Kean University Researcher Helps Develop AI Platform to Make Drug Discovery Safer
the staff of the Ridgewood blog
Union NJ, Kidney toxicity is one of the leading reasons promising new pharmaceuticals fail during development. Traditional screening requires expensive, years-long laboratory and animal studies before clinical trials can even begin.
Now, Supratik Kar, Ph.D., an Assistant Professor at Kean University, in collaboration with researchers from the University of Salerno in Italy, has co-developed a breakthrough solution: KidneyTox_v1.0 (KidneyTox).
Published in Scientific Reports, this open-source, web-based platform utilizes artificial intelligence to predict whether small molecules are likely to cause kidney damage—saving pharmaceutical researchers years of effort and millions in resources.
How KidneyTox Is Transforming Pharmaceutical Research
Unlike black-box AI algorithms, KidneyTox provides transparent, explainable insights into chemical toxicity:
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Explainable AI (XAI): Rather than offering a simple binary result, KidneyTox highlights the specific chemical structures responsible for predicted toxicity, allowing scientists to redesign compounds early in development.
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Proven Data Foundation: Built on a curated dataset of 565 FDA-approved small molecules—including roughly 300 drugs with known renal toxicity alongside safe control compounds.
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Open-Access Resource: Available at no cost to researchers, students, and institutions worldwide to evaluate chemical compounds prior to costly experimental trials.
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Built-in Limitations Alert: The platform explicitly alerts users when a compound falls outside the model’s trained chemical space, preventing over-reliance on predictions.
Looking Ahead: Multi-Organ AI Screening
Building on his prior research with AI-driven liver toxicity tools, Dr. Kar aims to expand this framework into a comprehensive, one-click screening tool capable of evaluating multiple organ toxicities simultaneously.
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