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Aladdin Healthcare Technologies completes Biomedical Knowledge Graph for Commercial use In Drug Development

DGAP-News: Aladdin Healthcare Technologies SE / Key word(s): Product Launch Aladdin Healthcare Technologies completes Biomedical Knowledge Graph for Commercial use In Drug Development 21.09.2020 / 09:00 The issuer is solely responsible for the content of this announcement.

Aladdin Healthcare Technologies completes Biomedical Knowledge Graph for Commercial use In Drug Development

- Proprietary Knowledge Graph 'PharmaKG' released as Software As A Service (SAAS)

- PharmaKG makes key findings of potential drug candidates visible

- PharmaKG identifies target molecules, pathological causalities and new fields of application for drugs

- Great interest from customers in the USA, China and Norway

BERLIN/LONDON, September 21, 2020 - Aladdin Healthcare Technologies SE ("Aladdin", ISIN: DE000A12ULL2), a leading developer of Artificial Intelligence (AI) based healthcare diagnostics and drug discovery applications, has successfully released its proprietary biomedical knowledge graph 'PharmaKG' as SAAS ( Software As A Service).

PharmaKG has been used by Aladdin and its partners to process biomedical knowledge and reasoning, to accelerate the discovery of artificial intelligence (AI) drugs. The PharmaKG allows to uncover key findings, mechanisms of action and potential drug candidates by revealing essential relationships between diseases, genes, chemical compounds or drugs. The Pharma Knowledge Graph offers key functions such as the identification of target molecules, the discovery of pathological causalities, the analysis of mechanisms and the repurposing of drugs to new fields of application.

Wade Menpes-Smith comments: "Aladdin's knowledge graphs help to discover new disease patterns and viral mechanisms to accelerate drug development in collaboration with pharmaceutical companies. Customers from China, the USA and Norway are already showing strong interest in the PharmaKG".
A knowledge graph is a graph-structured knowledge database, where facts are represented in the form of relationships between and from different data providers. In a knowledge graph, entities (nodes) are related to each other by means of the so-called edges and are contextualized thematically. Aladdin's AI team, through the use of advanced text mining techniques, was able to extract biomedical knowledge from over 30 million research articles and to construct a large scale knowledge graph with more than 800 thousand entities and over 10 million edges among diseases, targets, compounds, biomarkers and genes.