Shubha Das
Jadavpur University
Research areas: Pharmacology, Toxicology and Pharmaceutics · Drug Discovery · Computational Drug Discovery Methods · Environmental Toxicology and Ecotoxicology · Machine Learning in Materials Science
0009-0004-1596-8900
About
Shubha Das has completed his Master’s degree in Pharmaceutical Chemistry from Jadavpur University. He qualified the GPAT and NIPER examinations in 2022 and has gained over three years of research experience in the field. His research interests include QSAR, molecular modeling, docking studies, toxicity modeling, and ecotoxicology. He has authored 16 publications in reputed international journals, including one featured on a cover page. His work has received 92 citations with an h-index of 5, reflecting the growing impact of his contributions in computational and predictive toxicology.
Employment
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Jadavpur University Research Scholar (PhD)2024 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (17)
- HumanToxPredict: An interpretable data-driven framework for human oral TDLo prediction and toxicity assessment of pharmaceuticals and bioactive compounds Save
- A round-robin exercise for the precise prediction of aqueous solubility of organic chemicals using chemometric, machine learning, and stacking ensemble of deep learning models Save
- An alternative to in vivo/in vitro toxicity testing: Consensus-based prediction for toxicity assessment and prioritisation of diverse chemicals in Japanese eel to safeguard aquatic and public health Save
- Chemometric modelling for eco-toxicological risk assessment of diverse chemicals towards mammalian species Save
- Computational modeling of avian toxicities: Risk assessment of chemicals Save
- From structure to strategy: chemometric modeling for the prediction of terminal half-life of pharmaceuticals and its role in future therapeutics Save
- Predictive q-RASAR modeling of intrinsic toxicity of pharmaceuticals and bioactive compounds in cats Save
- QSAR meets ecology: Predictive framework for assessing pesticide toxicity against mayfly using consensus modelling Save
- q-RASAR modeling of antibiotics-microplastics mixtures: Towards predictive aquatic toxicology and resistance risk assessment Save
- Bridging chemistry and toxicology: Chemometric-driven prediction and prioritization of various drugs addressing hazardous effects for human safety Save
- First report on q-RASTR modelling of hazardous dose (HD5) for acute toxicity of pesticides: an efficient and reliable approach towards safeguarding the sensitive avian species Save
- Intelligent consensus prediction for addressing ecotoxicological effects of diverse pesticides on California quail Save
- Revolutionizing toxicity predictions of diverse chemicals to protect human health: Comparative QSAR and q-RASAR modeling Save
- Risk assessment of industrial chemicals towards salmon species amalgamating QSAR, q-RASAR, and ARKA framework Save
- Chemometrics-driven prediction and prioritization of diverse pesticides on chickens for addressing hazardous effects on public health Save
- Comprehensive Ecotoxicological Assessment of Pesticides on Multiple Avian Species: Employing Quantitative Structure-Toxicity Relationship (QSTR) Modeling and Read-Across Save
- Quantitative read-across structure–property relationship (q-RASPR): a novel approach to estimate the bioaccumulative potential for diverse classes of industrial chemicals in aquatic organisms Save