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TERATEC 2020 Forum
Tuesday October 13, 2020 - Workshops

Workshop 07 - 14:00 to 15:30

Digital twin in medicine: are we [im] patients?
Chared by Philippe Gesnouin Project Officer EIT Health and EIT Digital, Inria

How virtual patients cohorts can support us in identifying the patients who will mostly benefit from our treatments ?
By Sylvia Julien, Director Digital Biometry, Ipsen

A virtual clinical trial is a trial run to test multiple clinical scenarios using virtual patients. The purpose of running a virtual trial is identify the type of patients who will most benefit from our treatment. 

At Ipsen, we generate virtual patients population leveraging all clinical data and available disease knowledge by the mean of robust statistical methods to generate virtual patients and of machine learning approaches to predict potential clinical endpoint(s). By design, virtual clinical trials are low in cost, allowing us to run multiple scenarios, that increase the probability of the trial succeeding. Ethically, virtual clinical trials represent the future of drug testing because they avoid exposing patients to drugs with low expected benefits, improve trial design and consequently patient safety and help insure more confidence in drug efficacy.

Biography  : Sylvia Julien currently leads Scientific Intelligence, Analytics, and Modeling team at Ipsen R&D. Sylvia is a scientist by training with a PhD in oncology from Institut Curie, Orsay and an oncology post-doctoral fellow in Max Planck Institute in Martinsried (Munich, Germany) in the department of Axel Ullrich who has deeply contributed to Sutent discovery. She has also a strong biochemical, cellular & molecular background inherited from her years at Ecole Normale SupĂ©rieure of Cachan. She has started her industry Career at Ipsen in 2008 where she had several positions since then: Post-doctoral fellow in the generation of collections of Patients Derived Xenograft models, project leader for multiple external partnerships with Oncology Centers of Excellence, IMI initiatives, and Data integration & modeling consortium with Dassault Systèmes, and Head of Europe in Scientific Affairs department to source external assets. Since 2017, Sylvia leads the SIAM team who is composed of key experts in bioinformatics, Real World data analysis, scientific intelligence and predictive modeling to leverage all data available to inform decisions on projects when it comes to: i) biomarkers identification, ii) better knowledge of patients populations and comparators, iii) competitive intelligence and iv) better identification of the optimal patients settings in clinical studies (among others).

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