AI Industry Connect Talks | Purposeful

Continuing our series of monthly business talks titled AI Industry Connect Talks in February we hosted Dr George Drakakis, CEO of Purposeful. The talk was online on Wednesday 16 February 2022 at 14.00.

Talk title: Purposeful: In silico drug repurposing for the treatment of rare diseases

Talk description: There are approximately 7000 rare diseases, 95% of which do not have a known cure or treatment. De novo drug discovery timelines are estimated to be between 12 and 15 years, while development costs are insurmountable. This is where drug repurposing can prove useful. With the use of computational models, we are able to derive promising candidates for many diseases, from the pool of drugs already on the market. In this presentation, we will discuss the workflow, challenges faced and the future needs of Purposeful.

Short bio: Dr Georgios Drakakis is the CEO of the in silico drug repurposing company Purposeful, focused on finding treatments for rare diseases. His research interests include machine learning, data mining, machine vision, as well as chemo- and bioinformatics. After obtaining the EPSRC Doctoral Prize, Dr. Drakakis worked as a research associate for a combined 3.5 years at the National Technical University of Athens and the University of Cambridge. He has recently co-authored 15 research publications in these fields and contributed to 2 book chapters.


The AI Industry Connect Talks series was launched in March 2021 by SKEL | The Artificial Intelligence Lab, Institute of Informatics & Telecommunications at NCSR Demokritos and is supported by ahedd Digital Innovation Hub. Through this series of talks, we aim to bring AI innovation to the forefront and inform wider audiences of the endless possibilities. Domain professionals tell us how the Industry applies scientific results in real-life.

A Q&A session follows the presentations. The sessions are live-streamed via Zoom and on YouTube.

[See all previous talks in the dedicated webpage here – [Marine Traffic, Contexity, Causaly, Atypon, LifebitJADBioElsevierQualcoBehavioral Signals, SCiFY]

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