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AI3SD Video: Drug Repositioning for COVID-19

AI3SD Video: Drug Repositioning for COVID-19
AI3SD Video: Drug Repositioning for COVID-19
Pandemics, such as Covid-19. are by definition essentially unanticipatable and rapid onset. Features unfortunately incompatible with current industry capabilities in drug discovery. This has led to a large number of studies, both theoretical and experimental to reposition, or reuse an existing drug for Covid-19 therapy. There are some general patterns of success in historical repositioning that point to the most likely strategies for drug repositioning, and also, following some specific data gathering and curation, to point towards specific actionable activities for Covid-19. The presentation will briefly overview drug repositioning as a general strategy, and then the focussed application of core concepts towards the treatment of Covid-19.
Machine Learning, Drug Discovery, COVID-19, Deep Learning, Artificial Intelligence, AI, ML, Machine Intelligence, Scientific Discovery
Overington, John
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Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
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Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Overington, John
3f268478-0c27-41eb-8725-7e2acd050bb4
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Overington, John (2020) AI3SD Video: Drug Repositioning for COVID-19. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom. 01 Jul - 23 Sep 2020. (doi:10.5258/SOTON/P0046).

Record type: Conference or Workshop Item (Other)

Abstract

Pandemics, such as Covid-19. are by definition essentially unanticipatable and rapid onset. Features unfortunately incompatible with current industry capabilities in drug discovery. This has led to a large number of studies, both theoretical and experimental to reposition, or reuse an existing drug for Covid-19 therapy. There are some general patterns of success in historical repositioning that point to the most likely strategies for drug repositioning, and also, following some specific data gathering and curation, to point towards specific actionable activities for Covid-19. The presentation will briefly overview drug repositioning as a general strategy, and then the focussed application of core concepts towards the treatment of Covid-19.

Video
AI3SDOnlineSeminarSeries-1-JPO-010720 - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 1 July 2020
Additional Information: John has had extensive experience in technology driven drug discovery. In his work as CIO at the Medicine Discovery Catapult he leads research projects for developing and applying informatics-based approaches for drug discovery. Prior to this he worked for Benevolent AI where he was involved in the development of novel data extraction and integration strategies, integrating deep learning and other Artificial Intelligence approaches to drug target validation and drug optimisation.
Venue - Dates: AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom, 2020-07-01 - 2020-09-23
Keywords: Machine Learning, Drug Discovery, COVID-19, Deep Learning, Artificial Intelligence, AI, ML, Machine Intelligence, Scientific Discovery

Identifiers

Local EPrints ID: 446448
URI: http://eprints.soton.ac.uk/id/eprint/446448
PURE UUID: 90a9b571-aa1d-4447-a95d-8428bd78d6b5
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 10 Feb 2021 17:32
Last modified: 18 Feb 2021 17:36

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Contributors

Author: John Overington
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan
Editor: Victoria Hooper

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