SOURCE-LINKED INTELLIGENCE

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

CORDIS · observation · Publication date unknown

ty 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.

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR