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Mathematics against fibrous dysplasia: Biomarker discovery and treatment optimization

Fibrous dysplasia (FD) is a genetic disease caused by a mutation in the gene GNAS1 that leads to scar-like tissue growth in place of normal bone. It usually manifests for the first time in children ages 3 to 5 and results in bone deformity, brittle bones, pain and/or uneven growth of bones. There is no curative treatment. Skeletal-derived manifestations are typically treated with orthopedic surgery and/or bisphosphonates, and there are investigational drugs under study, like tocilizumab and denosumab. However, there is not a clear guideline of which patient should receive each treatment and what should be the dosage and schedule. Hence, great advantage could be obtained from the development of mathematical models and study in-silico of medical decision-making for FD.

Why Mathematics?

Mathematical models describe real systems by abstraction and mathematical formalism and may help in finding the best therapeutic combination regimens for specific patients. The rarity of the FD makes it challenging to investigate and to design clinical studies. Clinical trials for investigational new treatments are rare and typically involve a limited number of research sites recruiting from a small pool of dispersed patients.

We intend to add the mathematical dimension to these efforts to provide a new perspective on these problems. However, no previous mathematical studies have considered FD. This project has a substantial multidisciplinary content. It includes mathematical and advanced computational methods, and advanced biomedical knowledge. The use of clinical data, imposing toxicity and real-world restrictions requires the involvement of medical doctors.

The Team

The research team for the mathematical part of the project includes Víctor M. Pérez García (MOLAB-UCLM), Juan Belmonte Beitia (MOLAB-UCLM), Gabriel F. Calvo (MOLAB-UCLM), Julián Pérez-Beteta (MOLAB-UCLM), Magdalena Caballero (UCO), Juan Carlos Beltran Vargas (MOLAB-UCLM), Mariia Soloviova (MOLAB-UCLM).

Biological knowledge is provided by Luis A. Fernandez de Castro (NIH), Bethesda, USA. Clinical aspects will be addressed in collaboration with leading medical doctor Dr Alison Marie Boyce and Dr Vardit Kram Frankel (NIH), Bethesda, USA, as well as with members of the scientific committee of the Spanish Fibrous Dysplasia Association (ADF) Beatriz Lecumberri (endocrinologist at Autonomous University of Madrid and La Paz University Hospital) and Diana Ovejero (endocrinologist researcher at the Hospital del Mar Medical Research Institute).

Impact

Many benefits could be obtained from the development of mathematical models to aid in biomarker discovery and the development of in silico clinical trials to find optimal therapeutic approaches in FD. They may help to identify patients with potentially limited response, to find the best delivery scheme for the therapy minimizing rebound effects, or to extrapolate to large patient groups the results obtained in a small number of patients. A relevant use of mathematical models in FD is their ability to describe the patient’s response to treatments in silico, so that they can be used as test beds for different treatment schedules.

Funded by

Sponsors

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

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