A Personalized Medicine Approach Using Clinical Utility Index and Exposure-Response Modeling Informed by Patient Preferences Data

Selection of a personalized dose for an individual patient can be informed by the patient's preferences, translated as weights on each of the clinically relevant safety and efficacy drug attributes, based on results from a brief patient preference elicitation questionnaire. In this analysis, the weighted attributes were simulated to represent various endometriosis patient profiles. Exposure-response simulations were performed for elagolix, a drug approved for management of moderate to severe pain associated with endometriosis, across a range of plasma exposures corresponding to a range of doses. The results were combined to calculate a personalized clinical utility index. An interactive user-friendly online application was developed and envisioned as a physician's desk tool to personalize the dose selection process based on individual patient preferences. This demonstration should serve as an example of how patient/physician conversation can be facilitated with quantitative tools for personalizing the dose.