https://www.youtube.com/watch?v=gcgeTVfiVl4&ab_channel=AI4ScientificDiscovery Interview: Dr Wendy Warr interviewed John prior to this seminar. This interview can be found here: https://eprints.soton.ac.uk/441804/ Abstract: Pandemics, such as Covid-19. are by definition essentially unanticipatable and rapid onset. Features…
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.
In March 2020, right before our world got turned upside down and we went into lockdown, we managed to hold our big joint Network Conference: AIReact2020 in the beautiful setting…
This is a joint meeting between the Dial-a-Molecule, Directed Assembly and AI3SD (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) Networks. The meeting will examine the state of the art and future opportunities in the use of Artificial Intelligence to predict the outcome of unknown chemical reactions, and consequently design optimum synthetic routes to desired molecules. A wide variety of AI approaches will be illustrated including expert systems, statistical methods, mechanism based and Machine Learning. The meeting will also consider: Data sourcing, sharing, and quality. Automated experimentation to generate reaction knowledge. Theoretical calculations to enrich or replace experimental data. The meeting will include talks to introduce the breadth of the area to all participants. Discussion sessions and opportunities to develop collaborations will be a key aspect of the meeting.
Back in January 2019 AI3SD announced their first funding call. We funded 3 pilot projects, and one of the successful applicants of this funding call was Professor Mat Todd from…
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. Lunch will be provided as part of this event. GitHub Repository: https://github.com/OpenSourceMalaria/Series4_PredictiveModel
In November 2019 AI3SD held their first annual conference to mark the end of the first year of the Network. A full report on this event has been written by…
We are the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery). The network+ is funded by EPSRC and hosted by the University of Southampton and aims to bring together researchers looking to show how cutting edge artificial and augmented intelligence technologies can be used to push the boundaries of scientific discovery. We launched in December 2018, and this conference marks the end of our first year. This is a two day event with a mixture of keynote talks from experts in the different areas of AI for Scientific Discovery, and discussions around different research areas. There will be dedicated time for networking and we will be implementing a smart badge system whereby attendees can mark their badges according to whether they are looking for a collaborator, employment, job candidates, PhD students etc. We will report on the activities of AI3SD over the last year, including the workhops and hackathons we have run and attended, and there will be an opportunity to hear from the projects we funded in AI3SD-FundingCall1. On the evening of the 18th there will be drinks and networking in the Winchester Science Centre followed by a pre dinner talk by famous Science Communicator Steve Mould! This will be followed by a formal conference dinner at the Holiday Inn.
On the 17th October 2019 AI3SD, IoFT (The Internet of Food Things Network+) and members of the Food Water and Waste Research Group at the University of Nottingham teamed up to host…
This event is brought to you by the AI3SD (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) and the IoFT (Internet of Food things) Networks. As food allergies and intolerances are on the rise, allergen detection and awareness is becoming more critical than ever at all stages of the food production pipeline; from cleaning the factories and kitchens the food is produced in, to detecting allergens in food, right through to creating allergen free food in the future. Unsurprisingly research has turned to technological solutions to combat this issue. This workshop is centered around the usage of Artificial Intelligence in Allergen Detection and Smart Cleaning within Food Production; research areas that co-align between both AI3SD & IoFT. The workshop will begin with some thought provoking talks to report on the current state of affairs, and consider where we need to be going in the future. There are five main working group topics identified for this workshop, and talks will be given on the different aspects that need to be considered with respect to allergen detection and smart cleaning before we break into the working groups for more formal discussions. There are multiple sessions for the working group discussions, and so there will be opportunities to take part in as many group discussions as you wish. The workshop will be formally recorded and the suggestions for going forward will be captured in a position paper. Lunch will be provided and the workshop will end with networking drinks.