During this session, the panelists discussed how stakeholders in the clinical research market can leverage new technologies to better identify subjects, optimize trial conduct and reduce costs. For example, common use cases of artificial intelligence (AI) in research include automating administrative and documentation tasks. Panelists also discuss the role of technology in curating data to power clinical trials. Challenges remain in implementing research-focused technology tools, especially as trials increase in size and patients remain concerned about large collections of sensitive health data.

Session panelists:

• Nathan Cohen, Vice President, Norwest VenHture Partners
• Jennifer Geetter, Partner, McDermott Will & Emery
• Raj Kothari, Senior Vice President, Jefferies
• Seungtaek Lee, Vice President of Strategic Provider Partners, ConcertAI
• Alexander Saint-Amand, Chief Executive Officer and Co-Founder, Topography Health
• Moderator: Kevin Sullivan, Partner, McDermott Will & Emery

IN DEPTH

Top takeaways included:

• Research Technology Can Address Pain Points in Research; Persistent Hurdles in Implementation. Time, cost, patient recruitment and increasing complexity in study design – present ongoing and new challenges impacting clinical research. Technology has a key role to play in minimizing these challenges. For pharmaceutical companies, bringing a product to market requires massive investment and can involve a long and uncertain development runway. One persistent frustration is difficulty with patient enrollment. The companies able to deploy technology to address these concerns include Contract Research Organizations (CROs), large technology companies and, of most interest to investors lately, independent technology providers that take a community lens, independently serving CROs and sponsors to help conduct trials more efficiently. To implement effective technology solutions, stakeholders need to: a) invest in sophisticated data tracking solutions; b) consider the implementation hurdles of multiple point of care solutions for overstressed health system CISOs and CTOs; c) be sensitive to and address privacy concerns and cyber threats; and d) consider user-friendly tools that can be understood by subjects.
• AI Will Play an Increasingly Important Role as Trials Become More Focused on Big Data Initiatives. For AI to add value to the research sector, the data training AI must be reliable and fit for purpose. Stakeholders that executive strategic partnerships to harness well-curated EHR and other data sources and implement effective strategies to both be a data provider and data ingester will see strategic advantages. With appropriately designed and tested AI tools, technology can be deployed to accelerate patient matching to find candidates that meet the study’s criteria, with lower screening failure rates, and can be used to accelerate drug development. IRBs do need additional training to understand AI and its role in clinical research.
• Investor Funding in Cutting-Edge Technologies, but Also in Proven Tools, Will Continue. In the next year, investors will continue to seek out exciting new technologies, such as wearable devices that can make patient data easier to transmit for real-world clinical trials and platforms that can make informed consent easier for patients to understand with videos and other interactive features. Because large technology companies have run into stumbling blocks when migrating different tech tools, investors are also interested in starting new businesses organically with technology that is interoperable and has data-linking capabilities. There is an interest in data review solutions, with some emerging in risk-based quality management or monitoring. In addition to state-of-the-art products, dollars will continue to flow toward defensive, proven, profitable businesses in the research space, such as Electronic Clinical Outcome Assessment tools and Interactive Response Technology.