Road mapping AI implementation in life sciences

 

Implementing technological advances into the work that life sciences companies do has always been foundational — few industries are so consistently driven by advances in science. But each technological advance needs to be first assessed to understand its potential and only then adopted for use in a company’s overall mission.

 

Grant Thornton Life Sciences National Managing Partner Zara Muradali recently sat down with MassMEDIC President Brian Johnson, AI Ethicist Matt Sample of the Institute of Experiential AI and Modi Ventures General Partner Sahir Ali for an hour-long discussion about AI and life sciences. Part of that discussion, excerpted below, centered on a big-picture view of the life sciences industry and explored the motivations for leveraging new technologies to improve and simplify processes.

 

 

 

New directions using AI

 

3:20 | Transcript

 

In this portion of their discussion, Johnson points out that, while machine learning has been a part of the medical device industry for decades, a new era is upon us, one in which we are exploring new applications of the technology to improve the patient experience and outcomes. He paints a picture of a future in which the industry explores ways to leverage the work that has already been done and to work with the FDA to shorten go-to-market timelines.

 

3:07 | Transcript

 

In this video clip, Sample insists that a roadmap is needed for any deployment of AI. He recommends that, because of the ever-evolving nature of regulations impacting the implementation of new technologies, it is important to assign a dedicated team to manage compliance requirements and to understand the ongoing nature of the responsibility.

 

3:36 | Transcript

 

In this excerpt, Ali answers the question by comparing the current scenario with the historic adoption of electronic health record (EHR) technology by the healthcare industry. He presents the argument that widespread adoption of any technology solution requires an incentive, such as that of the Medicare incentive payments that were offered to physicians for adoption of certified EHR systems in 2010.

 

Productive approaches

 

4:02 | Transcript

 

Governance is an important issue that must be addressed when an organization makes the decision to roll out an artificial intelligence implementation. Sample talks here about the assessments needed to begin implementing new technology at a company, especially with large infrastructure governance. He shared how the experience at his Institute at Northeastern University includes recommendations to take an organization-wide approach to launching an AI initiative and to encourage employee involvement in the process.

 

3:13 | Transcript

 

In this clip, Ali draws comparisons of today’s shift to value-based care with the shift to the cloud. He discusses the evolution that begins at the business unit level and how it rolls out through the enterprise. He shares his belief that a number of new C-level roles will be needed to ensure the success of AI when the shift to value-based care happens.

 
 

4:08 | Transcript

 

In this excerpt, Johnson focuses on the need for governments to play a major role in convening and listening to stakeholders, including an illustrative example in Massachusetts. Sample points out the need for these sorts of discussions when developing digital policies. Ali calls out the need to act precipitously, because of the speed at which these new technologies are being adopted.

 
 

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