Publication Topic

Covington T, Borghoff SJ, Sims JL, Kamel A, Markey K, Wetmore BA, Lynn SG. Use of an in silico mass balance model to predict chemical suitability for screening chemicals in a high-throughput assay platform for potential endocrine activity. Poster 3, Poster Session II, American Society for Cellular and Computational Toxicology (ASCCT) 15^th Annual Meeting, Durham, NC, October 28, 2026

Patlewicz G, Mihalchik AL. Refinement of the threshold of toxicological concern (TTC): A computational framework for cross-scheme comparison of TTC values. Poster Session 1, Poster 24, American Society for Cellular and Computational Toxicology (ASCCT) 15^th Annual Meeting, Durham, NC, October 27, 2026.

Patlewicz GY, Mihalchik AL. 2026. Revisiting the Threshold of Toxicological Concern: A computational framework for structural classification, cross-scheme comparison and opportunities for refinement. Comput Toxicol 39(Sept):100443; doi: 10.1016/j.comtox.2026.100443.

Patlewicz GY, Mihalchik AL, East A, Borghoff SJ, Thompson CM. 2026. Investigating the feasibility of deriving new environmentally relevant thresholds of Toxicological Concern (TTCs) from estimated chronic human equivalent benchmark dose (eBMD_HED) values. Comput Toxicol 38(June):100417; doi: 10.1016/j.comtox.2026.100417.

Shobair M, Allen D, Ballone I, Brull M, Burbank M, Choksi N, Fitch S, Irizar A, et al. A machine-learning approach for the development of a knowledgebase to identify systemic toxicity mechanistic targets and evaluate biological space coverage. Abstract 5161, Society of Toxicology 65^th Annual Meeting, San Diego, CA, March 2026.

Beggs AH, Haselkorn T, Solomon F, Rumantir R, Bylsma LC, Vue S, Mitchell M, Kelsh M, Sacks NC, Graham RJ. Epidemiology of x-linked myotubular myopathy (XLMTM) in the United States using a machine learning model. Abstract/Poster 106S, Muscular Dystrophy Association (MDA) Clinical and Scientific Conference, Orlando, FL, March 2026.

Snyder K, Greene N, De Nieu M, Anger L, Shah F. Developing predictive models to facilitate interpretation of toxicology study results. Symposium co-chair, Symposium S04, American College of Toxicology (ACT) 46^th Annual Meeting, Phoenix, AZ, November 2025.

Seal S, Trapotsi M, Subramanian V, Spjuth O, Greene N, Bender A. 2025. PKSmart: An open-source computational model to predict in vivo pharmacokinetics of small molecules. J Cheminform 17(1):147; doi: 10.1186/s13321-025-01066-5. PMID: 41013647.

Hanser T, Ahlberg E, Amberg A, Anger LT, Barber C, Brennan RJ, Brigo A,…, Greene N, et al. 2025. Data-driven federated learning in drug discovery with knowledge distillation. Nat Mach Intell 7(Mar):423–436; doi: 10.1038/s42256-025-00991-2.

Blanchette AD, Donnell MT, Covell LT, Madl AK. A machine learning-based framework for predicting carcinogenic potencies for nitrosamine compounds. Abstract 4040, Society of Toxicology 64^th Annual Meeting, Orlando, FL, March 2025.

Seal S, Trapotsi MA, Spjuth O, Singh S, Carreras-Puigvert J, Greene N, Bender A, Carpenter AE. 2025. Cell painting: A decade of discovery and innovation in cellular imaging. Nat Meth 22(2):254-268; doi: 10.1038/s41592-024-02528-8. PMID: 39639168.

Hagan B, Patlewicz G, Shah I. Metabolic similarity in read-across prediction: A case study using graph convolutional networks to predict genotoxicity outcomes from metabolic networks. Abstract 62, American Society for Cellular and Computation Toxicology 13th Annual Meeting, Research Triangle Park, NC, October 2024.

Leary AJ, Patlewicz G, Shah I. An exploration of the use of hybrid fingerprints in generalized read-across and their impact on predictive performance for selected in vivo toxicity outcomes. Abstract 42, American Society for Cellular and Computation Toxicology 13th Annual Meeting, Research Triangle Park, NC, October 2024.

Wright PSR, Briggs KA, Thomas R, Smith GF, Maglennon G, Mikulskis P, Chapman M, Greene N, et al. 2023. Statistical analysis of preclinical interspecies concordance of histopathological findings in the eTOX database. Regul Toxicol Pharmacol 138(Feb):105308; doi: 10.1016/j.yrtph.2022.105308. PMID: 36481279.

Zwickl CM, Graham JC, Holly RA, Bassan A, Ahlberg E, Amberg A, Anger LT,.., Patlewicz G, et al. 2022. Principles and procedures for assessment of acute toxicity incorporating in silico methods. Comput Toxicol 24(Nov):100237; doi: 10.1016/j.comtox.2022.100237. PMID: 36818760.

Patlewicz G, Nelms MN, Rua D. 2022. Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices. Comput Toxicol 24(Nov):100246; doi: 10.1016/j.comtox.2022.100246. PMID: 36405647.

Nicolas CI, Linakis MW, Minto MS, Mansouri K, Clewell RA, Yoon M, Wambaugh JF, Patlewicz G, et al. 2022. Estimating provisional margins of exposure for data poor chemicals using high throughput computational methods. Front Pharmacol 13(Oct 7):980747; doi: 10.3389/fphar.2022.980747. PMID: 36278238.

Roell K, Koval LE, Boyles R, Patlewicz G, Ring C, Rider CV, Ward-Caviness C, Reif D, et al. 2022. Development of the intelligence and machine learning toolkit (TAME) for introductory data science, chemical-biological analyses, predictive modelling, and database mining for environmental health research. Front Toxicol 4(Jun 22):893924; doi: 10.3389/ftox.2022.893924. PMID: 35812168.

Fender CL, Good S, Jaramillo-Garcia M. Exploring the impacts of evaporation on chemical trends in a regional river and irrigation canal, using nontarget LCMS approaches. Poster presentation at Pacific Northwest Water Symposium, Corvallis, OR, 2022.

Fender CL, Good S, Jaramillo-Garcia M. Using nontarget LCMS and in silico toxicological approaches for the detection and prioritization of contaminant mixtures is a regional irrigation canal. Poster presentation at SETAC Nontarget Special Topics Session, Durham, NC, 2022.