DIA: AI increasingly used in drug development

By Jenni Spinner

- Last updated on GMT

(sdecoret/iStock via Getty Images Plus)
(sdecoret/iStock via Getty Images Plus)

Related tags Drug development Artificial intelligence Data management DIA

A leader with the industry association discusses the surging interest in harnessing artificial intelligence to advance various treatments and therapies.

Like many life-sciences industry events, the Drug Information Association (DIA) has shifted from a physical conference taking place at a brick-and-mortar building, to a virtual event. In a discussion with Outsourcing-Pharma, DIA global chief executive Barbara Lopez Kunz revealed taking the session-packed program online was not easy but organizers achieved the transition by keeping the attendee in mind.

"We thought to ourselves, 'How would this person be best appropriated to receive this information?,' or 'How might this learning format gain (through live chat during a presentation, for example) or lose clarity via an intermediary screen?' Like anything else, it’s a constant work in progress, but we’ve had several meetings thus far with excellent attendee response and feedback. I like to think that as we share knowledge and provide a community space, we’re also learning and enhancing that experience with each passing day," she said.

Surge in AI interest

Many of the sessions available during the program (scheduled June 14 to June 18) focus on artificial intelligence (AI), and its utility in drug development. Kunz told us use of and attitudes toward use of AI have evolved as of late.

Over the last several years more and more companies are looking to the use of AI in drug development, to both increase efficiency as well as reduce costs​,” Kunz said. “The amount of data available across areas of drug development, including target verification, patient recruitment, clinical trial site selection, post-market safety surveillance, etc., has grown exponentially​.”

Kunz added, “This explosion of data requires efficient data analyses methods and better data analysis capacity. AI is perfectly poised to help with both​.”

Kunz shared with us a recent collaboration between DIA and the Tufts Center for the Study of Drug Development. A survey of 217 organizations (including pharmaceutical/biotechnology companies and service providers) discovered AI is used in every major function.

According to survey respondents, AI is most often used in clinical operations functions (61%), pharmacovigilance, safety, and risk management (57%) and information technology (55%). Also, 85% of respondents noted that their organization was looking to add AI expertise to their staff.

Greater understanding

Barbara Lopez Kunz, global chief executive, DIA

Kunz also commented that AI appeals because it “enables the generation of significant results from various, complex datasets​.”

AI can also analyze -omics datasets and help in precision and personalized medicine approaches. While often thought of as the silver bullet, AI analyses are limited by both the algorithms used to program systems and by unstructured datasets with potential inherent biases,​” she said.

She also said while personnel in some circles still are dubious of AI’s usefulness and practicality, she predicted that nervousness likely will shift.

Strengthening the AI infrastructure within the drug development industry, working to develop appropriate employee skill sets, and partnering with organizations developing the algorithms will alleviate any uncertainties around the use of AI in drug development,​” she explained.

AI-focused sessions

Kunz shared with OSP what she feels are strong AI-related sessions on the DIA roster, with diverse speaker representation (including sponsors, regulators and others):

• Non-Traditional Clinical Trials Require a Non-Traditional Workforce​, Tuesday June 16, 11:30am to 12:30 pm: panelists include representatives from Tufts, Association of Clinical Research Professionals, Paraxel and VirTrial

• How the FDA’s MyStudies Platform is Accelerating the Use of Digital Technology in Clinical Research and Clinical Trials​, Thursday June 18, 11:30 am to 12:30 pm: panelists include representatives from Google, Real World Evidence Analytics, Stanford University and Boston Technology

• Getting Real About Data Sharing for Drug Development and Drug Safety: What COVID-19 is Teaching Us About the Possibilities and How to Move from Anomaly to Precedent​, Thursday June 18, 5 pm: forum participants include representatives from Citizen, FDA, and Eli Lilly

• Sponsor and Regulator Challenges, Risks, and Mitigation Strategies for Ensuring Third-Party Oversight of Vendors: Is Your Study Data at Risk?​, Tuesday June 16, 11:30 am to 12:30 pm: forum participants include representatives from Gilead Sciences, Medicines and Healthcare Products Regulatory Agency and FDA.

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