Periodic Reporting for period 1 - LEOPARD (Liver Electronic Offering Platform with Artificial intelligence-based Devices)
Berichtszeitraum: 2023-11-01 bis 2025-04-30
Liver transplantation (LT) is a life-saving procedure for decompensated cirrhosis (DC) and hepato-cellular carcinoma (HCC). Its efficacy is hampered by the risk of death/drop-out on the Wait List (WL). This risk is driven by organ shortage and is mitigated by organ offering schemes. According to a sickest first policy, offering schemes prioritize LT candidates with the highest risk of dying, as assessed by predictive models. To drive allocation, Organ Sharing Organizations (OSOs) use a 20-year-old model, the MELD, predicting mortality in DC but not in HCC. Because of a dramatic increase in % of HCC candidates (40% vs 10% in early 20ties), MELD schemes are increasingly inaccurate, with persisting 15 to 30% mortality in countries with low/medium donation rate. This scenario, together with advances in prognosis in DC and HCC candidates and statistics, prompts LT community to look for new algorithms to refine offering schemes. To address this issue, key European LT stakeholders including OSOs, LT experts, Statisticians, Research Labs and SME joined LEOPARD. LEOPARD propose to design and validate an AI-based LEOPARD predictive algorithm outperforming current allocation MELD-based models by better stratifying patients on the risk of mortality, to be proposed OSOs to drive allocation as well as LEOPARD calculators available for professional for assistance in complex decision-making processes. We expect that these computational tools improve candidates’ outcomes, with more patients transplanted on time and significant reduction in the risk of death on the WL. Also, adoption of LEOPARD tools should result in harmonization of European heterogeneous prioritization schemes, and in a significant reduction in disparities of access to LT, a major objective pointed out by the European Commisssion. LEOPARD should place Europe in leading position for organ offering schemes.
LEOPARD project first identified a set of variables with potential predictive value that will serve as the foundation for training advanced first-generation AI-based predictive models. These include both routinely collected data from national OSO systems and a set of additional, clinically relevant variables selected by expert clinicians. Two tailored datasets were created: one for patients with DC and other end-stage liver diseases, and another for patients with HCC in order to obtain clinical predictors relevant to each patient population.
A major milestone was the launch of the Training and Validation Data Collection Study (TVDCS – NCT06675604). This prospective, multicenter European study includes two sub-cohorts:
• A training cohort used to develop second-generation predictive models.
• A validation cohort used to test the performance of these models under real-world conditions.
Between February and June 2025, data were collected from patients across five countries (France, Italy, Germany, Belgium, and Austria), with 22 centers active and >120 patients already enrolled. Study launch in Spain and the Netherlands is expected by September 2025 to enroll patients from 65 transplant centres in 7 countries.
In parallel, a second clinical study, PVC1 (NCT06723275) has been prepared. This study provides an independent external validation of the LEOPARD models while supporting the integration of cutting-edge omics and radiomics data to shape the development of third-generation models. The clinical protocol and all regulatory documentation have been finalized. Ethics submission has been completed in France and is scheduled for September in the remaining participating countries. Dedicated electronic Case Report Forms (eCRFs) and harmonized data infrastructure are already in place.
To ensure secure and consistent data collection across all LEOPARD activities, a pseudonymized identifier system has been developed, allowing tracking of patient data without storing any personally identifiable information. All data flows, are securely encrypted and managed. Access is restricted and monitored through rigorous audit mechanisms.
The project also established a dedicated LEOPARD Imaging Repository, designed to centralize and harmonize imaging data collected from participating centers.
From an operational perspective, LEOPARD has achieved solid governance and coordination:
• A Scientific Advisory Board was set up, providing strategic insight and enhancing scientific direction.
• A strong coordination structure has supported effective collaboration across partners and work packages.
• Key milestones have been reached, and core deliverables were submitted on time, reflecting successful project implementation.
In line with its commitment to equity and inclusion, the project launched a Gender and Diversity Monitoring Framework. This initiative tracks relevant indicators and promotes inclusive participation in all project activities.
Overall, LEOPARD has laid a robust foundation for its scientific and technological goals. It has successfully initiated a major study, developed key digital infrastructures, and ensured regulatory preparednress for the launch of the second study. The work conducted to date sets the stage for upcoming breakthroughs in AI-driven liver transplant prioritization, with the potential to impact clinical practice and health policy across Europe.
A major milestone was the launch of the Training and Validation Data Collection Study (TVDCS – NCT06675604). This prospective, multicenter European study includes two sub-cohorts:
• A training cohort used to develop second-generation predictive models.
• A validation cohort used to test the performance of these models under real-world conditions.
Between February and June 2025, data were collected from patients across five countries (France, Italy, Germany, Belgium, and Austria), with 22 centers active and >120 patients already enrolled. Study launch in Spain and the Netherlands is expected by September 2025 to enroll patients from 65 transplant centres in 7 countries.
In parallel, a second clinical study, PVC1 (NCT06723275) has been prepared. This study provides an independent external validation of the LEOPARD models while supporting the integration of cutting-edge omics and radiomics data to shape the development of third-generation models. The clinical protocol and all regulatory documentation have been finalized. Ethics submission has been completed in France and is scheduled for September in the remaining participating countries. Dedicated electronic Case Report Forms (eCRFs) and harmonized data infrastructure are already in place.
To ensure secure and consistent data collection across all LEOPARD activities, a pseudonymized identifier system has been developed, allowing tracking of patient data without storing any personally identifiable information. All data flows, are securely encrypted and managed. Access is restricted and monitored through rigorous audit mechanisms.
The project also established a dedicated LEOPARD Imaging Repository, designed to centralize and harmonize imaging data collected from participating centers.
From an operational perspective, LEOPARD has achieved solid governance and coordination:
• A Scientific Advisory Board was set up, providing strategic insight and enhancing scientific direction.
• A strong coordination structure has supported effective collaboration across partners and work packages.
• Key milestones have been reached, and core deliverables were submitted on time, reflecting successful project implementation.
In line with its commitment to equity and inclusion, the project launched a Gender and Diversity Monitoring Framework. This initiative tracks relevant indicators and promotes inclusive participation in all project activities.
Overall, LEOPARD has laid a robust foundation for its scientific and technological goals. It has successfully initiated a major study, developed key digital infrastructures, and ensured regulatory preparednress for the launch of the second study. The work conducted to date sets the stage for upcoming breakthroughs in AI-driven liver transplant prioritization, with the potential to impact clinical practice and health policy across Europe.
LEOPARD is the first European initiative to develop AI tools for liver transplant decisions using data collected and tested in real-life conditions which opens the door for AI and machine learning to be used safely and effectively in healthcare decision-making.
If these new prediction tools prove to work well, they could be adopted by national Organ Sharing Organizations (OSOs) across Europe and support clinicians to make better decisions, improve survival chances for patients, and ensure fairer access to transplants regardless of country or hospital.
To make sure these tools can be used widely, we still need to:
• Run multi-country pilot studies to test model adoption in routine clinical practice and OSO decision-making workflows.
• Implement regulatory and standardization frameworks to facilitate the integration of AI tools into national transplant systems, ensuring compliance with GDPR.
• Access to financial support for the extension to non-EU countries, the sustainability and potentially commercialization of software tools and training modules developed within LEOPARD.
If these new prediction tools prove to work well, they could be adopted by national Organ Sharing Organizations (OSOs) across Europe and support clinicians to make better decisions, improve survival chances for patients, and ensure fairer access to transplants regardless of country or hospital.
To make sure these tools can be used widely, we still need to:
• Run multi-country pilot studies to test model adoption in routine clinical practice and OSO decision-making workflows.
• Implement regulatory and standardization frameworks to facilitate the integration of AI tools into national transplant systems, ensuring compliance with GDPR.
• Access to financial support for the extension to non-EU countries, the sustainability and potentially commercialization of software tools and training modules developed within LEOPARD.