Term: 01/2021-12/2024 (48 Monate)

Partner: H2020-MSCA-ITN-2020
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH) (Coordinator) et al.

Topic:

The AIDD will develop innovative AI methods by combining theoretical expertise of academic partners with access to large volumes of valuable proprietary data and outstanding medicinal and synthetic chemistry domain expertise of the industrial partners. The project brings together the scientific expertise and resources of three large european pharma companies and academic partners with deep domain knowledge of computational drug design. Until now, this has been very difficult because of Intellectual property (IP) restrictions and resulting conflicts of interest and restrictions on dissemination characteristic of industry funded collaborations.

The AIDD for the first time overcomes these restrictions by making all methodological developments available as open source. This will allow the widest possible dissemination of the project results to different target audiences, including SMEs. Dissemination will be also via publications in high impact journals, presentations at major scientific meetings and conferences, newsletters, open schools, professional networks, blogs, online lectures and courses, as well as public engagement via Open Days, public lectures to high schools and universities.

The AIDD will include an innovative education program in the use of AI for chemical and biological data analysis. The project leverages a new curriculum that is introduced as a part of MSc programs at academic partners. AIDD will extend this educational program to include not only medicinal chemistry but also multidisciplinary and intersectoral areas such as material informatics, computational toxicology, agrochemistry, synthetic chemistry, biomaterials and other areas.

The AIDD will provide structured training to its fellows through a combination of online courses and schools thus strengthening European innovation capacity in the education of specialists in AI methods. Since the research program is tightly coupled with the target users - large pharma companies and SMEs - it provides a clear path for technology transfer from academia to industry. The fellows will get comprehensive training in transferable skills.

The network PIs are experienced scientific leaders. Collectively they received six ERC grants, and have about 60k citations in 2019 only, coordinated multiple Horizon2020 projects (including MSC EID), represent top world-wide universities and were awarded multiple national and international prizes. They have supervised hundreds of PhDs, postdocs, staff scientists and talented early career entrepreneurial scientists (“young tigers”) who have established their own research groups or companies (e.g., DeepMind). PhD committees composed of industrial and academic partners, joint schools, and common research topics will stimulate cross- and intersectoral interactions between industrial partners, SMEs and academic organizations in doctoral and research training.