NEW DELHI, Feb 3: Researchers at the Indian Institute of Technology (IIT) Guwahati, National University of Singapore and University of Michigan have developed an innovative multi-stage clinical trial method aimed at revolutionising personalised medical care.
According to officials, the research adapts treatment plans in real-time based on each patient’s unique responses during trials, enabling highly tailored and effective healthcare solutions.
The findings of the research have been published in the esteemed journal Biometrics in a paper co authored by Palash Ghosh and Rik Ghosh from IIT Guwahati, Bibhas Chakraborty from Duke-NUS Medical School, National University of Singapore, along with Inbal Nahum-Shani and Megan E Patrick from University of Michigan, USA.
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The research 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, they said.
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.
“Multi-stage clinical trials are essential for developing effective DTRs, and SMART methodology enables researchers to test various treatment sequences to find the best fit for each patient. Unlike traditional trials, SMART involves multiple stages of treatment, where patients are reassigned based on their responses to earlier interventions,” said Palash Ghosh, assistant professor, Department of Mathematics, IIT Guwahati.
“Traditional SMART trials assign patients to treatment arms in equal numbers, even when some treatments prove less effective, based on interim data. This often leads to unnecessary treatment failures. We 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 favor of a better-performing treatment sequence at that point of time of the trial,” he added.
Ghosh explained the innovation will ensure that more patients receive effective treatments while maintaining scientific rigor.
“By focusing on both short-term and long-term outcomes, the method will improve the entire treatment process, reducing failures and enhancing patient care. 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,” he said.
The research team is now collaborating with the Indian medical institutions to conduct SMART trials for the effective management of mental health issues using traditional Indian medicines. (PTI)
