Fusing AI/ML with cheminformatics modelling into project concepts

CLOUDPHARM is aspiring to support consortia as WP leader / task leader for technological activities in innovative proposals. What we can offer and in which calls:

• Drug target prioritization: CLOUDPHARM could support HORIZON-MISS-2027-02-CANCER-01 by integrating cheminformatics and computational modelling to assess and prioritise newly identified cancer targets according to their druggability and potential for therapeutic intervention.

• Drug repurposing:Drug repositioning is identified as a recommended activity in HORIZON-MISS-2027-02-CANCER-03. In this context, CLOUDPHARM’s ligand–target interaction modelling capacity could support the identification and prioritisation of existing drugs with potential activity against molecularly defined rare cancers, particularly those driven by specific protein defects.

• Mechanistic molecular modelling: CLOUDPHARM can computationally model interactions between biomolecules, small molecules and molecular targets to investigate mechanisms of action, molecular pathways and biological effects. This capability can support the interpretation of disease mechanisms, biomarker relevance, therapeutic responses and chemical–biological interactions across several Health and Cancer topics.

  Cancer target discovery — HORIZON-MISS-2027-02-CANCER-01: molecular interaction modelling could help characterise the functional consequences and druggability of newly identified cancer targets, supporting mechanistic interpretation and therapeutic prioritisation.

  Virtual Human Twins — HORIZON-HLTH-2027-03-TOOL-04: molecular-level interaction models could complement multi-scale VHTs by providing mechanistic information on molecular pathways, preventive interventions and chemical effects relevant to disease states.

  Predictive biomarkers — HORIZON-HLTH-2027-02-TOOL-01-two-stage: mechanistic modelling could support the interpretation of candidate biomarkers and their relationship with disease progression or treatment response, complementing AI-based predictive models.

  Adverse drug reactions — HORIZON-HLTH-2027-01-CARE-02: molecular interaction modelling could help investigate mechanisms underlying drug–drug interactions and adverse responses, supporting the identification of patients or medication combinations associated with increased risk.

  Neurodegenerative diseases — HORIZON-HLTH-2027-02-DISEASE-14-two-stage: molecular modelling could support the investigation of disease mechanisms and therapeutic mechanisms of action, as well as the computational prioritisation of promising intervention strategies.

• AI / ML pipelines: In the CSA HORIZON-HLTH-2027-03-TOOL-08, CLOUDPHARM could contribute its expertise in harmonising heterogeneous data sources into structured, interoperable datasets for AI model development. This includes experience extracting and structuring unstandardised textual biomedical information using LLMs, as well as developing LLM-based reasoning workflows and agents for clinical decision-support applications.

We welcome discussions with potential partners with established consortia or interested in building interdisciplinary consortia around shared scientific, technological and societal challenges.