Sara C. Madeira, LASIGE integrated researcher, coordinates the LASIGE team that is responsible for the work package targeting patient stratification, according to their phenotype assessed all over the disease evolution, in the project BRAINTEASER (BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis) recently funded by H2020.
The team will also participate in other tasks concerning data science/artificial intelligent tasks, as the development of advanced machine learning models to unravel disease mechanisms, predict disease progression, and suggest interventions that can delay disease progression, where patient stratification is key given patient heterogeneity both in Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS), chronic diseases characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, cognitive).
Patients have to manage alternated periods in hospital with care at home, experiencing a constant uncertainty regarding the timing of the disease acute phases and facing a considerable psychological and economic burden that also involves their caregivers. Clinicians, on the other hand, need tools able to support them in all the phases of the patient treatment, suggest personalized therapeutic decisions, indicate urgently needed interventions.
Therefore, Artificial Intelligence is the key to successfully satisfy these needs to: i) better describe disease mechanisms; ii) stratify patients according to their phenotype assessed all over the disease evolution; iii) predict disease progression in a probabilistic, time-dependent fashion; iv) investigate the role of the environment; v) suggest interventions that can delay the progression of the disease.
The project will integrate large clinical datasets with novel personal and environmental data collected using low-cost sensors and apps. Software and mobile apps will be designed to embrace an agile and user-centered design approach, accounting for the technical, medical, psychological, and societal needs of specific users.
BRAINTEASER will implement a system able to guarantee cybersecurity and data ownership to the patients; will provide quantitative evidence of benefits and effectiveness of using AI in health-care pathways implementing a proof-of-concept of its use in a real clinical setting. Procedural requirements that support Software as Medical Device certification will be used involving clinicians and patients stakeholders and producing a set of recommendations for public health authorities. Results will be disseminated accordingly to an open science paradigm under the European Open Science Cloud initiative.
This project is led by Universidad Politécnica de Madrid, involves 6 countries (Portugal, Italy, Spain, Ireland, Belgium, Serbia), 7 Academic and research institutions (LASIGE, iMM, Università degli studi di Torino, Università degli studi di Padova, Fondazione Instituto Nazionali Casimiro Mondino, Universidad Politécnica de Madrid and Servicio Madrileño de Madrid de Salud) and 4 private companies.