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AI3SD Video: A vision of Medicinal Chemistry for the future

AI3SD Video: A vision of Medicinal Chemistry for the future
AI3SD Video: A vision of Medicinal Chemistry for the future
Historically, medicinal chemistry and computational chemistry have been separate roles within a drug discovery organization requiring differing backgrounds and expertise. Increasingly in the modern world and going forwards these skillsets are coming closer and closer together, empowered by automation and increasingly advanced computational methods. Over time, there has been an increase in the amount of time a medicinal chemist spends at a computer compared with time in the lab which is expected to continue. For computational chemists, historically, the core skills were of computer science, not of chemistry due to the lack of well developed tools and computing power. As time goes on, with increases in the user friendliness of available tools and increases in automation, these roles are likely to move closer together, with others joining the field with more mixed skillsets too. The role of automation will likely increase allowing for easier synthetic tasks to be carried out by robots, and the more trivial thinking tasks to be carried out by a computer, leaving human scientists to perform more challenging laboratory work, and think about the most important problems. This presentation will discuss the likely necessary skills of the future, compared to those of today, and the role automation has to play in this transition.
AI, AI3SD Event, Artificial Intelligence, Chemistry, Machine Learning, Medicinal Chemistry
Vidler, Lewis
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Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
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Vidler, Lewis
7b3f826f-5a30-4688-9834-9cdec99ac6b9
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f

Vidler, Lewis and Frey, Jeremy G. (2021) AI3SD Video: A vision of Medicinal Chemistry for the future. Kanza, Samantha and Niranjan, Mahesan (eds.) AI3SD Autumn Seminar Series 2021. 13 Oct - 15 Dec 2021. (doi:10.5258/SOTON/AI3SD0167).

Record type: Conference or Workshop Item (Other)

Abstract

Historically, medicinal chemistry and computational chemistry have been separate roles within a drug discovery organization requiring differing backgrounds and expertise. Increasingly in the modern world and going forwards these skillsets are coming closer and closer together, empowered by automation and increasingly advanced computational methods. Over time, there has been an increase in the amount of time a medicinal chemist spends at a computer compared with time in the lab which is expected to continue. For computational chemists, historically, the core skills were of computer science, not of chemistry due to the lack of well developed tools and computing power. As time goes on, with increases in the user friendliness of available tools and increases in automation, these roles are likely to move closer together, with others joining the field with more mixed skillsets too. The role of automation will likely increase allowing for easier synthetic tasks to be carried out by robots, and the more trivial thinking tasks to be carried out by a computer, leaving human scientists to perform more challenging laboratory work, and think about the most important problems. This presentation will discuss the likely necessary skills of the future, compared to those of today, and the role automation has to play in this transition.

Video
AI3SDAutumnSeminar-171121-LewisVidler - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 24 November 2021
Additional Information: Lewis Vidler is a principal research scientist in computational medicinal chemistry at UCB, based in the UK. He completed an MChem Chemistry degree at the University of Oxford specializing in synthetic organic chemistry, followed by a PhD at the Institute of Cancer Research (ICR) in applied computational chemistry. After he finished his PhD he joined Eli Lilly and Company initially as a contractor before progressing to Senior Research Scientist and has primarily worked on active drug discovery projects in that time. For the past 17 months he has been working at UCB continuing to apply computational methods to drive drug discovery projects forward. Outside of direct project support he has significant interest in automating aspects of drug discovery and empowering others with data analytics tools.
Venue - Dates: AI3SD Autumn Seminar Series 2021, 2021-10-13 - 2021-12-15
Keywords: AI, AI3SD Event, Artificial Intelligence, Chemistry, Machine Learning, Medicinal Chemistry

Identifiers

Local EPrints ID: 453340
URI: http://eprints.soton.ac.uk/id/eprint/453340
PURE UUID: 38f0f331-eda7-4654-9512-092324fe8792
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

Catalogue record

Date deposited: 13 Jan 2022 17:42
Last modified: 14 Jan 2022 02:53

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Contributors

Author: Lewis Vidler
Author: Jeremy G. Frey ORCID iD
Editor: Samantha Kanza ORCID iD
Editor: Mahesan Niranjan ORCID iD

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