Quantitative Framework Could Aid Drug Review: Researchers

Share

UCLA Anderson School of Management researchers say they have developed a quantitative framework that FDA could use to assess candidate drugs based on severity and prevalence as well as characteristics of the drug development process and existing market. “Such a model could augment the complex decision-making and statistical analyses conducted by FDA, providing a more customized approach to policy-making,” the researchers say in their paper.

The researchers note that the tension between providing sick patients with potentially beneficial remedies, while protecting consumers from harmful adverse events, plays a significant role in FDA decision-making. They say they developed a “novel queuing model” of the drug approval process, starting from development through evaluation, FDA approval or rejection, and obsolescence or market expiry. “Our modeling framework can proffer insights for FDA’s approval policy, by permitting flexible approval standards based on differences in disease severity, the number of individuals afflicted with a disease, intensity of research and development, and the number of alternative treatments available for a target condition,” the paper says.

The researchers say their model accounts for three key contributors to the shortfall of therapies available to treat some diseases — low innovation in new drug formulation, lengthy clinical trials, and high rates of attrition in the development process. “Over the years, FDA has introduced a variety of programs designed to address these challenges,” the researchers write. “Our model could help evaluate the impact of these programs on health benefits/costs and monetary gains/losses and, in the case of drugs that qualify for multiple programs, identify which programs offer the largest societal benefit.”

The researchers’ tool is also discussed in this online blog.

Read more