At the recent Society of Toxicology 63rd Annual Meeting and ToxExpo March 10-14 in Salt Lake City, members of the University of Florida College of Public Health and Health Professions department of environmental and global health delivered several presentations, provided services and received multiple awards.
Zhoumeng Lin, Ph.D., D.A.B.T., C.P.H., an associate professor in the department of environmental and global health and a member of the Center for Environmental and Human Toxicology and Center for Pharmacometrics and Systems Pharmacology, focuses on the development and application of computational technologies to address research questions related to nanomedicine, animal-derived food safety assessment, and environmental chemical risk assessment. His team’s long-term goal is to develop AI-assisted computational approaches to support decision-making in human, animal, and environmental health.
Members of the Lin Lab provided the following services at the meeting:
Lin served as a co-chair of a workshop session on “Use of PBPK and Novel Pharmacokinetic Approaches for the Quantitative Prediction of Tissue Residue and Withdrawal Times for Human Food Safety Assessment.” Lin is now in his third year in the presidential chain of the Biological Modeling Specialty Section and is serving as the president for the current term from May 2023 to April 2024.
Chi-Yun Chen, postdoctoral associate, was elected as the postdoctoral representative of the Risk Assessment Specialty Section of Society of Toxicology.
Qiran Chen was elected as the postdoctoral representative of the American Association of Chinese in Toxicology (AACT) Specialty Interest Group of Society of Toxicology.
Xue Wu, doctoral student, was elected as the graduate student representative of the Biological Modeling Specialty Section of Society of Toxicology.
Members of the Lin Lab received the following awards:
- Best Paper of the Year Award 2023 presented by the Biological Modeling Specialty Section
- Lead author: Wei-Chun Chou, former UF research assistant professor and now an assistant professor of environmental health at University of California Riverside
- Corresponding author: Zhoumeng Lin
- Title: “An artificial intelligence-assisted physiologically based pharmacokinetic model to predict nanoparticle delivery to tumors in mice.”
- Perry J. Gehring Biological Modeling Endowment Award presented by the Biological Modeling Specialty Section
- Recipient: Chi-Yun Chen
- AACT and InnoStar Best Abstract Award (2nd Place) presented by the AACT Specialty Interest Group
- Recipient: Qiran Chen, Ph.D., postdoctoral fellow
- Title: “A physiologically based pharmacokinetic model of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and perfluorodecanoic acid (PFDA) in adult zebrafish.”
- Top 10 Best Abstract Award presented by the Risk Assessment Specialty Section
- Recipient: Chi-Yun Chen
- Title: “A physiologically based toxicokinetic model for assessing oral exposure to microplastics and nanoplastics in mice and its implications for human dietary intake.”
- Top 10 Best Abstract Awards presented by the Computational Toxicology Specialty Section
- Recipients: Chi-Yun Chen, Qiran Chen, Pei-Yu Wu
- Title: “A physiologically based toxicokinetic model for assessing oral exposure to microplastics and nanoplastics in mice and its implications for human dietary intake.”
- Title: “A physiologically based pharmacokinetic model of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and perfluorodecanoic acid (PFDA) in adult zebrafish.”
- Title: “A Physiologically-Based Pharmacokinetic (PBPK) Model of Perfluorobutane Sulfonate (PFBS) in Rodents with a Bayesian Approach.”
In addition, Kun Mi, postdoctoral associate, presented a poster entitled: “Applying machine learning and artificial intelligence approaches to predict tissue distribution and tumor delivery of nanoparticles in mice following intravenous injection.” Wei-Chun Chou presented a poster entitled “Development of a Multi-Organ Toxicity Predictive Model Using Multi-Task Learning in Deep Neural Network.” Xue Wu presented “Predicting the Plasma Half-Life of Medications Administered to Dogs: An Artificial Intelligence Based Quantitative Structure-Activity Relationship (AI-QSAR) Model” for the “Machine Learning in Toxicology” platform session. Lin gave a platform presentation entitled “Development and applications of PBPK models to predict tissue residues and withdrawal times of drugs in food-producing animals to support food safety assessment.”