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BSc in Biotechnology (UPM), MSc in Biophysics (UAM), and PhD in Applied Mathematics (UCLM). Currently holding a position as Assistant Professor of Applied Mathematics, his work at MOLAB focuses on evolutionary dynamics and virtual clinical trials in cancer. The discrete stochastic tumor growth model developed in his Ph.D. thesis (2022) has been used for human data-based studies on evolutionary dynamics, to discover new biomarkers in different cancers, and to optimize glioblastoma treatments. |
Publications
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On optimal temozolomide scheduling for slowly growing glioblastomas
Neuro-Oncology Advances 4(1), vdac155, 1-13 (2022)
B. Segura-Collar, J. Jiménez-Sánchez, R. Gargini, M. Dragoj, J. M. Sepúlveda, M. Pesic, M. A. Ramírez, L. E. Ayala-Hernández, P.Sánchez-Gómez, V. M Pérez-García
Projects
- Model-based digital twins for biomarker development and virtual clinical trials in oncology.
Supported by project SBPLY/24/180225/000193, funded by Junta de Comunidades de Castilla-La Mancha. Spain and European Regional Development Fund (ERDF A way of making Europe). (2025 - 2028) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024)
Jiménez Sánchez, Juan
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BSc in Biotechnology (UPM), MSc in Biophysics (UAM), and PhD in Applied Mathematics (UCLM). Currently holding a position as Assistant Professor of Applied Mathematics, his work at MOLAB focuses on evolutionary dynamics and virtual clinical trials in cancer. The discrete stochastic tumor growth model developed in his Ph.D. thesis (2022) has been used for human data-based studies on evolutionary dynamics, to discover new biomarkers in different cancers, and to optimize glioblastoma treatments. |
Publications
- On optimal temozolomide scheduling for slowly growing glioblastomas
Neuro-Oncology Advances 4(1), vdac155, 1-13 (2022)
B. Segura-Collar, J. Jiménez-Sánchez, R. Gargini, M. Dragoj, J. M. Sepúlveda, M. Pesic, M. A. Ramírez, L. E. Ayala-Hernández, P.Sánchez-Gómez, V. M Pérez-García
Projects
- Model-based digital twins for biomarker development and virtual clinical trials in oncology.
Supported by project SBPLY/24/180225/000193, funded by Junta de Comunidades de Castilla-La Mancha. Spain and European Regional Development Fund (ERDF A way of making Europe). (2025 - 2028) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024)
