Clinical trial NCT06620055: Development of an Artificial Intelligence Model for Optimising Therapy in Gliomas Gliomas
Official title: Development of an Artificial Intelligence Model for Optimising Therapy in Gliomas
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Glioma
Lead sponsor: Centro di Riferimento Oncologico - Aviano
Sponsor class: OTHER
First posted: 2024-10-01
Enrollment: 164
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: 164 patients with a histopathological diagnosis of glioma

Brief 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.

Detailed description: 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: 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. Presence of other neoplastic diseases in the last 5 years;
4. Pregnant and/or breastfeeding women

Primary outcomes:
measure: proportion of patients, out of total patients number, with molecular characteristics susceptible to potential drug therapies ('druggable') identified using an AI model
timeFrame: 24 months
Secondary outcomes:
Other outcomes:
Locations:
city: Aviano
country: Italy
facility: Centro di Riferimento Oncologico (CRO) di Aviano - IRCCS
state: Pordenone
city: Padova
country: Italy
facility: IOV
city: Udine
country: Italy
facility: Azienda Sanitaria Universitaria Friuli Centrale (ASUFC
Study officials:
affiliation: Centro di Riferimento Oncologico di Aviano (CRO) - IRCCS
name: Giuseppe Toffoli
role: PRINCIPAL_INVESTIGATOR
affiliation: Centro di Riferimento Oncologico di Aviano (CRO) - IRCCS
name: Maurizio Polano
role: STUDY_CHAIR
References: