Development of an Artificial Intelligence Model for Optimising Therapy in Gliomas Gliomas
ConditionGlioma
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorCentro di Riferimento Oncologico - Aviano
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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;
Age >=18 years;
Patients must understand and provide written informed consent;
Life expectancy >3 months;
Disqualifiers
Refusal of informed consent;
Uncooperative patients;
Presence of other neoplastic diseases in the last 5 years;
Pregnant and/or breastfeeding women
Trial population
164 patients with a histopathological diagnosis of glioma
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
proportion of patients, out of total patients number, with molecular characteristics susceptible to potential drug therapies ('druggable') identified using an AI model
proportion of patients, out of total patients number, with molecular characteristics susceptible to potential drug therapies ('druggable') identified using an AI model
Time frame
24 monthsSponsors and contacts
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Source ClinicalTrials.gov