What if clinical trials could be conducted faster, required fewer patients, cost less and led to improved health? ITOM Professor Vishal Ahuja and his co-author have developed a breakthrough approach long overdue in healthcare. “Our approach is good for patients, companies and the public health at large, bringing needed drugs to market sooner,” according to Ahuja.

Clinical trials, particularly phase-3 trials, have been cited as major contributors to the rising costs of taking a new drug to market, estimated at $300 million to $600 million. Traditionally, clinical trials have followed a fixed (non adaptive) design that randomly assigns patients to treatments in a constant proportion throughout the trial. Because these designs often result in lengthy trials and poor outcomes, pharmaceutical firms and regulators seek more efficient designs.

The bulk of work in adaptive design development has been in sequential or “one-person-at-a-time” trials. But most trials have multiple patients that need to be randomly assigned at the same time. Ahuja and his co-author proposed a design that allows for this randomization of several patients at the same time. However, developing a protocol for implementing adaptive designs (which the FDA requires before a trial can begin) means that one must consider all possible scenarios. Given the large number of scenarios, often in the billions, solving them poses huge computational challenges, which is a key barrier for adaptive designs in practice.

The authors developed a computationally efficient approach using heuristics, or rules-of-thumb, to implement adaptive designs. The authors then simulated their model called “SLAX” multiple times on the computer; they settled on around 5,000 times, which worked well, another rule-of-thumb. Ahuja noted that these types of problems “are a combinatorial nightmare, and given the limits of computation, may not have been possible to solve a few years ago.”

“Clinical trials, particularly phase-3 trials, have been cited as major contributors to the rising costs of taking a new drug to market.”

The authors tested their approach retrospectively on three phase-3 clinical trials that studied Rolapitant, a drug used for chemotherapy-induced nausea. “On every dimension, the outcomes [in our approach] were better,” said Ahuja. Drug companies want to get their products to market sooner and at lower cost. This advance is “a big deal,” according to Ahuja. The paper, “An Approximation Approach for Response Adaptive Clinical Trial Design,” chronicles their work.