The PRE-PDAC pilot study aims to evaluate the effectiveness of a Polygenic Risk Score (PRS) in predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC)—one of the deadliest cancers due to its typically late diagnosis, limited treatment options, and rapid progression.
The study, carried out in collaboration between Università Cattolica del Sacro Cuore and the IRCCS San Raffaele Hospital, involves both patients with a histological diagnosis of PDAC and healthy control subjects. The PRS, calculated from known genetic variants, is integrated with clinical and behavioral risk factors (such as diabetes and smoking) to build a multifactorial risk stratification model.
The primary objective is to assess the association between the PRS and the likelihood of developing PDAC. Secondary objectives include analysing how certain factors—such as age, sex, tumor characteristics, the presence of specific blood biomarkers (CA19-9 and IL-6), and the type of treatment received—vary across different genetic risk groups.
The pilot study seeks to identify high-risk population subgroups in order to guide targeted interventions and promote personalised surveillance strategies within a precision medicine framework.
Breast cancer is the most common form of cancer among women in Italy. Today, medicine is exploring new tools to improve prevention, such as the use of genetic information.
A pilot study conducted in Rome at the Policlinico Gemelli, in collaboration with the Università Cattolica del Sacro Cuore, involves 510 women to assess whether knowing one’s genetic risk—calculated through a score called the Polygenic Risk Score (PRS)—can help personalise breast cancer prevention.Through a simple blood test, participants will find out whether their DNA contains genetic variants that increase the risk of developing this disease. The results will be integrated with other personal and family risk factors using the CanRisk model, an advanced tool for estimating individual risk.Based on this information, the women will receive personalised prevention advice, such as more frequent screenings or risk-reducing strategies. Researchers will also evaluate how acceptable and useful this approach is in everyday clinical practice.
This study represents an important step toward more personalised medicine, where genetics can support individuals in taking more informed and effective care of their health.
Ovarian cancer is the gynecological malignancy with the highest mortality rate in Europe. Its prognosis is often poor due to several factors, including:
The Polygenic Risk Score (PRS) is an index that measures an individual’s genetic predisposition to developing a specific disease. This score is calculated by analysing thousands of genetic variants associated with the risk of a given condition and can be obtained through a simple blood or saliva sample. The PROVE prospective study, promoted by the Università Cattolica del Sacro Cuore and conducted at the Gemelli University Hospital in Rome, aims to assess the effectiveness of PRS in predicting the genetic risk of developing epithelial ovarian cancer in the Italian population. The study will involve 1,300 women, divided between cases (confirmed cancer) and controls (healthy individuals), all undergoing blood sampling to identify genetic variants necessary for PRS calculation. This approach could represent an innovative prevention strategy. Key potential benefits include:
Heart diseases, such as heart attacks and strokes, are very common and often caused by unhealthy lifestyles, like poor diet, physical inactivity, or smoking. To prevent them, medicine is exploring new ways to motivate people to live healthier lives.A pilot study conducted in Rome on 650 employees of the Gemelli University Hospital aims to understand whether knowing one’s genetic risk—what is written in the DNA—can encourage individuals to adopt healthier lifestyles. The study is coordinated by the Hygiene Section of the Università Cattolica del Sacro Cuore, in collaboration with the Cardiology Department of the Gemelli University Hospital.
Through a blood sample, participants will discover whether they are genetically predisposed to developing cardiovascular diseases. They will then receive personalised advice on nutrition, physical activity, and other healthy habits, based on the guidelines of the European Society of Cardiology (ESC). Researchers will check after six months whether participants have improved their behaviors and cholesterol levels.
This study will help determine whether genetic information can truly motivate individuals to take better care of their health. In the future, this approach could become part of routine medical practice.
The Generation Gemelli pilot project aims to investigate how environmental exposures affecting the mother before and during pregnancy can influence the newborn’s health and development in early childhood. Specifically, the project focuses on two clinically significant conditions: preterm birth and intrauterine growth restriction. The initiative stems from the growing attention to the so-called “first 1000 days” of life, a crucial period during which the foundations for a child’s future health and physical, cognitive, and behavioural development are established.
The study, conducted at the A. Gemelli University Hospital IRCCS, involves the enrolment of mother-newborn pairs, the collection of biological samples (blood, placenta, saliva, meconium), and the administration of a questionnaire on environmental conditions and lifestyle factors. Children are then monitored up to the age of two to assess their growth, nutrition, possible diseases, and the development of psychomotor and social skills.
By integrating clinical, environmental, and biological data, Generation Gemelli aims to provide new scientific evidence to improve prevention strategies and promote targeted interventions from the very earliest stages of life.
The CAREVAX project is an initiative aimed at improving access to vaccinations for vulnerable adult patients, reducing the risk of preventable diseases. Developed in Rome through a collaboration between the Fondazione Policlinico Gemelli IRCCS and ASL RM1, the project leverages digital technologies to automatically identify patients who need vaccinations, enhancing coordination between hospitals and local healthcare services.
How does it work?
An intelligent algorithm analyses patients’ clinical data (such as age, chronic conditions, and treatments) and cross-references it with the Digital Vaccination Registry to determine which vaccines are missing. Eligible patients receive an invitation to get vaccinated, with the option to do so either at the hospital or at ASL centers. The recommended vaccinations include:
Benefits of the CAREVAX model
Personalisation: The algorithm selects only those patients who will truly benefit from vaccination.
Efficiency: It reduces human error and automates an otherwise complex process.
Hospital-to-community integration: It bridges the gap between healthcare facilities, improving care continuity.
Innovation and future vision
CAREVAX serves as a pilot model for digital health, opening new possibilities for the integration of IT advancements and preventive care. The outcomes can inform more effective health policies and support the expansion of this approach to other regions and patient categories.
To deploy an interoperable web-based platform to provide epidemiological and health surveillance against LTBI (Latent Tubercolosis Infection) in the hospital setting.
Tuberculosis (TB) prevention represents a primary objective in both hospital and academic settings. Given the potential progression or reactivation of latent TB infection (LTBI), screening of healthcare workers and medical students is currently a key component of TB control programs.
This ambispective observational pilot study aims to:
Total sample size: 3,503 participants (FPG/UCSC, UNIPA, UNIBA/University Hospital of Bari).
Developing a predictive model for diseases related to heavy metals and nanoparticles, through the identification of a shared clinical and laboratory profile between allergic contact dermatitis and systemic allergic syndrome, along with the investigation of susceptibility biomarkers in a large at-risk population, will enable the assessment of the health effects of exposure to emerging contaminants and the early identification of individuals at risk for metal-related diseases.
Environmental and health data collected will be integrated into a digital platform to support the development of predictive models based on algorithmic approaches.
The target population of the study includes patients with allergic contact dermatitis to metals (Nickel, Chromium, Cobalt, Palladium, Copper, Molybdenum, and Aluminum), patients with systemic allergic syndromes related to metals, at-risk workers, and healthy individuals.
The study will be conducted in multiple phases and will involve the following centers and associations: Fondazione Policlinico Universitario A. Gemelli (FPG), University of Bologna (UNIBO), University of Palermo (UNIPA), Azienda Ospedaliera Universitaria Policlinico di Catania (AOUPCT), and the Regional Environmental Protection Agency – Sicily (ARPA Sicilia).
The primary objective of the EVACS initiative is to include hard-to-reach patients in health communities, in order to enhance vaccination coverage among these population groups. This goal will be achieved by creating an integrated flow system between existing healthcare platforms and the territory, which will aid in identifying these patients.
To accomplish this, ICT systems will be utilized to analyse sentiment about vaccinations on social media and to identify gasp in immunization coverage.
Ultimately, this project will empower and increase engagement among these population groups.
The sample size for the present study could be the identification of tailored vaccination needs for approximately 25% of the hard-to-reach estimated target (15000 to be identified/60000 estimated) and the provision of proper vaccination for the 30% of the identified population.
This project aims to identify early metabolic indicators of gestational diabetes risk using isothermal calorimetry to monitor red blood cell metabolism. By detecting these markers in the first trimester, it enables early intervention through tailored diet and lifestyle changes. The study compares metabolic profiles of high-risk and healthy women to validate this approach, potentially revolutionizing primary prevention of gestational diabetes.
To leverage isothermal calorimetry to monitor red blood cell metabolism and detect early metabolic changes linked to gestational diabetes mellitus, enhancing primary prevention by identifying at-risk individuals for timely interventions.
Sample size: 30 Healthy pregnant women and 30 pregnant women with gestational diabetes.
Liver dysfunctions are on the rise, along with cirrhosis, hepatocellular carcinoma, and the need for liver transplantation.
Currently, there are no specific pharmacological treatments available; management relies primarily on lifestyle interventions.
In this context, secondary and tertiary prevention play a crucial role.
CALIBRE proposes an innovative model of care that integrates clinical practice with digital tools, aiming to promote early diagnosis, slow disease progression, and reduce cirrhosis-related complications. The model includes a professional dashboard and a patient-facing app designed for individuals with advanced MASLD, encouraging lifestyle change through active and informed engagement.
Each day, the patient receives:
When the patient completes at least four challenges per week, they receive a reward, such as a nutritional chart and a recipe, to encourage continued participation. This approach offers ongoing, personalised, and sustainable support, enabling healthcare professionals to more effectively manage chronic liver disease through proactive patient engagement.
The project aims to lay the groundwork for developing a model of integrated healthcare and social care, supported by telemedicine and Artificial Intelligence (AI).
The development of this model will take into account the guidelines provided in the Decalogue for the implementation of national healthcare services through Artificial Intelligence systems.The overall objective is to create an algorithm based on Machine Learning (ML) techniques to predict the length of hospital stay for patients. This model will provide useful insights to help prevent Over-Threshold (OT) hospitalisations and reduce the percentage of Frequent Users (FU) of healthcare services.
The research project involves the development of the predictive system through a retrospective cohort study, based on routinely collected information by hospital staff and provided to the Health Directorate of the Tor Vergata University Hospital (PTV), which is involved in the project.
The model will be developed using data from hospital admissions in the years 2022, 2023, and 2024. The data used will be obtained from Hospital Discharge Records (SDO) and from the Emergency Information Management System (GIPSE).
The stages of the pilot:
The PRE-PDAC pilot study aims to evaluate the effectiveness of a Polygenic Risk Score (PRS) in predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC)—one of the deadliest cancers due to its typically late diagnosis, limited treatment options, and rapid progression.
The study, carried out in collaboration between Università Cattolica del Sacro Cuore and the IRCCS San Raffaele Hospital, involves both patients with a histological diagnosis of PDAC and healthy control subjects. The PRS, calculated from known genetic variants, is integrated with clinical and behavioral risk factors (such as diabetes and smoking) to build a multifactorial risk stratification model.
The primary objective is to assess the association between the PRS and the likelihood of developing PDAC. Secondary objectives include analysing how certain factors—such as age, sex, tumor characteristics, the presence of specific blood biomarkers (CA19-9 and IL-6), and the type of treatment received—vary across different genetic risk groups.
The pilot study seeks to identify high-risk population subgroups in order to guide targeted interventions and promote personalised surveillance strategies within a precision medicine framework.
Breast cancer is the most common form of cancer among women in Italy. Today, medicine is exploring new tools to improve prevention, such as the use of genetic information.
A pilot study conducted in Rome at the Policlinico Gemelli, in collaboration with the Università Cattolica del Sacro Cuore, involves 510 women to assess whether knowing one’s genetic risk—calculated through a score called the Polygenic Risk Score (PRS)—can help personalise breast cancer prevention.Through a simple blood test, participants will find out whether their DNA contains genetic variants that increase the risk of developing this disease. The results will be integrated with other personal and family risk factors using the CanRisk model, an advanced tool for estimating individual risk.Based on this information, the women will receive personalised prevention advice, such as more frequent screenings or risk-reducing strategies. Researchers will also evaluate how acceptable and useful this approach is in everyday clinical practice.
This study represents an important step toward more personalised medicine, where genetics can support individuals in taking more informed and effective care of their health.
Ovarian cancer is the gynecological malignancy with the highest mortality rate in Europe. Its prognosis is often poor due to several factors, including:
The Polygenic Risk Score (PRS) is an index that measures an individual’s genetic predisposition to developing a specific disease. This score is calculated by analysing thousands of genetic variants associated with the risk of a given condition and can be obtained through a simple blood or saliva sample. The PROVE prospective study, promoted by the Università Cattolica del Sacro Cuore and conducted at the Gemelli University Hospital in Rome, aims to assess the effectiveness of PRS in predicting the genetic risk of developing epithelial ovarian cancer in the Italian population. The study will involve 1,300 women, divided between cases (confirmed cancer) and controls (healthy individuals), all undergoing blood sampling to identify genetic variants necessary for PRS calculation. This approach could represent an innovative prevention strategy. Key potential benefits include:
Heart diseases, such as heart attacks and strokes, are very common and often caused by unhealthy lifestyles, like poor diet, physical inactivity, or smoking. To prevent them, medicine is exploring new ways to motivate people to live healthier lives.A pilot study conducted in Rome on 650 employees of the Gemelli University Hospital aims to understand whether knowing one’s genetic risk—what is written in the DNA—can encourage individuals to adopt healthier lifestyles. The study is coordinated by the Hygiene Section of the Università Cattolica del Sacro Cuore, in collaboration with the Cardiology Department of the Gemelli University Hospital.
Through a blood sample, participants will discover whether they are genetically predisposed to developing cardiovascular diseases. They will then receive personalised advice on nutrition, physical activity, and other healthy habits, based on the guidelines of the European Society of Cardiology (ESC). Researchers will check after six months whether participants have improved their behaviors and cholesterol levels.
This study will help determine whether genetic information can truly motivate individuals to take better care of their health. In the future, this approach could become part of routine medical practice.
The Generation Gemelli pilot project aims to investigate how environmental exposures affecting the mother before and during pregnancy can influence the newborn’s health and development in early childhood. Specifically, the project focuses on two clinically significant conditions: preterm birth and intrauterine growth restriction. The initiative stems from the growing attention to the so-called “first 1000 days” of life, a crucial period during which the foundations for a child’s future health and physical, cognitive, and behavioural development are established.
The study, conducted at the A. Gemelli University Hospital IRCCS, involves the enrolment of mother-newborn pairs, the collection of biological samples (blood, placenta, saliva, meconium), and the administration of a questionnaire on environmental conditions and lifestyle factors. Children are then monitored up to the age of two to assess their growth, nutrition, possible diseases, and the development of psychomotor and social skills.
By integrating clinical, environmental, and biological data, Generation Gemelli aims to provide new scientific evidence to improve prevention strategies and promote targeted interventions from the very earliest stages of life.
The CAREVAX project is an initiative aimed at improving access to vaccinations for vulnerable adult patients, reducing the risk of preventable diseases. Developed in Rome through a collaboration between the Fondazione Policlinico Gemelli IRCCS and ASL RM1, the project leverages digital technologies to automatically identify patients who need vaccinations, enhancing coordination between hospitals and local healthcare services.
How does it work?
An intelligent algorithm analyses patients’ clinical data (such as age, chronic conditions, and treatments) and cross-references it with the Digital Vaccination Registry to determine which vaccines are missing. Eligible patients receive an invitation to get vaccinated, with the option to do so either at the hospital or at ASL centers. The recommended vaccinations include:
Benefits of the CAREVAX model
Personalisation: The algorithm selects only those patients who will truly benefit from vaccination.
Efficiency: It reduces human error and automates an otherwise complex process.
Hospital-to-community integration: It bridges the gap between healthcare facilities, improving care continuity.
Innovation and future vision
CAREVAX serves as a pilot model for digital health, opening new possibilities for the integration of IT advancements and preventive care. The outcomes can inform more effective health policies and support the expansion of this approach to other regions and patient categories.
To deploy an interoperable web-based platform to provide epidemiological and health surveillance against LTBI (Latent Tubercolosis Infection) in the hospital setting.
Tuberculosis (TB) prevention represents a primary objective in both hospital and academic settings. Given the potential progression or reactivation of latent TB infection (LTBI), screening of healthcare workers and medical students is currently a key component of TB control programs.
This ambispective observational pilot study aims to:
Total sample size: 3,503 participants (FPG/UCSC, UNIPA, UNIBA/University Hospital of Bari).
Developing a predictive model for diseases related to heavy metals and nanoparticles, through the identification of a shared clinical and laboratory profile between allergic contact dermatitis and systemic allergic syndrome, along with the investigation of susceptibility biomarkers in a large at-risk population, will enable the assessment of the health effects of exposure to emerging contaminants and the early identification of individuals at risk for metal-related diseases.
Environmental and health data collected will be integrated into a digital platform to support the development of predictive models based on algorithmic approaches.
The target population of the study includes patients with allergic contact dermatitis to metals (Nickel, Chromium, Cobalt, Palladium, Copper, Molybdenum, and Aluminum), patients with systemic allergic syndromes related to metals, at-risk workers, and healthy individuals.
The study will be conducted in multiple phases and will involve the following centers and associations: Fondazione Policlinico Universitario A. Gemelli (FPG), University of Bologna (UNIBO), University of Palermo (UNIPA), Azienda Ospedaliera Universitaria Policlinico di Catania (AOUPCT), and the Regional Environmental Protection Agency – Sicily (ARPA Sicilia).
The primary objective of the EVACS initiative is to include hard-to-reach patients in health communities, in order to enhance vaccination coverage among these population groups. This goal will be achieved by creating an integrated flow system between existing healthcare platforms and the territory, which will aid in identifying these patients.
To accomplish this, ICT systems will be utilized to analyse sentiment about vaccinations on social media and to identify gasp in immunization coverage.
Ultimately, this project will empower and increase engagement among these population groups.
The sample size for the present study could be the identification of tailored vaccination needs for approximately 25% of the hard-to-reach estimated target (15000 to be identified/60000 estimated) and the provision of proper vaccination for the 30% of the identified population.
This project aims to identify early metabolic indicators of gestational diabetes risk using isothermal calorimetry to monitor red blood cell metabolism. By detecting these markers in the first trimester, it enables early intervention through tailored diet and lifestyle changes. The study compares metabolic profiles of high-risk and healthy women to validate this approach, potentially revolutionizing primary prevention of gestational diabetes.
To leverage isothermal calorimetry to monitor red blood cell metabolism and detect early metabolic changes linked to gestational diabetes mellitus, enhancing primary prevention by identifying at-risk individuals for timely interventions.
Sample size: 30 Healthy pregnant women and 30 pregnant women with gestational diabetes.
Liver dysfunctions are on the rise, along with cirrhosis, hepatocellular carcinoma, and the need for liver transplantation.
Currently, there are no specific pharmacological treatments available; management relies primarily on lifestyle interventions.
In this context, secondary and tertiary prevention play a crucial role.
CALIBRE proposes an innovative model of care that integrates clinical practice with digital tools, aiming to promote early diagnosis, slow disease progression, and reduce cirrhosis-related complications. The model includes a professional dashboard and a patient-facing app designed for individuals with advanced MASLD, encouraging lifestyle change through active and informed engagement.
Each day, the patient receives:
When the patient completes at least four challenges per week, they receive a reward, such as a nutritional chart and a recipe, to encourage continued participation. This approach offers ongoing, personalised, and sustainable support, enabling healthcare professionals to more effectively manage chronic liver disease through proactive patient engagement.
The project aims to lay the groundwork for developing a model of integrated healthcare and social care, supported by telemedicine and Artificial Intelligence (AI).
The development of this model will take into account the guidelines provided in the Decalogue for the implementation of national healthcare services through Artificial Intelligence systems.The overall objective is to create an algorithm based on Machine Learning (ML) techniques to predict the length of hospital stay for patients. This model will provide useful insights to help prevent Over-Threshold (OT) hospitalisations and reduce the percentage of Frequent Users (FU) of healthcare services.
The research project involves the development of the predictive system through a retrospective cohort study, based on routinely collected information by hospital staff and provided to the Health Directorate of the Tor Vergata University Hospital (PTV), which is involved in the project.
The model will be developed using data from hospital admissions in the years 2022, 2023, and 2024. The data used will be obtained from Hospital Discharge Records (SDO) and from the Emergency Information Management System (GIPSE).
The stages of the pilot: