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Benchmarking AI to predict mutagenicity by combing chemical structure and genome-wide mutation data

Project description

AI-driven platform to predict mutagenicity from chemical compounds

Evaluating mutagenicity (the potential of a substance to harm DNA) is vital in drug development to ensure safety. The drug development process is complex, time-consuming and costly. Inadequate assessment of mutagenicity can lead to severe consequences. Effective evaluation can prevent these outcomes and the use of AI and whole genome sequencing can enhance this process. The ERC-funded MUTAPREDICT project aims to create an AI-driven platform that transforms drug development by predicting the mutagenic potential of new chemical compounds. This approach addresses the ethical and economic challenges of traditional animal testing, offering a humane and efficient alternative. The solution accelerates drug development by using advanced whole genome sequencing data while ensuring safety and efficacy.

Objective

Assessing mutagenicity, the capacity of a substance to cause permanent and potentially harmful changes to an organism's DNA, is a pivotal concern in drug development. This assessment is crucial because it helps to predict the carcinogenic potential of new pharmaceuticals, ensuring that they are safe for human use. The importance of evaluating mutagenicity in drug development cannot be overstated. Drugs are designed to interact with biological systems to treat or prevent diseases, but they must do so without causing harmful genetic alterations. The process of developing a new drug involves a complex, time-consuming, and costly sequence of research and testing to ensure efficacy and safety. If mutagenicity is not accurately assessed, the consequences can be severe. Addressing the complexities and limitations associated with assessing mutagenicity in drug development, an innovative approach utilizing artificial intelligence (AI) and whole genome sequencing (WGS) data presents a promising solution. MUTAPREDICT introduces an innovative AI-driven platform designed to revolutionize the field of drug development by accurately predicting the mutagenic potential of new chemical compounds. This platform is set to address the ethical, economic, and temporal challenges associated with conventional animal testing and in vitro analyses, promoting a more humane, cost-effective, and efficient approach to drug safety assessments. Leveraging advanced WGS data, our solution significantly accelerates the drug development process, ensuring both safety and efficacy. Our value proposition encompasses ethical and sustainable drug development by offering a viable alternative to animal testing, thus meeting the growing demands for ethical research practices.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

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(opens in new window) ERC-2024-POC

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Host institution

PRINSES MAXIMA CENTRUM VOOR KINDERONCOLOGIE BV
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Beneficiaries (1)

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