New Delhi, Feb 3 (PTI) – Researchers from the Indian Institute of Technology (IIT) Guwahati, the National University of Singapore, and the University of Michigan have pioneered an innovative multi-stage clinical trial method aimed at transforming personalized medical care by dynamically adapting treatments based on individual patient responses.
This groundbreaking research, published in the prestigious journal Biometrics, was 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 the University of Michigan, USA.
DTRs function as an advanced decision-making framework that adjusts treatments dynamically according to a patient’s evolving condition. For example, if a diabetes patient shows resistance to an initial medication, the system might recommend switching drugs or combining therapies. By incorporating intermediate outcomes, such as blood sugar level changes, DTRs personalize medical interventions rather than relying on a one-size-fits-all approach.
"Multi-stage clinical trials are crucial for developing effective DTRs, and the SMART methodology allows researchers to assess various treatment sequences to find the best fit for each patient," said Palash Ghosh, Assistant Professor, Department of Mathematics, IIT Guwahati.
"Traditional SMART trials may lead to unnecessary treatment failures by assigning equal numbers of patients to all treatment arms, even when some are less effective. Our adaptive randomization technique ensures that more patients receive the most effective treatment while maintaining scientific rigor," Ghosh explained.
By focusing on both short-term and long-term treatment outcomes, the method aims to reduce failures and enhance patient care. Additionally, adaptive trial designs like this could boost patient participation in clinical research, as individuals are more likely to stay engaged when they receive tailored treatments.
This advancement in clinical trial methodology represents a significant step toward making personalized medicine a reality, ultimately leading to more effective and patient-centered healthcare solutions.
This groundbreaking research, published in the prestigious journal Biometrics, was 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 the University of Michigan, USA.
Enhancing Treatment Strategies with Adaptive Trials
The study focuses on Dynamic Treatment Regimes (DTRs), a method designed through Sequential Multiple Assignment Randomized Trials (SMARTs) to optimize treatment plans for patients who respond differently to therapies over time.DTRs function as an advanced decision-making framework that adjusts treatments dynamically according to a patient’s evolving condition. For example, if a diabetes patient shows resistance to an initial medication, the system might recommend switching drugs or combining therapies. By incorporating intermediate outcomes, such as blood sugar level changes, DTRs personalize medical interventions rather than relying on a one-size-fits-all approach.
"Multi-stage clinical trials are crucial for developing effective DTRs, and the SMART methodology allows researchers to assess various treatment sequences to find the best fit for each patient," said Palash Ghosh, Assistant Professor, Department of Mathematics, IIT Guwahati.
A Smarter Approach to Clinical Trials
Unlike traditional SMART trials, which allocate patients equally across treatment arms regardless of effectiveness, the research team has devised an adaptive randomization method. This method dynamically assigns patients to treatment arms based on real-time trial data, shifting allocations in favor of better-performing treatments."Traditional SMART trials may lead to unnecessary treatment failures by assigning equal numbers of patients to all treatment arms, even when some are less effective. Our adaptive randomization technique ensures that more patients receive the most effective treatment while maintaining scientific rigor," Ghosh explained.
By focusing on both short-term and long-term treatment outcomes, the method aims to reduce failures and enhance patient care. Additionally, adaptive trial designs like this could boost patient participation in clinical research, as individuals are more likely to stay engaged when they receive tailored treatments.
Expanding the Impact Beyond Medicine
Beyond clinical treatments, the research has the potential for broader public health applications, such as personalized substance abuse recovery plans and chronic disease management. The research team is now collaborating with Indian medical institutions to conduct SMART trials for mental health treatments using traditional Indian medicine.This advancement in clinical trial methodology represents a significant step toward making personalized medicine a reality, ultimately leading to more effective and patient-centered healthcare solutions.