Life sciences experts see great potential for artificial intelligence to improve health care. A recent Accenture survey found that 90 percent of life sciences’ executives recognized AI as important in driving innovation and achieving outcomes, such as hyper-personalized experiences, new sources of growth, and new levels of efficiency. However, some challenges remain.
Regulations have yet to catch up to the technology, data management continues to consume valuable time, there’s organizational resistance to change, and it can be difficult to understand why AI has come to a given conclusion.
The stakes are high — lives are literally in the balance. A deeper understanding of diseases and therapies will continue to personalize treatments, but to achieve the biggest impact, we’ll need to apply AI across data — no matter where or how it is stored — and strive for global cooperation and data sharing. Five experts weigh in.
1. Opportunities in Disease Management Are Significant
Because patients respond to treatments in various ways, physicians use a trial and error approach to treat some diseases. As methods improve to collect large volumes of patient-drug feedback, AI can help assess these trial and error clinical pathways — looking for markers and the different parameters that have led to success. We can try to answer questions about the impact of social and environmental factors, as well as physical responses to therapies. Finding that data and looking for patterns can help us find the right prescription in the right amount at the right time to treat diseases. —
Steven Gerhardt, CEO, Managing Partner of Element Blue
2. Opening the Black Box Will Increase Adoption
Explainable AI will become a requirement — especially for the medical industry. If AI makes a medical recommendation for an individual’s health or treatment, the doctor must be able to explain what logic and data was used to reach that conclusion. We are not yet at a point in our relationship with AI where many people are willing to take medication or have surgery because of a recommendation by AI, especially if the involved medical professional can’t explain the why of its recommendation. —
Candace Worley, VP and Chief Technical Strategist, McAfee
3. AI Can Help Bring Therapies to Market
It takes billions of dollars and more than 10 years to bring a new drug to market. The process generates massive amounts of data, and hidden in that data are the insights that could start a promising new drug program — or halt one otherwise doomed to fail expensively or one that is a possible risk to patients’ lives. Identifying drug candidates for repurposing in rare disease treatment or rigorously analyzing the safety and efficacy profiles of compounds in early R&D are all potential uses of AI in drug development. Overcoming obstacles in data cleanup and management will leave researchers free to focus on what the data is telling them in relation to their study. —
Tim Miller, VP, Life Sciences Platform Solutions, Elsevier R&D Solutions
4. AI Will Drive Changes in FDA Regulations
Companies pursuing AI technologies must realize that while the health care industry is embracing this technology, the regulatory landscape is still finding its footing. With AI being implemented across the health care continuum, the FDA and other agencies find themselves contending with the prospect of regulating a moving target. Use of AI systems promises better health care management for patients and faster, more accurate diagnoses for doctors, but FDA’s traditional regulatory framework will require major changes in preparation for the advances on the horizon. —
John J. Smith, partner at Hogan Lovell’s
5. AI Will Help Find Knowledge in Text
AI will help scientists use literature to make decisions, mine real-world evidence for insights, and match patients to trials. This helps address the challenge of the expense of bringing treatments to market, and efficiencies will need to be improved to mitigate some of that. So any repeatable, but time consuming, manual task likely can be automated. This frees up people to focus on the harder and more creative tasks. But challenges remain around transparency and organizational resistance to change.
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Matthew Michelson, CEO of Evid Science
Lucidworks Expert Roundups are invitation-only insights from leading C-Suite executives who share expertise, predictions, and observations about their industries. Email us if you are interested in contributing.
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