Ruemu E. Birhiray, MD, a medical oncologist and hematologist at Hematology Oncology of Indiana, an affiliate of the American Oncology Network, discussed the advantages of using artificial inteligence (AI)–based tools to enhance community-based clinical trials in oncology.
One advantage of integrating AI into the clinical research framework is its capacity to mitigate the administrative burden placed upon providers. By automating or streamlining heavy administrative tasks, AI ensures that clinical research can be conducted successfully without clinicians having to worry about non–patient-facing duties.
Beyond administrative relief, Birhiray emphasized the profound clinical utility of AI tools, particularly in the process of identifying eligible patients within a physician’s existing practice. This function is critical, as it directly addresses key bottlenecks in clinical trial operations, he explained. First and foremost, the precise identification of patients who meet the eligibility criteria leads to measurable improvements in clinical trial enrollment. Secondly, the strategic application of AI tools results in substantial time savings for clinicians.
Birhiray stressed that this conserved time can then be utilized in a more appropriate and patient-focused manner. For instance, a common practice challenge involves sifting through a large volume of patient records—potentially a pool of 2000 patients—to find appropriate candidates. An AI tool can perform this screening rapidly, narrowing the focus to a manageable number, such as 20 eligible individuals. This efficiency allows clinicians to actively “hone in on those 20 patients,” ensuring they are identified and recruited, Bihiray stated. Because the physician now has more dedicated time, the likelihood of enrolling a greater number of appropriate patients increases.
Ultimately, technological tools like AI are vital for optimizing the administrative and clinical processes necessary for advancing community-based clinical research, Bihiray concluded.