7th Artificial Intelligence in Chemistry Symposium
Event
7th RSC-CICAG / RSC-BMCS Artificial Intelligence in Chemistry
Dates
Monday-Wednesday, 16th – 18th September 2024
Place
Churchill College, Cambridge
Important links and downloads
X hashtag – #AIChem24
To register for the meeting, click here
To Exhibit or Sponsor the meeting, click here
Synopsis
Artificial Intelligence is experiencing a renaissance in the development of new methods and practical applications to ongoing challenges in Chemistry. Following the successes of five annual “Artificial Intelligence in Chemistry” meetings starting in 2018, we are pleased to announce that the Chemical Information & Computer Applications Group (CICAG) and Biological & Medicinal Chemistry Sector (BMCS) of the Royal Society of Chemistry are once again organising a conference to present the current advances in AI and machine learning in Chemistry. The meeting will be held over two and half days and combine aspects of artificial intelligence and deep machine learning methods to applications in chemistry. The programme will include a mixture of keynote talks, panel discussion, oral presentations, flash presentations, posters and opportunities for open debate, networking and discussion.
This year meeting has changed format to two and half days and will include workshop on first day, please keep checking website for updates.
Workshop on Monday 16th September
One of the key pieces of feedback from the previous meetings was the desire for an introduction to AI/ML for Chemistry. For scientists new to the area the acronyms and terminology can be a significant barrier. For those who are already involved in AI/ML the whole scientific field is expanding so rapidly it is becoming impossible to keep abreast with latest developments and understand the strengths and weaknesses of the various approaches. So, the 2024 meeting will include a half-day workshop prior to the main meeting to provide this introduction. We are delighted to announce that workshop will be led by Andrea Volkamer and Pat Walters.
Who should attend
This meeting will be of interest to scientists of any level of experience from academia and industry
Call for Posters / Abstracts
The abstract submissions are now closed!
Want to become a member?
To join the RSC in order to qualify for discounted registration fees at all RSC, please follow this RSC link.
Bursaries
The RSC-BMCS and RSC-CICAG are offering a small number of bursaries to attend the meeting in person. Applications are open to PhD and post-doctoral applicants studying at academic institutions or non-profit institutions. Preference will be given to members of the RSC-BMCS and RSC-CICAG. Bursary applications are also invited from RSC or EFMC members who are of working age, but currently unemployed, and from those who may have difficulty in funding themselves or whose organisations may have difficulty in funding their attendance. The bursary value for this event is up to £700 and applicants have to fill either an RSC-BMCS or RSC-CICAG application form. The bursary application has now closed.
AI in Chem 24 Programme
Monday 16th September| 12.00-13.00 | Registration & Refreshments |
| Session Chair: Chris Swain | |
| 13.30-14.30 | Workshop 1 Pat Walters & Andrea Volkamer |
| 14.30-15.00 | Break |
| 15.00-16.00 | Workshop 2 Pat Walters & Andrea Volkamer |
| 16.00-16.30 | Break |
| 16.30-17.30 | Workshop 3 Pat Walters & Andrea Volkamer |
| 17.30-18.00 | Q&A |
| 18.00 | Close |
| 19.00 | Barbecue for all registered at Churchill |
Tuesday 17th September
| 09.15-10.00 | Registration & Refreshments |
| 10.20-10.30 | Opening Remarks |
| Session 1 Chair: Garrett M. Morris | |
| 10.30-11.30 | Keynote 1: Predicting general biomolecular interactions with AlphaFold 3 John Jumper, Google DeepMind, UK |
| 11.30-12.00 | Flash Posters 20 x 1.5 min talks |
| FT01: Machine learning and chemical kinetics models of phosphate dissolution: utilizing scarce and noisy data Aleksandra Zahharova, Tallinn University of Technology, Estonia FT02: On the effectiveness of quantum chemistry pre-training for small molecule property prediction Arun Raja, University of Oxford, UK FT03: Refining Drug-Like Space Diffusion Modelling Through Iterative Guidance Auro Varat Patnaik, University of Edinburgh, UK FT04: The Best of Both Worlds: Density Functional Theory and Machine Learning Integration for Inorganic Vapor Pressure Predictions Christopher Pashartis, IMEC, Belgium FT06: Bringing back the human touch: Expert-in-the-loop AI in chemistry using probabilistic models Hessam Mehr, University of Glasgow, UK FT07: Predicting the biochemical activities of unidentified chemicals from MS2 spectra to pinpoint potential toxic agents Ida Rahu, Stockholm University, UK FT08: How to make machine learning scoring functions competitive with FEP Isak Valsson, University of Oxford,UK FT09: A multitask model to predict the stability of double stranded nucleic acids Ivan Yankov, University of Strathclyde, UK FT10: PolyCL: Contrastive Learning for Polymer Representation Learning via Explicit and Implicit Augmentations Jiajun Zhou, Imperial College London, UK FT11: SAFEPATH: Using AI to understand the molecular mechanisms causing safety failures, enabling drug optimisation and turnaround Layla Hosseini-Gerami, Ignota Labs, UK FT12: How do autoencoders help explore the conformational space of MD simulations of cyclic peptides? Leonie Windeln, University of Southampton, UK FT13: SynFlowNet: Towards Molecule Design with Guaranteed Synthesis Pathways Miruna Cretu, University of Cambridge, UK FT14: Implementation and assessment of 3D scoring functions within de novo drug design platform REINVENT Nicholas Runcie, AstraZeneca, UK FT15: Improving Route Development Using Convergent Retrosynthesis Planning. Paula Torren-Peraire, Janssen Pharmaceutica NV, Belgium FT16: KinoDL-3D: Structure-based models for kinase-centric drug design Michael Backenkohler, Saarland University, Germany FT17: BALM: Binding Affinity Predictions with Protein and Ligand Language Models Rohan Gorantla, University of Edinburgh, UK FT18: Towards Automated Reassignment of Nuclear Magnetic Resonance Spectra Ruslan Kotlyarov, University of Cambridge, UK FT19: An adaptive approach for exploring protein conformational ensembles using generative models Anna Puszkarska, The University of Edinburgh, UK FT20: Harnessing Instruction-Tuned Large Language Models to Mine Structured Chemical-Pathway Dataset from Literature Yufan Liu, The University of Surrey, UK |
|
| 12.00-13.30 | Lunch, Exhibition, Posters (odd numbers), and Networking |
| Session 2 Chair: Kim Jelfs | |
| 13.30-14.30 | Keynote 2: Working: Leveraging community knowledge in transition metal complex and metal organic framework discovery Heather Kulik, Massachusetts Institute of Technology, USA |
| 14.30-15:00 | Directional Multiobjective Optimization of Metal Complexes In Vast Chemical Spaces Hannes Kneiding, University of Oslo, Norway |
| 15:00-15.30 | CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning Ulrik Friis-Jensen, Department of Chemistry, University of Copenhagen, Denmark |
| 15.30-16.00 | Refreshments, Exhibition, Posters (even numbers), and Networking |
| Session 3 Chair: Chris Swain | |
| 16.00-16.30 | Molecular Set Representation Learning Maria Boulougouri, EPFL, Switzerland |
| 16.30-17.00 | Hybrid AI and Open-Source for Molecular Design Andrea Volkamer, Saarland University, Germany |
| 17.00-18.00 | Perspective: AI in Drug Discovery – Where are we making an impact? Patrick Walters, Relay Therapeutics, USA |
| 18.00 | Close |
| 18.30 | Walk to conference dinner |
| 19.00 | Reception & Conference Dinner at St John's |
Wednesday 18th September
| 08.30-09.30 | Refreshments |
| Session 4 Chair: Pradip Songara | |
| 09.30-10.00 | Val Gillet, University of Sheffield. |
| 10.00-10.30 | Training Instruction-Tuned and Byte-Level Language Models for Organic Reaction Prediction Jiayun Pang, University of Greenwich, UK |
| 10.30-11.00 | Refreshments, Exhibition, Posters (even numbers), and Networking |
| Session 5 Chair: Nessa Carson | |
| 11.00-11.30 | Practical Machine Learning for Organic Small Molecule Modelling Emma King-Smith, University of Cambridge, UK |
| 11.30-12.00 | Incorporating Synthetic Accessibility in Drug Design: Predicting Reaction Yields of Suzuki Cross-Couplings by Leveraging AbbVie's 15-Year Parallel Library Dataset Priyanka Raghavan, Massachusetts Institute of Technology, USA |
| 12.00-13.30 | Lunch, Exhibition, Posters (odd numbers), and Networking |
| Session 6 Chair: Samantha Hughes | |
| 13.30-14.00 | Learning the Language of Crystal Chemistry: Using Concepts from Natural Language to Model Solid State Chemistry Keith Butler, UCL, UK |
| 14.00-14.30 | AI-enabled polypharmacology at proteome scale Alexsis Molina, Nostrum Biodiscovery, Barcelona, Spain |
| 14.30-15.00 | MolSnapper: Conditioning Diffusion for Structure Based Drug Design Yael Ziv, University of Oxford, UK |
| 15.00-15.30 | Refreshments, Exhibition, and Networking |
| Session 7 chair: Nathan Brown & Chris Swain | |
| 15.30-16.00 | Continuous monitoring of molecular data and model drift to improve reliability and support of QSAR models David Marcus, GSK, UK |
| 16:00-16.30 | Machine learning and AI for targeted protein degradation Eva Nittinger, AstraZeneca, Sweden |
| 16.30-17.00 | Poster Prizes and Closing Remarks - Chris Swain |
| 17.00 | Conference Close |
Keynotes:
John Jumper, Google DeepMind, UK
Heather Kulik, Massachusetts Institute of Technology, USA
Speakers:
Alexis Molina, Nostrum Biodiscovery, Spain
Andrea Volkamer, Saarland University, Germany
David Marcus, GSK, UKEmma King-Smith, University of Cambridge, UK
Eva Nittinger, AstraZeneca, Sweden
Hannes Kneiding, University of Oslo, Norway
Jiayun Pang, University of Greenwich, UK
Keith Butler, UCL, UK
Maria Boulougouri, EPFL, Switzerland
Pat Walters, Relay Therapeutics, USA
Priyanka Raghavan, MIT, USA
Ulrik Friis-Jensen, University of Copenhagen, Denmark
Val Gillet, University of Sheffield
Yael Ziv, University of Oxford, UK
Workshop:
Andrea Volkamer, Saarland University, Germany
Pat Walters, Relay Therapeutics, USA
Registration
The registration is now closed.
In person registration fees
RSC Member* £340
Non-Member £430
RSC Student ** Member* (Undergraduate and post-graduate) £195
Student** Non-Member (Undergraduate and post-graduate) £250
Online attendance registration fees
RSC Member* £235
Non-Member £282
RSC Student ** Member* (Undergraduate and post-graduate) £125
Student** Non-Member (Undergraduate and post-graduate) £162
* Member is a paid-up member of the RSC
** Student rates apply to undergraduate and post-graduate students only, but not post-doctoral students.
Sponsorship/Exhibition Opportunities
Click here to book exhibition stand or sponsor the meeting.
Exhibition stand package is priced at £1,300 and includes:
– A six-foot trestle table and chair(s);
– Access to electricity and Wi-fi;
– Logo inclusion in pdf delegate handbook and rolling slides;
– Exhibitors promotional page in the pdf delegate handbook;
– Logo included in the communication emails to delegates;
– One exhibitor stand staff with access to the technical sessions and Conference dinner (excluding accommodation)
We are also seeking sponsorship from organisations supporting the low registration fees offered to students. You can support and sponsor this meeting by clicking the booking link above.
Poster Prize Sponsors
Exhibitors
Sponsors
Scientific Organising Committee
Nathan Brown, Healx
Nessa Carson, AstraZeneca
Samantha Hughes, AstraZeneca
Kim Jelfs, Imperial College London
Garrett M. Morris, University of Oxford (Co-Chair)
Pradip Songara, Rothamsted Research (Treasurer)
Chris Swain, Cambridge MedChem Consulting (Co-Chair)
Secretariat Contact
Hg3 Conferences Ltd
+44 (0)1423 529333
E-mail