Development of an Artificial Intelligence Model for Optimising Therapy in Gliomas Gliomas
Artificial intelligence (AI) undoubtedly represents the main tool currently available in the definition of complex algorithms and its use in the medical field is becoming increasingly strategic.As reported in the literature, it is increasingly difficult to find new therapeutic strategies for neoplasms, especially neuro
| Condition(s) | Glioma |
|---|---|
| Status | Recruiting |
| Study type | Observational |
| Summary | Artificial intelligence (AI) undoubtedly represents the main tool currently available in the definition of complex algorithms and its use in the medical field is becoming increasingly strategic.As reported in the literature, it is increasingly difficult to find new therapeutic strategies for neoplasms, especially neurological ones. Molecular characterisation is therefore increasingly essential, as is the use of new predictive methods. With this in mind, the aim of this study is to assess, by means of AI algorithms applied to genomic data, in what percentage molecular alterations are susceptible to potential drug therapies, compared to the literature data that does not consider AI algorithms for this purpose. |
| Who can participate | Inclusion Criteria: 1. Patients with a histopathological diagnosis of glioma for whom it is possible to have cryopreserved or fixed in formalin and embedded in paraffin biological material. Specimens may result from incisional biopsy and/or surgical resection and/or blood. Whole blood is taken for germinal analysis; 2. Age \>=18 years; 3. Patients must understand and provide written informed consent; 4. Life expectancy \>3 months; 5. Presence of biological material from resection and blood considered sufficient by quality and quantity to proceed to molecular characterisation in the opinion of the Investigator Principal Investigator; 6. Presence of available and accessible clinical and histopathological data. Exclusion Criteria: 1. Refusal of informed consent; 2. Uncooperative patients; 3. |
| Ages | 18 Years |
| Sex | All |
| Lead sponsor | Centro di Riferimento Oncologico - Aviano |
| Locations | Aviano, Pordenone, Italy; Padova, Italy; Udine, Italy |
| Start date | 2023-11-16 |
| NCT ID | NCT06620055 |
| Official listing | https://clinicaltrials.gov/study/NCT06620055 |