Swapnil Chavan

Employment

• RISE Research Institutes of Sweden AB Project Leader & Data Scientist (Computational Toxicology)
  2020 - Present
• Örebro Universitet Postdoc
  2018 - 2019
• US Environmental Protection Agency Postdoc
  2016 - 2018

Education

• Linnaeus University PhD
  2011 - 2016
• National Institute of Pharmaceutical Education and Research MS
  2008 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (8)

• An Agentic AI Framework for Hepatotoxicity Prediction: Integrating Multi-Descriptor Deep Learning Ensembles with Reasoning-Based Escalation
  2026 DOI: 10.26434/chemrxiv.15006192/v1
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• Metabolite-Gen: Joint Prediction of Sites of Metabolism, Reaction Class, and Metabolite Structures Using Graph Neural Networks
  2026 DOI: 10.26434/chemrxiv.15002775/v1
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• Moving Towards Making (Quantitative) Structure-Activity Relationships ((Q)SARs) for Toxicity-Related Endpoints Findable, Accessible, Interoperable and Reusable (FAIR)
  Altex 2025 DOI: 10.14573/altex.2411161
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• Toward safer and more sustainable by design biocatalytic amide-bond coupling
  Green Chemistry 2024 DOI: 10.1039/d4gc03665d
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• A safer and more sustainable by design perspective in biocatalytic amide-bond coupling of in silico controlled chemical space
  Chemrxiv 2023 DOI: 10.26434/chemrxiv-2023-x8f25
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• In Silico Prediction of Eye Irritation Using Hansen Solubility Parameters and Predicted pKa Values
  Alternatives to Laboratory Animals 2023 DOI: 10.1177/02611929231175676
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• hERG-toxicity prediction using traditional machine learning and advanced deep learning techniques
  Current Research in Toxicology 2023 DOI: 10.1016/j.crtox.2023.100121
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• Predicting Chemical-Induced Liver Toxicity Using High-Content Imaging Phenotypes and Chemical Descriptors: A Random Forest Approach
  Chemical Research in Toxicology 2020 DOI: 10.1021/acs.chemrestox.9b00459
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