With the advent of electronic health records, low-cost genome sequencing, molecular imaging, and wearable devices, the digital footprint of the average patient is rapidly expanding. As an increasing number of data scientists and computer scientists join those on the front lines of medical research and these researchers gain access to an enormous amount of computing power in the cloud, there will be unprecedented opportunities to use data to accelerate medical research and develop more cost-effective, personalized treatments.
ITIF’s Center for Data Innovation will host a public forum with key stakeholders from government, the private sector, and academia to discuss the latest developments in using data to improve health care outcomes, reduce health care costs, and empower patients. In particular, this event will focus on the successful ways the pharmaceutical industry is using data to create more value in health care, especially by using data to drive down costs, bring drugs to market faster, and address the needs of different patient populations.
Panel 1: Accelerating Data-Driven Drug Discovery
Pharmaceutical research is an increasingly data-driven process. Researchers are using artificial intelligence to automate the drug discovery and development processes. For example, researchers can use recommendation algorithms to predict which untested compounds show the most promise and send these for more advanced testing in the lab. Similarly, researchers are using machine learning techniques and image recognition technology to extract biological insights from new experimental compounds. And researchers are making significant advances in using in silico research methods to predict how patients might respond to various experimental treatments. What are the opportunities and challenges that will arise from these advances in data-driven medical research, and how can government help accelerate these types of innovations?
Panel 2: The Future of Data-Driven Clinical Trials
New technologies, particularly wearables and mobile apps, present new opportunities for collecting data during clinical trials, while the growth of electronic health records and online communities creates new opportunities to recruit qualified participants for clinical trials as well as using new research designs that embed clinical research into traditional medical care. What are the technical, organizational, and legal obstacles to data sharing in clinical research settings, and what improvements would allow patients, researchers, and companies to extract more value from health data? Moreover, how can policymakers support growing the patient data pool, increasing data sharing, and addressing the needs of diverse populations, including patients that suffer from rare diseases?
Panel 3: Modernizing Regulatory Processes for Data-Driven Medicine
Proper government oversight of medical products is responsible for delivering safe, effective, and affordable treatments to patients. As drug research and development and clinical trials evolve to make use of expanding data sets and new technologies, regulatory agencies need to keep pace with these changes. For example, regulatory agencies can use artificial intelligence to analyze diverse data sets to improve the speed and accuracy of regulatory decisions, as well as enhance post-market surveillance. How are regulatory agencies adapting to recent innovations in medical research, and how can better use of data improve the regulatory review process?
Speakers to be announced. Learn more at datainnovationday.org.