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Nova at AHA Scientific Sessions in Chicago, Nov 6–9Our prediction of Lp(a)HORIZON, presented Sunday, Nov 8See the sessions
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Berlin, Germany · 16–18 November 2026

Nova will be at the ESMO AI & Digital Oncology Congress

Three of us are on site in Berlin. Book a meeting, or come find us during the poster session.

About the congress

The congress brings oncology and AI specialists together to discuss digital innovation in cancer care, including responsible clinical use, ethics, regulation, and autonomous and agentic AI systems.

Come meet the team

Three of us are in Berlin for the congress. Book a slot ahead of time, or find us at a poster.

Frédéric Cogny

Frédéric Cogny

Co-CEO & Chief Product Officer

Leads product at Nova. Presents the work on grounding generative AI in mechanistic simulation and historical trial data.

Book a meeting
Yishu (Hélio) Wang

Yishu (Hélio) Wang

QSP Scientist

Presents three posters on mantle cell lymphoma modeling, synthetic control arms, and Digital Twin generation with cVAEs.

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Simon Arsène

Simon Arsène

VP of Scientific Solutions

Leads scientific solutions at Nova, keeping modeling projects efficient, collaborative, and scientifically rigorous.

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Come see our posters

Four posters on generative AI, mechanistic modeling, and Digital Twins. Frédéric presents 347P; Yishu (Hélio) Wang presents 192P, 362P, and 240P. Session details will be added once confirmed.

Frédéric CognyFrédéric Cogny
Poster
347P

Beyond Chatbots: Grounding Generative AI in Mechanistic Simulation and Historical Trial Data for Reliable Oncology Clinical Decision Support

Yishu (Hélio) WangYishu (Hélio) Wang
Poster
192P

Mechanistic Reconstruction of Mantle Cell Lymphoma Dynamics: Development and Calibration of a Quantitative Systems Pharmacology Model

Yishu (Hélio) WangYishu (Hélio) Wang
Poster
362P

A Digital Twin Framework for Synthetic Control Arm Generation: A Proof-of-Concept Assessment of the Phase III ECHO Trial Intervention Cohort

Yishu (Hélio) WangYishu (Hélio) Wang
Poster
240P

Conditional Variational Autoencoders (cVAE) for High-Fidelity Digital Twin Generation: Preserving Complex Patient Heterogeneity in In Silico Oncology Trials

View ESMO AI Digital Oncology Congress details

Cannot make it to Berlin?

Book a call with our scientists and we will walk you through the same work, applied to your program.

Talk to our scientists