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Transferring mathematical models to drive innovation in virtual clinical trials for the biomedical industry (TRANSFERMATH)

2025-2028

The TRANSFERMATH project aims to advance early-phase clinical trial design through mechanistic model-based virtual clinical trials (VCTs). It will deliver a proof-of-concept for integrating predictive mathematical models into academic and industrial drug development, enabling data-efficient, ethical, and cost-effective trial optimization. We will work on two clinician-led trials in rare diseases: CELYVIR-based virotherapy for paediatric brain tumours (Hospital Niño Jesús, Madrid) and denosumab for fibrous dysplasia (NIH, Bethesda). We will also target industrial validation through retrospective simulation of Phase II trials with CROs and pharmaceutical partners, supporting dose optimization and improved trial design within a Model-Informed Drug Development framework.

Why Mathematics?

TRANSFERMATH will integrate of mechanistic mathematical model-based virtual clinical trials (VCTs) into early drug development and translational research. The Project will implement a fully operational pipeline linking model development, clinical interpretation, and trial design in both research academic and industrial settings. This end-to-end workflow from model calibration to simulation-driven decision support and Phase II trial design marks a significant advancement in biomedical modelling.

The Team

The team is composed by the MOLAB members at Universidad de Castilla-La Mancha, Universidad de Cádiz, Universidad de Córdoba and Universidad Carlos III de Madrid, with multidisciplinary profiles in the area of applied mathematics, and a network of clinical collaborators including Manuel Ramírez Orellana (Hospital del Niño Jesús de Madrid), Alyson Boyce and Luis Fernández de Castro (National Institutes of Health Clinical Center, Bethesda, USA).

Impact

TRANSFERMATH will address essential requirements for auditability, explainability, and regulatory acceptability of model-based simulations. By working with clinicians, CROs, and industry partners, the project will identify real-world use cases where VCTs can reduce development time, support treatment individualisation, and rescue suboptimal therapies through improved dosing or patient selection. By developing reusable tools, documentation, and demonstrators, TRANSFERMATH will contribute to the technical and procedural standardisation needed for broader VCT adoption. Its dual focuson academic and industry-led trialswill highlight the scalability and flexibility of the approach, proving VCTs to be scientifically credible, technically feasible, and economically viable.

Funded by

Sponsors

© Mathematical Oncology Laboratory – MOLAB
Universidad de Castilla-La Mancha

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