In silico Clinical Trials with Virtual Populations Help Accelerate Access to New Drugs (Webinar)

In silico modeling enhances clinical trials. Unlike regular clinical trials, in silico clinical trials enable researchers to explore an almost unlimited number of hypotheses. Mechanistic modeling encompasses more available knowledge than other in silico approaches. It can be useful even when data is limited. Mechanistic models create virtual populations that allow researchers to simulate both individual- and population-level effects. It captures differences between individuals, as well as intra-individual variability — changes within the same individual that may occur over time. In silico approaches are critical as medicines become more personalized and conventional trials become more challenging, both practically and ethically. This explains regulators’ strong interest in model-informed drug development. What you will learn: The advantages of in silico clinical trials based on mechanistic modeling How mechanistic modeling differs from (but can complement) data-driven and artificial intelligence (AI) approaches Why embracing modeling has become urgent Why the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are interested Speaker: Emmanuel Pham, VP Science & Customer Experience Europe, Novadiscovery Emmanuel has more than 20 years of pharmaceutical industry and academic experience. He is in charge of strengthening NOVA’s relationships with pharmaceutical companies to understand their specific requirements for incorporating in silico technology into existing clinical development programs with a view to streamlining the development process through smaller, more effective clinical trials. He also works with regulatory authorities to develop protocols to aid pharmaceutical companies in including clinical simulation data into regulatory dossiers for new drug applications.