RFPs: End User-Driven Application of Generative Artificial Intelligence Models in Healthcare

Aims

• This topic aims at supporting activities that are enabling or contributing to one or several expected impacts of destination “Ensuring equal access to innovative, sustainable, and high-quality healthcare”.

Scope

• This topic will contribute to advancing and generating research to better understand and improve Generative AI-based virtual assistant solutions and their applicability in healthcare settings by improving patient health outcomes, fostering personalised healthcare and support the resilience, sustainability, and efficiency of the healthcare systems. In addition, the topic aims to also cover the understanding and mitigation of possible shortcomings (biases) and frameworks for monitoring and overseeing these solutions’ use.
• Research actions under this topic should include all the following activities, ensuring multidisciplinary approaches and a broad representation of stakeholders in the consortia (e.g. industry, academia, healthcare professionals, patients):
  • Develop virtual assistant solutions based on new or optimised trustworthy and ethical Generative AI models, augmented by other AI tools to support healthcare professionals. The models should leverage extensive and diverse multimodal health and research data, public knowledge, and reliable healthcare systems information relevant for healthcare settings. Examples can include electronic health records, medical imaging, genomics, proteomics, molecular data, laboratory results, patient information (including on safety), and/or unstructured health data (the applicants may choose any type of available large-scale data). The development and training of the models should take place in multinational consortia and federated governance approaches should be considered. The applicants should demonstrate how the project goes beyond combining existing data and generates new specific knowledge to improve clinical decision making.
  • Demonstrate the added-value and clinical utility of the virtual assistant solutions in at least two healthcare use cases in different medical fields and unmet needs showing e.g. improved care management and efficiency, prediction of potential patient-specific therapeutic strategies and outcomes, etc. The applicants should provide evidence of high maturity technology for the use cases and assess the relative effectiveness of the solutions compared with standard of care, including on why these solutions would be superior to other AI tools and would deliver better outcomes. They should actively engage healthcare professionals as end users, and other stakeholders such as patients, caregivers in the development and testing of the solutions, ensuring that diverse perspectives and intersectional considerations are integrated throughout the process. Training and education activities for healthcare professionals should be organised.
  • Develop a regulatory strategy/interaction plan with regulators (including in the area of Health Technology Assessment) for generating evidence, where relevant, in a timely manner. Consider also the potential for future regulatory impact of the results and sustainability aspects.
  • Develop or adapt existing methodologies for continuous assessment of the developed solutions. The methodologies should demonstrate technical robustness, healthcare utility and trustworthiness of the Generative AI-based solutions, by adopting:
    • Appropriate metrics for evaluating alignment with human values, ethical principles and the intended purposes of Generative AI models, performance including testing their technical robustness and clinical utility, as well as their model intelligibility, in view of ensuring AI trustworthiness.
    • Appropriate solutions to identify and mitigate potential bias of the models (e.g. representativeness of the data, bias of the trainer, bias of training and validation data, algorithmic discrimination and bias including gender bias etc.).
    • Appropriate techniques to discover and demonstrate explainability of model reasoning, increase users’ trust, and address the black box element, thus further enhancing transparency, model explainability and alignment.
    • Methods to systematically address and assess ELSI (Ethical, Legal and Societal Implications), including data privacy concerns and risk of discrimination/bias (not limited to sex, gender, age, disability, race or ethnicity, religion, belief, minority and/or vulnerable groups). The implication of medical errors originated from AI-assisted decision-making and the effects on potential legal liability for healthcare professionals should be explored.
  • All proposals should demonstrate EU added value by focusing on the development and/or use of trustworthy Generative AI models developed in the EU and Associated countries, involving in the consortium EU industrial developers, including leading-edge startups when possible. An open-source approach is encouraged when technically and economically feasible. Successful proposals are encouraged to utilise the resources offered by the AI factories, when relevant and in accordance with the specific access terms and conditions.

Funding Information

• Budget (EUR) -Year 2025: 40 000 000
• Contributions: 15000000 to 20000000

Expected Outcomes

• Proposals under this topic should aim to deliver results directed towards and contributing to all the following expected outcomes:
  • Healthcare professionals, at all stages of healthcare provision, have access to user-centric, robust and trustworthy virtual assistant solutions based on Generative Artificial Intelligence (AI)models and other AI tools to support them towards the provision of safer, more efficient and personalised care.
  • Healthcare professionals benefit from cross-country applicable methodologies with the aim to facilitate acceptability, healthcare uptake and public trust of virtual assistant tools based on Generative AI models.
  • Patients benefit from enhanced outcomes, more personalised care, and increased engagement with their healthcare professionals, leading to improved safety, quality of care, access to appropriate healthcare information and patient-doctor communication.
  • Healthcare systems benefit from improved cost-effective patient outcomes, superior to standard of care in terms of accuracy, safety, and quality, and from cost-savings through advancements in highly accurate, transparent, traceable, and explainable solutions.

Eligibility Criteria

• Entities eligible to participate:
  • Any legal entity, regardless of its place of establishment, including legal entities from nonassociated third countries or international organisations (including international European research organisations) is eligible to participate (whether it is eligible for funding or not), provided that the conditions laid down in the Horizon Europe Regulation have been met, along with any other conditions laid down in the specific call/topic.
  • A ‘legal entity’ means any natural or legal person created and recognised as such under national law, EU law or international law, which has legal personality and which may, acting in its own name, exercise rights and be subject to obligations, or an entity without legal personality.
• To become a beneficiary, legal entities must be eligible for funding.
• To be eligible for funding, applicants must be established in one of the following countries:
  • the Member States of the European Union, including their outermost regions:
    • Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden.
  • the Overseas Countries and Territories (OCTs) linked to the Member States:
    • Aruba (NL), Bonaire (NL), Curação (NL), French Polynesia (FR), French Southern and Antarctic Territories (FR), Greenland (DK), New Caledonia (FR), Saba (NL), Saint Barthélemy (FR), Sint Eustatius (NL), Sint Maarten (NL), St. Pierre and Miquelon (FR), Wallis and Futuna Islands (FR).
  • countries associated to Horizon Europe;
    • Albania, Armenia, Bosnia and Herzegovina, Canada, Faroe Islands, Georgia, Iceland, Israel, Kosovo, Moldova, Montenegro, New Zealand, North Macedonia, Norway, Serbia, Tunisia, Türkiye, Ukraine, United Kingdom.

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