Developed by Dr. Chen, AnimalGAN is an AI-based suite that generates specific animal-study datasets for new and untested chemicals by learning from legacy animal-study data. The successful implementation of this AI-based suite is the first example of a generative adversarial network (GAN)-specific application’s use in a virtual animal model. 

Watch the final round of the Bioinformatics Challenge and learn about the other two AI4TOX initiatives, BERTox and PathologAI. For additional information, please contact Dr. Weida Tong.

 

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