Optimal personalised treatment computation through in silico clinical trials on patient digital twins
This work addresses precision medicine by potentially reducing time, cost, and ethical concerns in clinical trials, though it appears incremental as it applies existing simulation methods to a specific domain.
The paper tackles the problem of optimizing personalized pharmacological treatments by using in silico clinical trials on patient digital twins, demonstrating effectiveness in a case study on assisted reproduction protocols.
In Silico Clinical Trials (ISTC), i.e., clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation--based experimental campaigns (ISTC) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine). e show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.