Pharmacy Times: How AI, machine learning can benefit pharmaceutical development, research
Pharmacy Times highlighted a presentation from the University of Cincinnati's Shawn Xiong discussing the potential for artificial intelligence (AI) and machine learning to bolster pharmaceutical development and research.
Xiong, PhD, assistant professor at UC's James L. Winkle College of Pharmacy, presented the American Pharmacists Association (APhA)-Academy of Pharmaceutical Research and Science Keynote at the 2024 APhA Meeting and Exposition March 22.
In the pharmaceutical industry, Xiong said the top three use cases for AI are predictive maintenance, quality inspection and assurance and manufacturing process optimization. In clinical practice, Xiong said early detection and personalized treatment are particularly exciting areas of potential.
“This is not only about identifying the disease itself,” Xiong said. “It’s also about providing insights into the unique situations of the patient so that we can make personalized treatments for the patient, especially considering the concept of patient-centered care.”
While the potential is encouraging, Xiong noted there are still limitations and concerns, including nuances of medical language and privacy and security concerns with patient data. As these issues are addressed, however, Xiong said AI and machine learning could significantly improve the future of pharmacy.
“AI and machine learning can help automate the medication filling process, improving accuracy and also saving time,” Xiong said. “The AI can help check and double-check errors in the medication orders, and they can help us identify errors and reduce errors so that patients are getting what they need and how they need it.”
Read the Pharmacy Times article.
Featured image courtesy of Adobe Stock.
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