This article was originally published in July 2023 on Pharma's Almanac. Here is an excerpt:

Cristina Varner, Senior Vice President and National Life Science and Digital Health & Telemedicine Practice Leader, Newfront

"The potential applications of machine learning in pharma/biopharma are vast, and the technology is likely to transform the industry in the years to come.  Like many industries, the life sciences industry overall needs to continue to evolve and improve efficiencies. Machine learning can help optimize clinical trials by identifying patient populations that are most likely to respond to a particular therapy. AI algorithms can help identify and screen patients who are suitable for clinical trials by analyzing large data sets and electronic health records. The algorithms can match patients with specific eligibility criteria and engage them through online platforms, leading to faster enrollment and recruitment.  These applications could potentially be useful in streamlining the variability and complexity of clinical trial insurance. AI can monitor patients remotely, eliminating time-consuming and costly regular hospital or site visits.  AI has the potential to improve the efficiency, accuracy, and safety of clinical trials by optimizing various processes from recruitment to patient monitoring and data analysis."