CHELONIA SA

Their core work

CHELONIA SA is a small Swiss private company specialising in drug discovery, with capabilities spanning both experimental structural biology (X-ray crystallography, cryo-EM) and computational drug design (molecular dynamics, AI/ML-driven ligand generation). They have contributed to two successive Europe-wide drug discovery platforms built on exascale HPC infrastructure — first in response to COVID-19, then in building a next-generation portable drug design pipeline. In practice, they bring a technically specific profile to large consortia: the ability to characterise target proteins experimentally and then translate that structural knowledge into computational screening campaigns. Their small size suggests a focused team of specialists rather than a broad research organisation.

What they specialise in

How they've shifted over time

In their first project (2020–2021), CHELONIA's contribution was dominated by experimental and biological methods — structural biology, crystallography, cryo-EM, biochemical and phenotypic screening — applied to the urgent problem of identifying COVID-19 antivirals through repurposing. By their second project (2021–2024), the keyword profile shifted decisively toward computational methods: molecular dynamics, computer-aided drug design, and AI/ML, with no mention of wet-lab techniques. This progression suggests CHELONIA is either broadening from a structural biology base into computational chemistry, or positioning itself as a bridge between the two disciplines within exascale drug discovery pipelines.

CHELONIA is moving toward AI-augmented computational drug discovery on portable HPC platforms, making them an increasingly relevant partner for any consortium that needs to connect experimental target characterisation with scalable in silico screening.

How they like to work

CHELONIA has never coordinated an H2020 project — in both cases they joined as participants within large multi-institutional consortia. With 24 unique partners across 9 countries from just 2 projects, they consistently operate in very large, pan-European teams rather than small bilateral collaborations. This profile indicates they are brought in for a well-defined technical contribution rather than to manage or lead; consortium builders should expect a focused, expert-level contributor rather than an administrative or coordinating partner.

CHELONIA has accumulated 24 unique consortium partners across 9 countries from only 2 projects, reflecting their participation in large, geographically distributed consortia typical of major health and HPC initiatives. Their network is European in scope with no apparent regional concentration, driven by the composition of the consortia they joined rather than bilateral relationships.

What sets them apart

CHELONIA occupies an uncommon position for an SME of its size: proven experience in both structural biology (experimental target characterisation using crystallography and cryo-EM) and computational drug design (molecular dynamics, AI/ML), within the specific context of exascale HPC platforms. Most organisations of similar scale specialise in one side of this divide. Their repeated inclusion in Europe's largest drug discovery platform projects — EXSCALATE4CoV and LIGATE — suggests they are a trusted and technically credible contributor in a highly competitive field. For consortium builders, they offer a rare combination of experimental validation capacity and computational design capability from a single, nimble SME partner.

Highlights from their portfolio

• EXSCALATE4CoV
  One of Europe's highest-profile emergency COVID-19 drug discovery projects, where CHELONIA contributed structural biology and repurposing expertise to a platform that screened millions of compounds against SARS-CoV-2 targets.
• LIGATE
  CHELONIA's largest funded project (EUR 156,625, running to 2024), focused on building a portable AI-powered ligand generation platform at exascale — representing the clearest evidence of their shift into computational and machine-learning drug design.