Paul holds a PhD in Molecular Biology from Université Pierre et Marie Curie, where he studied epigenetic modifications and their effect on gene transcription in development and oncology. He brings more than 10 years of hands-on expertise in presales and technical solution consulting for pharmaceutical accounts across EMEA, working with teams that engineer and deploy modalities beyond the classical antibody, from bispecifics and ADCs to cell and gene therapies.
Antibody programs sit on years of data that should be an ML advantage. In practice, it rarely is. Data infrastructure hasn't kept pace with novel formats, leaving data siloed and relationships missing. AI-driven discovery demands a standard nomenclature and connected experimental context. To solve this problem, we're introducing Benchling Biologics—antibody registration with structural awareness and automated annotation across mAbs, bispecifics, and fusions—and show how teams unlock faster DBTL cycles with structured data.