4 Steps the FDA plan to take to improve the use of AI and RWE in clinical trials

Gottlieb pushes for the use of new approaches and new technology to make more reliable treatment decisions

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Natasha Taylor
02/05/2019

In a recent speech at the Bipartisan Policy Center conference, FDA Commissioner, Scott Gottlieb, discussed how the future success of clinical trials will be underpinned by new streams of real world data (RWD). This includes information collected from electronic health records, lab tests, wearable devices, insurance claims and even social media.

As he made clear, “digital technologies are one of the most promising tools we have for making health care more efficient and more patient-focused”.

The FDA believes that these new approaches to collecting data and the utilization of new technology can radically expand the sources of data available. This will offer important evidence on both the product safety and effectiveness in settings and populations that are notably different to those used within approved trials. The increased level of information on the practical use of treatments can also help to drive more reliable treatment decisions. As Dr. Gottlieb recognized, in many cases the tools can “help make prospective trials more efficient and more reflective of how care is delivered in the ‘real world’”.

 

How the FDA intends to advance digital technology use in clinical trials

During his speech, Dr. Gottlieb announced four additional activities the FDA will be pursuing to help advance the opportunities from these new streams of data for the benefit of patients.

First, the FDA plans to convene a stakeholder meeting to develop a framework on how digital systems can be used to enhance the efficient oversight of clinical trials. This is to support future seamless integration of digital technologies within clinical trials. Dr. Gottlieb notes that “these technologies present important opportunities to streamline drug trials and improve data site integrity by remotely monitoring data trends”. It is hoped that by working collaboratively with the clinical trial community and patient groups, the FDA will be able to develop scientific and technical standards that will allow new technology to increase agility and accessibility in trials, for both patients and regulatory bodies.

Second, Dr. Gottlieb recognized the great potential digital technologies have to bring clinical trials to the patient, rather than requiring the patient to travel to the investigator. Creating more accessible clinical trials, which facilitate participation by more diverse patient populations within diverse community settings, is a top priority. The FDA has established a formal working group on decentralized trials, who are working to release guidance in the coming months.

The FDA is also exploring how reviewers can have more insight into how labeling changes inform provider prescribing decisions and patient outcomes. Dr. Gottlieb explained how the Information Exchange and Data Transformation (INFORMED) is currently using RWD to examine the impact of a recent FDA labeling change for two approved products from weight-based dosing to flat-dosing of immune checkpoint inhibitors. This project aims to review how community practices are adopting the flat-dose label changes and the barriers or factors affecting this adoption.

Finally, to ensure that the agency can truly benefit from the volume, velocity and variety of real world data, the FDA will be looking to develop the capabilities of their staff with deep quantitative expertise. In the coming year, they will be looking to develop an FDA curriculum on Machine Learning and Artificial Intelligence in partnership with external academic partners. Dr. Gottlieb hopes that this initiative will allow them to “evaluate products that incorporate advanced algorithms facilitate the FDA’s capacity to develop novel regulatory science tools harnessing these approaches”.

 

As Dr. Gottlieb makes clear, the core aim of pursuing these initiatives is to make the healthcare system safer, smarter and more patient focused.


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