AI is key to precision medicine.

RC: Just as genomics transformed oncology care over the last several decades and offered the ability to treat with precision, the behavioral measurements we are now able to capture with Al tools will help catalyze precision medicine in drug development and tailor interventions with unprecedented specificity. For example, novel patient assessments such as video- and audio-based digital biomarkers can identify the subtleties of a patient's wellbeing and response to treatment in ways that in-person assessments alone cannot. Particularly for conditions with symptoms that need to be or can be assessed with audio and visual cues by tracking metrics such as a patient's facial expressions, eye twitches, speech, or movement, digital biomarkers help detect specific behaviors associated with certain diseases and treatments with more precision than ever before. By assessing these objective insights over time, physicians can understand how medications are impacting a person's quality of life, such as their ability to tie their shoe or write their name and make informed decisions about the future of their care plan. OSP: Please talk about the use of Al to track patients and predict their behavior. RC: In addition to digital biomarkers, Al-powered predictive analytics can also help drive precision medicine by predicting patient behavior before trials even begin. Using a placebo lead-in period, Al can help predict if a patient will likely adhere to their treatment plan, or if they tend to have trouble staying on track. Knowing this in advance can help sites effectively focus on patients who may need more support once they are enrolled in the trial, tailoring their interventions and personalizing resources accordingly to keep them engaged. Predicting a patient's future behavior based on past behavior allows sites to be more proactive and personal in their engagement tactics.