AI-Powered Signal Detection in Pharmacovigilance

The main goal of this opportunity is to improve drug safety by using artificial intelligence (AI) to detect adverse drug reactions more quickly and accurately. It focuses on proactive risk management and aims to make patient safety decisions faster and more reliable. Key areas include evaluating and optimizing AI algorithms for signal detection, ensuring transparency and trustworthiness in AI-driven decisions, and encouraging collaboration among stakeholders. It is part of the Horizon Europe program and supports research and innovation in pharmacovigilance.

• Projects must focus on AI-powered signal detection in pharmacovigilance.
• Proposals must evaluate or optimize AI algorithms for identifying adverse drug reactions.
• Projects should address transparency and trust in AI decision-making.
• Collaboration between different stakeholders is encouraged.
• Proposals must be submitted within the specified page limits (20 pages for short proposals at stage 1, 50 pages for full proposals at stage 2).
• Applicants from the UK and Canada are not eligible for funding.

Examples:

• A project that develops a new AI model to detect rare adverse drug reactions using large-scale health data.
• A collaboration between hospitals and technology companies to improve the reliability and transparency of AI-driven pharmacovigilance systems.
• An initiative to create open-source tools for evaluating the trustworthiness of AI algorithms used in drug safety monitoring.

Expenses that are directly envolved in this project are considered eligible. There is not a specific set of eligibile expenses for this call.

• Total budget of the grant: €8,825,000. Applicants must include a 45% industry contribution in their budget. Entities from the UK and Canada are not eligible to receive funding for this topic.

• Applicants must be established in countries listed as eligibile countries
• Applicants must not be legal entities from the UK or Canada.
• Applicants must adhere to ethical and legal principles, including trustworthy AI frameworks such as ALTAI.
• Applicants must submit the application in consortium
• The consortium must follow the Triple Helix Innovation Framework (Academia, Industry/Companies, Government)
• Proposals must be submitted according to the call management rules and page limits.
• Applicants must follow the conditions described in the IHI JU Work Programme.