The neurodegeneration research community remembers the major outcome of the AETIONOMY project funded by the Innovative Medicine Initiative . The project delivered the basis for the generation of mechanism-based taxonomies for neurodegenerative diseases; major achievements of this project were the mechanism-enrichment server NeuroMMSig and the demonstration that mechanism-based stratification of Alzheimer patients is possible (Khanna, S., et al.,. (2018).
Using multi-scale genetic, neuroimaging and clinical data for predicting alzheimer’s disease and reconstruction of relevant biological mechanisms. Scientific reports, 8(1), 1-13.). Not known to a wider community is the fact that teams at Fraunhofer have worked on a knowledge graph representing the majority of interactions of drugs with the pathophysiology mechanisms underlying Alzheimer´s disease. This knowledge graph is part of the “Human Brain Pharmacome”, a comprehensive model of Alzheimer´s disease pathophysiology mechanisms and their drug-target relationships. On June 9, 2021, the teams will introduce the Human Brain Pharmacome to the community.
PHARMACOMEs are way to represent complex biological, chemical and pharmaceutical data and knowledge in a structured, searchable and interpretable form. PHARMACOMEs thus integrate relevant data and knowledge about biological processes, pathophysiology mechanisms and the known chemistry that modulates both. PHARMACOMEs also allow modelling these known modulations in order to predict future compounds as candidate novel modulators.
The purpose of the symposium is to introduce the PHARMACOME concept and to highlight the utility of this specialised knowledge graph for the identification of druggable pathophysiology mechanisms. The 1st Fraunhofer Symposium on PHARMACOMEs will focus on the use of a dedicated graph model, the Human Brain PHARMACOME, in target- and candidate drug- identification. We will provide an overview on:
- Using information extraction technologies (on scientific publications and patents),
“text-2-graph” technologies and dynamic data fusion for PHARMACOME generation
- Applying AI-based network algorithms and BiKMi, a dedicated PHARMACOME user interface,
to identify pathophysiology mechanisms that are suitable for targeting
- Development of novel strategies for high throughput and high content screening & experimental validation of in silico hypotheses
- Provide a walkthrough on a well-defined example in the Alzheimer research context
(here: targeting the regulation of post-translational modification of TAU)
- Using PHARMACOMEs for future drug targeting and drug repurposing approaches
(e.g. proximity drug strategies)
- Computational biologists and computational chemists
- Pharmaceutical industry and biotech technology scouts
- AI experts involved in target discovery and drug development
- Biochemical and cellular assay specialists from industry and academia
Visit this page to register for the event: https://www.scai.fraunhofer.de/en/events/mavo_symposium.html