• Chou Laboratory

    @ University of California, Riverside 

    Using Artificial Intelligence & Machine Learning Approaches to Advance Environmental Health and Toxicology Research

  • MEET OUR TEAM

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    Wei-Chun Chou, PHD

    Principal Investigator

    Assistant Professor of Environmental Health

     

    Department of Environmental Sciences

    College of Natural & Agricultural Sciences

    University of California, Riverside

     

    Office: 210 Science Lab I

    Email: weichun.chou@ucr.edu

    UCR Website: https://profiles.ucr.edu/weichun.chou 

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    Alexa Canchola, PHD

    Assistant Project Scientist

     

    Environmental Toxicology Program

    College of Natural & Agricultural Sciences

    University of California, Riverside

     

    Office: 322 Science Lab I

    Email: alexa.canchola@email.ucr.edu

     

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    Kunpeng Chen, PHD

    Postdoctoral Fellow 

     

    Department of Environmental Sciences

    College of Natural & Agricultural Sciences

    University of California, Riverside

     

    Office: 215 Science Lab I

    Email: kunpeng.chen@email.ucr.edu

     

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    Keyuan Li

    PhD Student

     

    Keyuan will join Chou Lab in 2025. She will develop a Generative Artificial Intelligence to generate a nanoparticle library with the desired tumor delivery efficiency.

     

    Office: 211 Science Lab I

    Email: kli219@ucr.edu 

  • RESEARCH

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    Applying Machine Learning and Artificial Intelligence for Predicting ADME-tox Properties of Environmental Chemicals

     

    Research descriptions:

    ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity (tox) are critical factors in assessing the impact of chemicals on living organisms and the environment. This project aims to leverage advanced computational techniques, specifically the physiologically based pharmacokinetic (PBPK) and quantitative structure-activity relationship (QSAR) model, to predict the ADME-tox properties of environmental chemicals and enhance our understanding and prediction capabilities regarding how environmental chemicals interact with biological systems, facilitating more informed and efficient risk assessment in environmental and health contexts. Additionally, the machine learning and artificial intelligence algorithms were further used to support and assist these computational models in implication in PFAS risk assessment and further developed the AI-assisted PBPK model to estimate the tumor delivery efficiency of cancer nanomedicines.

     

    More detailed information can refer to selected publications:

    • Chou, W. C.; Lin, Z., Development of a gestational and lactational physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) in rats and humans and its implications in the derivation of health-based toxicity values. Environmental Health Perspectives 2021, 129 (3), 037004. https://doi.org/10.1289/EHP7671 
    • Chou, W. C.; Lin, Z., Bayesian evaluation of a physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) to characterize the interspecies uncertainty between mice, rats, monkeys, and humans: Development and performance verification. Environment International 2019, 129, 408-422. https://doi.org/10.1016/j.envint.2019.03.058 
    • Chou, W. C.; Lin, Z., Probabilistic human health risk assessment of perfluorooctane sulfonate (PFOS) by integrating in vitro, in vivo toxicity, and human epidemiological studies using a Bayesian-based dose-response assessment coupled with physiologically based pharmacokinetic (PBPK) modeling approach. Environment International 2020, 137, 105581. https://doi.org/10.1016/j.envint.2020.105581

    Computational Modeling on the Interaction of Nanomedicine with Protein Corona and Its Impact on Tumor Delivery Efficiency

     

    Research descriptions:

    Motivated by the advanced development of artificial intelligence (AI) models, AI-based approaches have found promising applications across diverse domains, ranging from generative language and image generation to drug discovery. Specifically, generative adversarial networks (GAN) in machine learning have successfully been applied in smart drug design and generate novel compounds with the desired functionality, while neural ordinary differential equations (NODEs) efficiently resolve pharmacokinetic profiles through data-driven learning. This project aims to develop an AI-based approach that integrates GAN and NODE methodologies to optimize interactions between nanoparticles (NPs) and protein corona for enhancing tumor delivery efficiency in nanomedicine. Our hypothesis posits that the combined use of GAN and NODEs will enable the generation of virtual protein corona fingerprints corresponding to distinct physicochemical properties of nanoparticles. Neural ODE, considering the interplay between protein corona and NPs properties, will simulate NPs biodistribution, facilitating the identification of ideal nanomedicine candidates with optimal tumor delivery efficiency.

     

    More detailed information can refer to selected publications:

    • Chou, W. C.; Lin, Z., Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling. Toxicological Sciences 2023, 191 (1), 1-14. https://doi.org/10.1093/toxsci/kfac101 
    • Chou, W. C.; Chen, Q.; Yuan, L.; Cheng, Y. H.; He, C.; Monteiro-Riviere,N. A.; Riviere, J. E.; Lin, Z., An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice. Journal of Controlled Release 2023, 361, 53-63. https://doi.org/ 10.1016/j.jconrel.2023.07.040
    • Chen, Q.; Yuan, L.; Chou, W. C.; Cheng, Y. H.; He, C.; Monteiro-Riviere, N. A.; Riviere, J. E.; Lin, Z., Meta-Analysis of Nanoparticle Distribution in Tumors and Major Organs in Tumor-Bearing Mice. ACS nano 2023. https://doi.org/10.1021/acsnano.3c04037
    • Chou, W. C.; Cheng, Y. H.; Riviere, J. E.; Monteiro-Riviere, N.A.; Kreyling, W. G.; Lin, Z., Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats. Particle and Fibre Toxicology 2022, 19 (1), 1-19. https://doi.org/10.1186/s12989-022-00489-4
    • Lin, Z.; Chou, W. C.; Cheng, Y. H.; He, C.; Monteiro-Riviere, N. A.; Riviere, J. E., Predicting nanoparticle delivery to tumors using machine learning and artificial intelligence approaches. International Journal of Nanomedicine 2022,1365-1379. https://doi.org/10.2147/IJN.S344208

    Development of Generative AI in Reconstructing the Structure of Unidentified Chemicals and Predicting their Combined Toxicity in Environmental metrics from Non-Target Analysis

     

    Research descriptions:

    By employing generative AI, the study aims to enhance the accuracy and efficiency of reconstruction of the molecular structures of unknown substances in environmental samples based on the detected signals from non-target analysis. Furthermore, the project will be extended to predicting the combined toxicity of these unidentified chemicals in environmental metrics. This innovative approach promises to improve our understanding of the environmental impact of unknown chemicals, offering valuable computational tools for effective risk assessment and management.

  • PUBLICATIONS

     

    Selected Peer-Reviewed Publications (2019 - 2023)

    [52]. Qin, S.; Zeng, H.; Wu, Q.; Li, Q.; Zeeshan, M.; Ye, L.; Jiang, Y.; Zhang, R.; Jiang, X.; Li, M., Chou, W.C.; et al. An integrative analysis of lipidomics and transcriptomics in various mouse brain regions in response to real-ambient PM2. 5 exposure. Science of The Total Environment 2023, 165112. https://doi.org/10.1016/j.scitotenv.2023.165112          

     

    [51]. Liu, L. S.; Guo, Y.T.; Wu, Q. Z.; Zeeshan, M.; Qin, S. J.; Zeng, H. X.; Lin, L. Z.; Chou, W. C.; Yu, Y.-J.; Dong, G.-H., Per-and polyfluoroalkyl substances in ambient fine particulate matter in the Pearl River Delta, China: Levels, distribution and health implications. Environmental Pollution 2023, 334, 122138. https://doi.org/10.1016/j.envpol.2023.122138           

     

    [50]. Liao, K. W.; Chen, P. C.; Chou, W. C.; Shiue, I.; Huang, H. I.; Chang, W. T.; Huang, P. C., Human biomonitoring reference values, exposure distribution, and characteristics of metals in the general population of Taiwan: Taiwan environmental survey for Toxicants (TESTs), 2013-2016. International Journal of Hygiene and Environmental Health 2023, 252, 114195. https://doi.org/10.1016/j.ijheh.2023.114195 

     

    [49]. Li, Q. Q.; Huang, J.; Cai, D.; Chou, W. C.; Zeeshan, M.; Chu, C.; Zhou, Y.; Lin, L.; Ma, H. M.; Tang, C., Prenatal Exposure to Legacy and Alternative Per-and Polyfluoroalkyl Substances and Neuropsychological Development Trajectories over the First 3 Years of Life. Environmental Science & Technology 2023, 57 (9), 3746-3757. https://doi.org/10.1021/acs.est.2c07807          

     

    [48]. Chou, W. C.; Tell, L. A.; Baynes, R. E.; Davis, J. L.; Cheng, Y. H.; Maunsell, F. P.; Riviere, J. E.; Lin, Z., Development and application of an interactive generic physiologically based pharmacokinetic (igPBPK) model for adult beef cattle and lactating dairy cows to estimate tissue distribution and edible tissue and milk withdrawal intervals for per-and polyfluoroalkyl substances (PFAS). Food and Chemical Toxicology 2023, 181, 114062. https://doi.org/10.1016/j.fct.2023.114062          

     

    [47]. Chou, W. C.; Lin, Z., Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling. Toxicological Sciences 2023, 191 (1), 1-14. https://doi.org/10.1093/toxsci/kfac101        

     

    [46]. Chou, W. C.; Chen, Q.; Yuan, L.; Cheng, Y. H.; He, C.; Monteiro-Riviere, N. A.; Riviere, J. E.; Lin, Z., An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice. Journal of Controlled Release 2023, 361, 53-63. https://doi.org/ 10.1016/j.jconrel.2023.07.040

     

    [45]. Chen, Q.; Yuan, L.; Chou, W. C.; Cheng, Y. H.; He, C.; Monteiro-Riviere, N. A.; Riviere, J. E.; Lin, Z., Meta-Analysis of Nanoparticle Distribution in Tumors and Major Organs in Tumor-Bearing Mice. ACS nano 2023. https://doi.org/10.1021/acsnano.3c04037          

     

    [44]. Cai, D.; Li, Q. Q.; Mohammed, Z.; Chou, W. C.; Huang, J.; Kong, M.; Xie, Y.; Yu, Y.; Hu, G.; Qi, J., Fetal Glucocorticoid Mediates the Association between Prenatal Per-and Polyfluoroalkyl Substance Exposure and Neonatal Growth Index: Evidence from a Birth Cohort Study. Environmental Science & Technology 2023, 57 (31), 11420-11429. https://doi.org/10.1021/acs.est.2c08831          

     

    [43]. Yuan, L.; Chou, W. C.; Richards, E. D.; Tell, L. A.; Baynes, R. E.; Davis, J. L.; Riviere, J. E.; Lin, Z., A web-based interactive physiologically based pharmacokinetic (iPBPK) model for meloxicam in broiler chickens and laying hens. Food and Chemical Toxicology 2022, 168, 113332. https://doi.org/ 10.1016/j.fct.2022.113332          

     

    [42]. Lin, Z.; Chou, W. C.; Cheng, Y. H.; He, C.; Monteiro-Riviere, N. A.; Riviere, J. E., Predicting nanoparticle delivery to tumors using machine learning and artificial intelligence approaches. International Journal of Nanomedicine 2022, 1365-1379. https://doi.org/10.2147/IJN.S344208          

     

    [41]. Lin, Z.; Chou, W. C., Machine learning and artificial intelligence in toxicological sciences. Toxicological Sciences 2022, 189 (1), 7-19. https://doi.org/10.1093/toxsci/kfac075          

     

    [40]. Huang, P. C.; Chen, H. C.; Chou, W. C.; Lin, H. W.; Chang, W. T.; Chang, J. W., Cumulative risk assessment and exposure characteristics of parabens in the general Taiwanese using multiple hazard indices approaches. Science of The Total Environment 2022, 843, 156821. https://doi.org/ 10.1016/j.scitotenv.2022.156821        

     

    [39]. Huang, H. B.; Cheng, P. K.; Siao, C. Y.; Lo, Y. T. C.; Chou, W. C.; Huang, P. C., Mediation effects of thyroid function in the associations between phthalate exposure and lipid metabolism in adults. Environmental Health 2022, 21 (1), 1-15. https://doi.org/10.1186/s12940-022-00873-9          

     

    [38]. Chou, W. C.; Tell, L. A.; Baynes, R. E.; Davis, J. L.; Maunsell, F. P.; Riviere, J. E.; Lin, Z., An interactive generic physiologically based pharmacokinetic (igPBPK) modeling platform to predict drug withdrawal intervals in cattle and swine: A case study on flunixin, florfenicol, and penicillin G. Toxicological Sciences 2022, 188 (2), 180-197. https://doi.org/10.1093/toxsci/kfac056          

     

    [37]. Chou, W. C.; Cheng, Y. H.; Riviere, J. E.; Monteiro-Riviere, N. A.; Kreyling, W. G.; Lin, Z., Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats. Particle and Fibre Toxicology 2022, 19 (1), 1-19. https://doi.org/10.1186/s12989-022-00489-4          

     

    [36]. Chen, Q.; Chou, W. C.; Lin, Z., Integration of toxicogenomics and physiologically based pharmacokinetic modeling in human health risk assessment of perfluorooctane sulfonate. Environmental Science & Technology 2022, 56 (6), 3623-3633. https://doi.org/10.1021/acs.est.1c06479          

     

    [35]. Tsen, C. M.; Liu, J. H.; Yang, D. P.; Chao, H. R.; Chen, J. L.; Chou, W. C.; Ho, Y. C.; Chuang, C. Y., Study on the correlation of bisphenol A exposure, pro-inflammatory gene expression, and C-reactive protein with potential cardiovascular disease symptoms in young adults. Environmental Science and Pollution Research 2021, 28, 32580-32591. https://doi.org/10.1007/s11356-021-12805-0       

     

    [34]. Liao, K. W.; Chang, W. H.; Chou, W. C.; Huang, H. B.; Waits, A.; Chen, P. C.; Huang, P. C., Human biomonitoring reference values and characteristics of Phthalate exposure in the general population of Taiwan: Taiwan Environmental Survey for Toxicants 2013-2016. International Journal of Hygiene and Environmental Health 2021, 235, 113769. https://doi.org/10.1016/j.ijheh.2021.113769        

     

    [33]. Chou, W. C.; Lin, Z., Development of a gestational and lactational physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) in rats and humans and its implications in the derivation of health-based toxicity values. Environmental Health Perspectives 2021, 129 (3), 037004. https://doi.org/10.1289/EHP7671       

     

    [32]. Chao, J. H.; Chuang, C. Y.; Chou, W. C.; Kuo, C. L.; Chang, F. C.; Chiang, A. C., Optimization of alkali fusion process for determination of I-129 in solidified radwastes by neutron activation. Applied Radiation and Isotopes 2021, 176, 109762. https://doi.org/10.1016/j.apradiso.2021.109762          

     

    [31]. Chang, W. H.; Chou, W. C.; Waits, A.; Liao, K. W.; Kuo, P. L.; Huang, P. C., Cumulative risk assessment of phthalates exposure for recurrent pregnancy loss in reproductive-aged women population using multiple hazard indices approaches. Environment International 2021, 154, 106657. https://doi.org/10.1016/j.envint.2021.106657            

     

    [30]. Xu, N.; Li, M.; Chou, W. C.; Lin, Z., A physiologically based pharmacokinetic model of doxycycline for predicting tissue residues and withdrawal intervals in grass carp (Ctenopharyngodon idella). Food and Chemical Toxicology 2020, 137, 111127. https://doi.org/10.1016/j.fct.2020.111127            

     

    [29]. Ling, M. P.; Hsiao, H. A.; Chen, S. C.; Chen, W. Y.; Chou, W. C.; Lin, Y. J.; You, S. H.; Yang, Y. F.; Lin, H. C.; Chen, C. Y., Assessing dietary exposure risk to neonicotinoid residues among preschool children in regions of Taiwan. Environmental Science and Pollution Research 2020, 27, 12112-12121. https://doi.org/10.1007/s11356-020-07832-2          

     

    [28]. Chou, W. C.; Lin, Z., Probabilistic human health risk assessment of perfluorooctane sulfonate (PFOS) by integrating in vitro, in vivo toxicity, and human epidemiological studies using a Bayesian-based dose-response assessment coupled with physiologically based pharmacokinetic (PBPK) modeling approach. Environment International 2020, 137, 105581. https://doi.org/10.1016/j.envint.2020.105581         

     

    [27]. Zhu, J.; Hsu, C. Y.; Chou, W. C.; Chen, M. J.; Chen, J. L.; Yang, T. T.; Wu, Y. S.; Chen, Y. C., PM2. 5-and PM10-bound polycyclic aromatic hydrocarbons (PAHs) in the residential area near coal-fired power and steelmaking plants of Taichung City, Taiwan: In vitro-based health risk and source identification. Science of the Total Environment 2019, 670, 439-447. https://doi.org/10.1016/j.scitotenv.2019.03.198          

     

    [26]. Lee, C. H.; Hung, P. F.; Lu, S. C.; Chung, H. L.; Chiang, S. L.; Wu, C. T.; Chou, W. C.; Sun, C. Y., MCP-1/MCPIP-1 signaling modulates the effects of IL-1β in renal cell carcinoma through ER stress-mediated apoptosis. International Journal of Molecular Sciences 2019, 20 (23), 6101. https://doi.org/ 10.3390/ijms20236101          

     

    [25]. Chou, W.C.; Tsai, W. R.; Chang, H. H.; Lu, S. Y.; Lin, K. F.; Lin, P., Prioritization of pesticides in crops with a semi-quantitative risk ranking method for Taiwan postmarket monitoring program. Journal of Food and Drug Analysis 2019, 27 (1), 347-354. https://doi.org/10.1016/j.jfda.2018.06.009          

     

    [24]. Chou, W. C.; Lin, Z., Bayesian evaluation of a physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) to characterize the interspecies uncertainty between mice, rats, monkeys, and humans: Development and performance verification. Environment International 2019, 129, 408-422. https://doi.org/10.1016/j.envint.2019.03.058     

     

    Click to see the full publication list via Google Scholar Profiles   

  • NEWS

    • [10/30/2024] Dr. Chou has been appointed to the Environmental Protection Agency (EPA) Scientific Advisory Board (SAB) to provide independent advice on the Integrated Risk Information System (IRIS) Toxicological Review of Chlorofom.
    • [06/2024] Dr. Chou join the Review Panel of NIH Small Business: Computational, Modeling, and BioData Management. Please refer to: the List of Reviewers.
    • [05/2024] Dr. Chou accepted the offer from the Journal, Frontiers in Public Health as Associate Editor.
    • [05/2024] The Chou Lab received an NIH R03 award for "Computational Modeling on the Interaction of Nanomedicine with Protein Corona and Its Impact on Tumor Delivery Efficiency". Thank you to the lab team, mentors, collaborators, and colleagues who helped along the way. Please refer to: NIH RePORTER
    • [3/13/2024] Dr. Chou received the Best Paper Award of the Year 2023 presented by the Biological Modeling Specialty Section during the Society of Toxicology annual conference in 2024. 
    • [2/14/2024] Dr. Chou gave a seminar presentation entitled “Leveraging Computational Modeling and Artificial Intelligence to Advance Environmental Health and Toxicology Research” invited by the Environmental Toxicology Graduate Program at the University of California, Riverside.
    • [1/11/2024] Dr. Chou gave a webinar presentation entitled “Development of artificial intelligence (AI)-assisted physiologically based pharmacokinetic (PBPK) and its applications in nanomedicine” invited by the College of Pharmacy at the University of Florida.
    • [1/5/2024] Dr. Chou has been appointed to the Environmental Protection Agency (EPA) Scientific Advisory Board (SAB) to provide independent advice on the Integrated Risk Information System (IRIS) Toxicological Review of Inorganic Arsenic. Please refer to the link: EPA SAB Inorganic Arsenic Panel
    • [01/01/2024] Dr. Chou officially joined the Department of Environmental Sciences in the College of Natural & Agricultural Sciences at University of California, Riverside (UCR).
    • [12/13/2023] Dr. Chou gave a webinar presentation entitled “Integrating Machine Learning and Quantitative Structure Activity Relationships (QSAR) Modeling Approaches to Develop Artificial Intelligence (AI)-Assisted Interactive Physiologically Based Pharmacokinetic (iPBPK) Modeling Web Dashboard” for Triple-Sponsored Webinar by Risk Assessment Specialty Section (RASS), Biological Modeling Specialty Section (BMSS) and the American Association of Chinese in Toxicology (AACT).
    • [09/23/2023] Dr Chou’s manuscript entitled “Development and Application of an Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Model for Adult Beef Cattle and Lactating Dairy Cows to Estimate Tissue Distribution and Edible Tissue and Milk Withdrawal Intervals for Per- and Polyfluoroalkyl Substances (PFAS)” has been accepted by Food and Chemical Toxicology. Link to the publication: https://doi.org/10.1016/j.fct.2023.114062
    • [07/24/2023] Dr Chou’s manuscript entitled “An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice” has been accepted by Journal of Controlled Release. Link to the publication: https://doi.org/10.1016/j.jconrel.2023.07.040
    • [04/26/2023] Dr. Chou gave a webinar presentation entitled “Machine learning and artificial intelligence in toxicology and physiologically based pharmacokinetic modeling in supporting chemical and nanoparticle toxicity and dosimetry assessment” for ExxonMobil Biomedical Sciences (EMBSI).
    • [04/05/2023] Dr. Chou gives a guest lecture entitled “An introduction to computational modeling and artificial intelligence in exposure science and its application in Environmental Chemicals, animal drugs, and nanomedicine” for the course “PHC 6702: Environmental Monitoring and Exposure Assessment” at UF. (04/05/2023)
    • [03/23/2023] Dr. Chou was elected as a Councilor of the Biological Modeling Specialty Section of Society of Toxicology.
    • [03/23/2023] Best Publication Award of the Year 2022 presented by Nanoscience and Advanced Materials Specialty Section; Recipients: Dr. Chou and Dr. Zhoumeng Lin; Title of the publication “Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats”. Link to the publication: https://doi.org/10.1186/s12989-022-00489-4

     

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  • TEACHING

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    2024 Spring

    Course Title: Risk Assessment

    • Instructors: Wei-Chun Chou
    • Course number: ENTX 154
    • Location: University of California, Riverside

    2023 Fall

    Course Title: Physiologically Based Pharmacokinetic Modeling in Toxicology and Risk Assessment

    • Instructors: Zhoumeng Lin and Wei-Chun Chou
    • Course number: PHC 7738C
    • Location: University of Florida

    2023 Spring

    Course Title: Artificial Intelligence in Environmental and Global Health

    • Instructors: Zhoumeng Lin and Wei-Chun Chou
    • Course number: PHC 6937
    • Location: University of Florida

    2022 Fall

    Course Title: Physiologically Based Pharmacokinetic Modeling in Toxicology and Risk Assessment

    • Instructors: Zhoumeng Lin and Wei-Chun Chou
    • Course number: PHC 7738C
    • Location: University of Florida 
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