CHEMOTARGETS SL

Their core work

Chemotargets is a Barcelona-based computational biology and cheminformatics SME specialising in in-silico target prediction, drug-target interaction modelling, and biomarker analytics. Their core product is software and analytical services that predict how chemical compounds interact with biological targets — applied both to drug discovery and to clinical decision-support in oncology. In PRIMAGE they contributed predictive modelling capabilities to a multiscale analytics platform designed to help clinicians personalise diagnosis and prognosis for paediatric cancers (neuroblastoma and DIPG). Their earlier involvement in BIGCHEM, a Marie Curie training network on Big Data in Chemistry, signals a foundational grounding in large-scale chemical data processing and machine learning applied to molecular systems.

What they specialise in

How they've shifted over time

In their earliest H2020 engagement (BIGCHEM, 2016–2019) Chemotargets operated at the methodological layer — contributing to a training network concerned with Big Data infrastructure and machine learning for chemistry broadly, with no project-level disease focus recorded. By 2018, they pivoted sharply toward clinical application: PRIMAGE repositioned their modelling capabilities directly inside a cancer-diagnosis pipeline, with explicit focus on paediatric tumours (neuroblastoma, DIPG) and imaging biomarkers. The trajectory is a clear move from generic computational chemistry tooling toward disease-specific precision medicine, with oncology as the landing zone.

Chemotargets is heading deeper into clinical AI — specifically computational tools that support oncology diagnosis and prognosis — making them a strong fit for future consortia in digital health, cancer biomarkers, or AI-assisted clinical decision support.

How they like to work

Chemotargets has never led an H2020 project as coordinator; they consistently enter consortia as a specialist technology contributor, bringing their computational platform to larger clinical or data-science projects. With 32 unique partners across 12 countries from just two projects, they clearly work inside sizeable consortia (PRIMAGE had over 15 partners) rather than small bilateral arrangements. This pattern suggests they are accustomed to operating as one technical module within a broader research infrastructure, which makes them a low-friction addition to multi-partner bids.

Across two projects Chemotargets has built a network of 32 unique partners spanning 12 countries, concentrated in Europe through PRIMAGE's wide clinical consortium (hospitals, imaging centres, IT companies). Their network is notably health- and data-science-oriented rather than purely chemistry-industry.

What sets them apart

Chemotargets occupies a rare intersection between classical cheminformatics (target prediction, QSAR) and clinical AI — they are not a pure software vendor and not a clinical research organisation, but a bridge between the two. Among Spanish SMEs in digital health, few combine molecular-level modelling with medical imaging biomarker analytics in a single toolset. For a consortium that needs a partner who can translate chemical or biological data into clinically actionable predictions, Chemotargets offers a validated, project-tested capability in paediatric oncology that most academic bioinformatics groups cannot match commercially.

Highlights from their portfolio

• PRIMAGE
  Their largest and most focused project (EUR 661,326; 2018–2023) placed Chemotargets at the core of an EU-funded clinical AI platform for paediatric cancer, directly demonstrating their ability to productise in-silico models for real diagnostic workflows.
• BIGCHEM
  A Marie Curie industrial training network (2016–2019) that situates Chemotargets within European cheminformatics research training, evidencing their credibility as a knowledge-transfer partner for early-career researchers in computational chemistry.