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IIT-G develops multi-stage clinical trial method for personalised medical care

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Guwahati, Feb 3: Researchers at the Indian Institute of Technology-Guwahati (IIT-G) here, in collaboration with leading institutions worldwide, have developed an innovative multi-stage clinical trial method aimed at revolutionising personalised medical care.

The cutting-edge approach adapts treatment plans in real-time based on each patient’s unique responses during trials, enabling highly tailored and effective healthcare solutions.

The research, conducted in partnership with Duke-NUS Medical School, the National University of Singapore, and the University of Michigan, USA, focuses on Dynamic Treatment Regimes (DTRs) designed through Sequential Multiple Assignment Randomised Trials (SMARTs).

“Together, these frameworks tackle the critical challenge of optimising treatment strategies, a sequence of treatments, for patients with varying responses to therapies over time,” a statement issued by IIT-G here on Monday said.

Notably, DTRs are advanced decision rules that adapt treatments dynamically as a patient’s condition evolves. For example, if a diabetes patient does not respond well to an initial medication, the DTR might recommend switching drugs or combining therapies.

By incorporating intermediate outcomes, such as changes in blood sugar levels, DTRs move beyond the one-size-fits-all model, tailoring care to individual progress and needs.

Palash Ghosh, assistant professor, department of mathematics, IIT-Guwahati, and his team have developed an adaptive randomisation method that dynamically assigns patients to treatment arms based on real-time trial data by optimally changing the patient allocation ratios in favour of a better-performing treatment sequence at that point of time of the trial.

Speaking about the research Ghosh said, “Adaptive designs like this would encourage more patient participation in clinical trials like SMART. When patients see they are receiving treatments tailored to their needs, they are more likely to stay engaged. This approach also has vast potential for public health interventions, such as tailoring substance abuse recovery plans to individual needs as well as in other chronic diseases.”

The findings of the research have been published in the journal, Biometrics, in a paper co-authored by Ghosh, along with his research scholar, Rik Ghosh from IIT Guwahati; Bibhas Chakraborty from Duke-NUS Medical School, National University of Singapore; Dr. Inbal Nahum-Shani and Megan E. Patrick, from University of Michigan.

The innovation ensures that more patients receive effective treatments while maintaining scientific rigour. By focusing on both short-term and long-term outcomes, the method improves the entire treatment process, reducing failures and enhancing patient care.

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