Aurelien Rizk

Chief Scientific Officer InterAx Biotech

Aurélien Rizk is the co-founder and Chief Scientific Officer of InterAx Biotech, a biotechnology company advancing drug discovery through mathematical modeling, AI, computational chemistry, and cellular assays to identify optimal GPCR signaling profiles for efficacy and safety and create differentiated therapeutics. He specializes in computational models of cell signaling and GPCR pathways and has published over 15 papers on mathematical modeling of GPCR signaling. Aurélien completed postdoctoral research in 2015 at ETH Zurich and the Paul Scherrer Institute, earned his Ph.D. in computer science at INRIA in 2011, and previously co-founded Algorizk, a company delivering real-time physics simulations for education. He studied mathematics, physics, and computer science at the French Grande École Normale Supérieure de Cachan, and works at the intersection of computational biology and innovative drug discovery.

Seminars

Wednesday 29th April 2026
Panel Discussion: Assessing the Pharmacological Impact of Biased Signaling, Endosomal Pathways & Oligomerization to Demystify GPCR Complexity
12:15 pm
  • What are the innovative methodologies to study biased, endosomal, and oligomeric GPCR signaling?
  • How can we establish best practices for interpreting complex signaling data and distinguishing true pharmacological effects?
  • How to translate mechanistic insights into improved GPCRs-targeted drug discovery and development
Wednesday 29th April 2026
GPCR Signaling Models for Mechanism-Driven Drug Discovery
9:00 am
  • Disentangling intrinsic, system, and kinetic bias using time-resolved signaling assays combined with mechanistic mathematical modeling to provide a clearer, more reproducible and more predictive view of GPCR signaling
  • Linking extended signaling parameters, beyond traditional potency and efficacy, to downstream functional effects to identify the optimal signaling profile for therapeutic efficacy and tolerability
  • Enabling more efficient small-molecule design and optimization by connecting mechanistic signaling insights directly to chemistry and SAR
Aurelien Rizk