CamAIDD

1st Cambridge AI in Drug Discovery Conference
(virtual)

Drug discovery, the process of discovering new medicines or therapies, is on the brink of witnessing a revolution. New machine learning techniques are replacing traditional methods in hypothesis generation, target identification and molecular design which are incredibly costly and time consuming. Billions of dollars of venture capital is getting poured into new startups, large pharmaceutical companies are building inhouse AI capabilities and conventional tech companies are now investing heavily in biology and drug discovery. However, like any new and exciting technology, it remains an open question whether AI will live up to its promises as it passes through the hype cycle and one of the main challenges remains its integration into real world experimental techniques and commercial discovery pipelines.

At this turning point for drug discovery, the 1st Cambridge University AI in Drug Discovery Conference (CamAIDD) will help students, academia and industry alike gain a sense of community and direction in this rapidly changing field. We aim to give a broad yet comprehensive overview of both the bleeding edge scientific research transforming drug discovery as well as glean insights from some of the most innovative entrepreneurs in the field.

Please sign up for the conference by filling out the form below!

Speakers

We invited speakers at the forefront of AI for drug discovery in academia and industry.

Michael Bronstein

Prof Michael Bronstein

Geometric Deep Learning: From Euclid to Drug Design

DeepMind Professor of AI @ Oxford
Head of Graph ML @ Twitter
Scientific Advisor @ Relation Therapeutics

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Sir Tom Blundell

Prof Sir Tom Blundell

Panelist

Prof Emeritus of Biochemistry @ Cambridge
Co-Founder @ Astex Therapeutics
Former President of the UK Science Council

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Andreas Bender

Prof Andreas Bender

AI in Drug Discovery 2022 – Aspects of Translation, Platform Validation, and Where We are on the Hype Cycle

CTO @ Terra Lumina
Professor of Molecular Informatics @ Cambridge

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Petar Velickovic

Dr Petar Veličković

Scientific tool of the 21st century: Introduction to Graph Neural Networks

Staff Research Scientist @ DeepMind
Affiliated Lecturer @ University of Cambridge

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Rabia Khan

Dr Rabia Khan

Talk title tbc

CEO/Founder @ Ladder Therapeutics

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Daniel Jamieson

Dr Daniel Jamieson

Using Cause-and-Effect to Empower Drug Discovery

CEO/Founder @ Biorelate

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Neel Madhukar

Dr Neel Madhukar

Talk title tbc

CEO/Founder @ OneTree Biotech

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Laksh Aithani

Laksh Aithani

Panelist

CEO/Founder @ Charm Therapeutics

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Neel Madhukar

Dr Nathan Benaich

Panelist

Founder and General Partner @ Air Street Capital
Founder @ RAAIS, London.AI and Spinout.fyi
Co-author of State of AI report

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Schedule

All talks will include 5-10 minutes for Q&A at the end.
Times are given in the GMT timezone.

10:00 Welcome address
[Zoom link - Session 1]
10:10 Talk | Petar Veličković

Scientific tool of the 21st century: Introduction to Graph Neural Networks

[Zoom link - Session 1]
10:50
10:50 Talk | Andreas Bender

AI in Drug Discovery 2022 – Aspects of Translation, Platform Validation, and Where We are on the Hype Cycle

[Zoom link - Session 1]
11:30
11:30 Break | 20 min
11:50 Talk | Michael Bronstein

Geometric Deep Learning: From Euclid to Drug Design

[Zoom link - Session 2]
12:30
12:30 Talk | Rabia Khan

Title TBA

[Zoom link - Session 2]
13:10
13:10 Break | 50 min
14:00 Talk | Neel Madhukar

Title TBA

[Zoom link - Session 3]
14:40
14:40 Talk | Daniel Jamieson

Using Cause-and-Effect to Empower Drug Discovery

[Zoom link - Session 3]
15:20
15:20 Break | 10 min
15:30 Panel | How to start an AI in Drug Discovery company

Rabia Khan, Daniel Jamieson, Neel Madhukar, Laksh Aithani

[Zoom link - Session 4]
16:30
16:30 Panel | Scientific frontiers in AI and Drug Discovery

Tom Blundell, Michael Bronstein, Nathan Benaich

[Zoom link - Session 5]
17:30

Organisers

A joint effort of the Cambridge AI Society, the AI in Medicine Society and the Computational Biology group at Cambridge.

Charlie
Harris

Charlie Harris

PhD student
AI for medicine

Sebastian
Hickman

Seb Hickman

PhD student
AI for environmental risk

Simon
Mathis

Simon Mathis

PhD student
AI for environmental risk

Pretesh
Patel

Pretesh Patel

MB
Medical student

Shreya
Dwarakacherla

Shreya Dwarakacherla

MB
Medical student

Will
Halfpenny

Will Halfpenny

MB
Medical student

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