Post Mortem Meeting on Jan 31st 2020

[mattodd]

As mentioned in #21, we will be having a short one-day meeting on this competition, partly in order to see what went wrong/right, and partly to discuss this area of science in more depth.

This Issue is a place where we can consult on the day's schedule. Please suggest either things or people to be added in.

We'll look into a way to broadcast, e.g. via Zoom for remote attendees like @holeung and @IamDavyG

We'll be financially supporting the meeting (lunch, coffees, no attendance fee) via AI3SD money. If there are any potential sponsors of the meeting, I'd love to know. We can offer some travel reimbursement for student attendees (will start separate issue on this).

Predicting the Activity of Drug Candidates when There is no Target
Friday January 31st 2020
Royal Society of Chemistry, Burlington House, Piccadilly, London, W1J 0BD

10:00 Introduction about OSM and this competition (Mat Todd and Ed Tse)
10:30 Talks from competition entrants @BenedictIrwin (Optibrium)
11:00 Talks from competition entrants @wvanhoorn (Exscientia)
11:30 Talks from competition entrants @gcincilla (Molomics)
12:00 Talks from competition entrants AN Other
12:30 Lunch
13:30 Talks from invited guests Who?
14:00 Talks from invited guests Who?
14:30 Talks from invited guests Who?
15:00 Talks from invited guests Who?
15:30 Closing remarks
16:00 End

[iainmwallace]

Great idea! I would be really interested in what went right
If you are looking for suggestions, perhaps John Overington (https://md.catapult.org.uk/team-member/professor-john-overington/) or Andreas Bender (https://www.ch.cam.ac.uk/person/ab454)

[mattodd]

Draft blurb for flyer/Eventbrite page, in case anyone had any improvements? Will put on Eventbrite page and on a one-page flyer for distribution.

Predicting the Activity of Drug Candidates when There is no Target
10-4, Friday January 31st 2020
The Royal Society of Chemistry, Burlington House, Piccadilly, London, W1J 0BD

This one-day meeting concerns the application of machine learning/artificial intelligence (ML/AI) approaches to the discovery of new drug leads. Specifically the meeting is about cases where the biological target is not clearly established - so-called phenotypic drug discovery.

The meeting centers on a real example - a competition run by Open Source Malaria (OSM), funded by a grant from the EPSRC/AI3SD+ network. Data on active and inactive compounds in one OSM antimalarial series were published online, and anyone was able to submit a model able to predict the actives. The models were judged against a dataset that was kept private, and the winners were asked to use their models to predict novel molecules. These are currently being made in the lab and biologically evaluated, and the results will be reported at the meeting, providing a real-world test, and a complete case study, of the capabilities of ML/AI approaches to accelerate modern drug discovery.

We will hear from some of the eleven competition entrants about how their models were constructed, and will have other presentations on related developments. We hope during this meeting to establish which approaches worked well, which did not, and why. All those interested in the application of ML/AI methods to drug discovery are encouraged to attend.

The meeting is free, but there will be a cap on numbers, meaning first come first served, meaning registration is essential.

Eventbrite page: (coming)
GitHub Repository: https://github.com/OpenSourceMalaria/Series4_PredictiveModel
Contact: (Me or Ed or Sam Kanza)

[mattodd]

Registration now live at https://www.eventbrite.co.uk/e/88690015223
Tweeted at https://twitter.com/AISciNet/status/1215555550244671490
LinkedIn at https://www.linkedin.com/feed/update/urn:li:activity:6621322997397536768/

Flyers are: https://github.com/OpenSourceMalaria/Series4_PredictiveModel/tree/master/Post%20Mortem%20Meeting

Please consider in particular any PhD students who might be working in a relevant area. I'm keen to attract them in.

[mattodd]

Final Schedule is below. All talks will have time for questions.

9:30 Gather at RSC, bring favourite coffee, collect badge.
10:00 Introduction about OSM and this competition (Mat Todd and Ed Tse)
10:25 Talks from competition entrants @IamDavyG (USyd)
10:50 Talks from competition entrants @BenedictIrwin (Optibrium)
11:15 Talks from competition entrants Laksh Aithani (Exscientia)
11:40 Talks from competition entrants @gcincilla (Molomics)
12:05 Talks from competition entrants @holeung (KSU)
12:30 Lunch, with tea/coffee served at 13:15
13:30 Joshua Meyers (Benevolent AI): "DeeplyTough: learning to structurally compare protein binding sites."
14:00 John Overington (Medicines Discovery Catapult): "The AssayNet Project: A Directed Graph of Bioassays."
14:30 Al Dossetter (MedChemica): "Explainable AI for the Medicinal Chemist."
15:00 Maria-Anna Trapotsi (University of Cambridge): "Multitask bioactivity prediction by comparing chemical and cell morphology information"
15:30 Closing remarks
16:00 End