Recently published research from the Massachusetts Institute of Technology (MIT) and Mayo Clinic proposes a mathematical framework that may accelerate drug development.
Statistics
The research, published in JAMA Oncology, involved incorporating patient preferences directly into the drug approval process. According to the senior author, Andrew Lo, PhD, the new approach would be more responsive to the most urgent unmet medical needs as well as greatly speed up the drug development process.
“Randomised clinical trials — where patients are assigned randomly to two groups, one receiving a new treatment and the other receiving a placebo — are the gold standard for determining the safety and effectiveness of a treatment,” said Lo. Once a significant improvement has been found in the treated group then regulators will approve the therapy, which prevents unsafe and ineffective therapies (false positives) entering the marketplace.
Lo and team worked out the optimal risk of false positives on a case-by-case basis by examining the severity of the disease, the number of patients affected and the value of an effective treatment to patients. For colon cancer, the method yielded an optimal risk of 2.3% but for glioblastoma, a fatal disease, the optimal risk was 47.5%, which reflects the fact that survival time for these patients is low and there are currently no effective treatments for the condition.
“The FDA already takes into account the urgency of unmet medical needs through a number of programmes and processes; our proposed framework will allow them to incorporate the patient perspective directly into their decisions in an objective, systematic, transparent and repeatable manner,” summarised Lo. “Terminal patients simply can’t afford to miss effective drugs that can extend their lives.”