From the pages of Politico:
Gottlieb promotes FDA move away from traditional three-phase clinical trials
FDA Commissioner Scott Gottlieb on Monday laid out new clinical trial approaches and digital techniques that he said could get medicines to patients sooner and at a lower price by moving away from the time-honored, traditional three phases of clinical trials.
"We're on an unsustainable path, where the cost of drug development is growing enormously, as well as the costs of the new medicines. We need to do something now, to make the entire process less costly and more efficient. Otherwise, we won't continue to realize the practical benefits of advances in science, in the form of new and better medicines," Gottlieb said in a speech delivered at the RAPs Convergence Conference.
Although development costs aren't necessarily mirrored in treatment prices, they are an important factor, he said. The steep price of development may also be causing fewer drugs to get developed, particularly because so much of the cost burden of drug development is front-loaded at the earliest stages, he said.
He called for savings in development costs to be passed along to consumers, but gave no details on how the government might ensure savings are shared.
"We need to reduce the risk and uncertainty that makes drug development increasingly costly, he said, "and make sure that we have markets that are competitive, and let us capture those savings in the form of lower prices."
FDA is taking a number of steps to modernize how clinical data can be collected, Gottlieb said.
One approach is "seamless" trials, which already have been used to test drugs on various cancers at a single time. In such studies, instead of conducting the usual three phases of clinical trials, a company conducts one large adaptive trial where data can be observed at certain intervals. This reduces the number of patients needed in the trial and saves time and money.
"This approach is well suited" to drugs being developed now to target specific changes that can be found in different disease states, Gottlieb said.
FDA is also encouraging companies to pursue common control studies, where multiple drugs are tested against the same control arm, and large simple trials, which have large sample sizes and statistical power, thereby providing less ambiguous results and minimizing the effects of random errors.
Another new approach is the master protocol concept, in which a single trial evaluates multiple treatments in more than one subtype of a disease or type of patient. Master protocols have been used in cancer drugs and in antibiotic development, to evaluate medicines targeting pathogens in different parts of the body.
The FDA plans to issue new policy and guidance documents to help companies make better use of these approaches, Gottlieb said.
To protect patients, the agency is adapting its safety screening to these new trial types, he said. For example, informed consent documents for seamless trials need to be updated throughout the trial to reflect new safety and efficacy evidence gathered in the process.
Since these trial designs may allow an entire drug development program to take place in just one study, FDA may also need to build in new regulatory milestone meetings to check on progress and provide oversight and advice.
"This is not 'business as usual' approach. It may require a much more iterative process, with greater communication between all of the stakeholders involved in the clinical trial processes," Gottlieb said.
FDA is also modernizing its evaluation of company data, with more advanced software and sophisticated statistical and computational models. Gottlieb said he wants to increase FDA investment in high-performance computing because access to this technology at the agency is limited.
Computer modeling can help select the optimal dose of a drug or better estimate effect size to figure out the ideal number of patients needed in a clinical trial. It can also help FDA determine whether the trial endpoint a company wants to study is appropriate for the disease at hand.
The agency will convene a series of workshops, publish guidance documents and develop policies and procedures for translating modeling approaches into regulatory review, Gottlieb said. It will also conduct a pilot project to test use of these new computer tools with willing drug companies.
The agency has ongoing projects underway to use software to develop natural history models of diseases like Parkinson's, Huntington's and Alzheimer's disease. This information can make trial recruitment more efficient and help evaluate the effect of a treatment again the normal course of disease.
The agency is developing algorithms that could help speed trials. For example, its working on a lung cancer algorithm it hopes can help classify how well a tumor responds to a drug treatment.