Dr. Shuvo was recently awarded a PVAMU RISE Undergraduate Award, “Toward Trustworthy and End-to-End AI for Next-Generation Computational Therapeutics”, to develop a trustworthy, explainable, and secure end-to-end AI framework that integrates multiple computational therapeutics tasks—from protein function prediction to drug response prediction—to accelerate and improve drug discovery. This is a 1-year grant to support an undergraduate student, up to $7,200.


Project Title: Toward Trustworthy and End-to-End AI for Next-Generation Computational Therapeutics

Principal Investigator: Md Hossain Shuvo, Ph.D.

Project Description:

Drug discovery is a long and expensive process, with many potential drug candidates failing before reaching clinical use. Artificial intelligence can help reduce this burden by identifying and prioritizing promising drug candidates earlier, but most existing AI tools focus on individual tasks and do not work together as a connected system. This project will develop a modular, end-to-end AI framework that connects important computational therapeutics tasks, including protein function prediction, drug–target affinity prediction, toxicity prediction, and drug response prediction. The project will also incorporate self-assessment and explainability so that the system can provide confidence estimates, identify important features behind its predictions, and better understand when and why models fail. In addition, the project will examine the effects of low-quality and potentially adversarial inputs and develop a secure deployment prototype with basic safeguards such as input validation, access control, secure communication, and activity logging. The expected outcome is a working prototype that demonstrates how multiple AI models can be connected into a more reliable, transparent, and secure computational therapeutics workflow. The results will provide a foundation for future research on trustworthy AI for biomedical applications and support the development of larger NIH, NSF, and DoD proposals.

Sponsor: R&I Division at Prairie View A&M University Funding Amount: $7,200 Project Period: FY 2026–2027