5th Artificial Intelligence in Chemistry Symposium

5th RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry

Thursday-Friday, 1st-2nd September 2022

Churchill College, Cambridge or Virtual Attendance

The intention is to hold this meeting in-person with talks also being live streamed from the auditorium over Zoom for remote attendees.
Networking and poster sessions are planned to be in-person only. The in-person nature of the
event is subject to COVID-19 – related government and local university requirements and might be
subject to change, so please be aware of this before planning your trip. The event organisers are
not responsible for any expenses incurred.

Important links and downloads
Twitter hashtag – #AIChem22
First announcement poster
Second announcement poster
5th RSC-BMCS/RSC-CICAG Meeting Report


Artificial Intelligence is experiencing a renaissance in the development of new methods and practical applications to ongoing challenges in Chemistry. Following the successes of four annual “Artificial Intelligence in Chemistry” meetings starting in 2018, we are pleased to announce that the Biological & Medicinal Chemistry Sector (BMCS) and Chemical Information & Computer Applications Group (CICAG) 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 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.

Who should attend
This meeting will be of interest to scientists of any level of experience from academia and industry

Call for Posters / Abstracts
Abstract submissions are now closed.

Thursday 1st September

9:15Registration and refreshments
10:20Opening remarks
Samantha Hughes, AstraZeneca, UK
Session 1:
Chair: Samantha Hughes, AstraZeneca, UK
10:30Keynote 1: Keynote 1: From a Combination of Chemical Synthesis and Automation to Enzymatic Design: the Many Opportunities of Language Models in Chemistry
Teodoro Laino, IBM Zurich, Switzerland

11:30Flash poster presentations

FO01: Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation
Jack Broad, University of Nottingham, UK

FO02: CACHE: An International Competition to Define the State-of-the-Art in Computational Molecular Design for Drug Discovery
Matthieu Schapira, SGC, Canada

FO05: Building a Machine Learning Platform to Enable Sustainable Solvent Selection
Samuel Boobier, University of Nottingham, UK

FO06: SARkush: Automated Markush-Like Structure Generation for SAR Communication
Lauren Reid, MedChemica Ltd, UK

FO07: Using Matched Molecular Pairs For CoreDesign®
Jess Stacey, MedChemica Ltd, UK

FO08: CoPriNet: Predicting compound prices using Graph Neural Networks
Ruben Sanchez Garcia, University of Oxford, UK

FO09: Persistent Images: A Novel Molecular Representation To Exploit Computer Vision Based Deep Learning Architectures For Drug Discovery
Aras Asaad, Oxford Drug Design Ltd, UK

FO10: Data-driven discovery of porous liquids: A combined theoretical and experimental approach
Austin Mroz, Imperial College London, UK

FO12: The Fragment Network as a novel source of fragment merges
Stephanie Wills, University of Oxford, UK

FO13: Improving the diversity of AI generated molecules for drug design
Maxime Langevin, Sanofi Aventis, France

FO14: Using AI to drive valuable insights from drug discovery data
Matthew Segall, Optibrium, UK

FO15: Fragment-Based Hit Discovery via Unsupervised Learning of Fragment-Protein Complexes
William McCorkindale, University of Cambridge, UK

FO16: BERT models in kinetic prediction: methodological insights and interpretation of predictions
Chloe Wilson, University of Oxford, UK

FO17: Transfer Learning for Improved Peptide Activity Prediction on Small Dataset
Erik Otovic, University of Rijeka, Croatia

FO18: Machine learning for yield prediction for chemical reactions using in situ sensors
Joseph Davies, University of Nottingham, UK

FO19: Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction
Austin Tripp, University of Cambridge, UK

FO20: High-throughput autonomous discovery of novel porous liquids
Austin Mroz, Imperial College London, UK

FO22: Bias in the Benchmark: Systematic experimental errors in bioactivity databases confound multi-task and meta-learning algorithms
Leo Klarner, University of Oxford, UK
12:05Lunch, Exhibition, poster session and networking
Session 2:
Chair: Nadia Ahmad, Charles River, UK
13:30S01 Global and Local Experts for Molecular Activity Prediction
Héléna Gaspar, BenevolentAI, UK
14:00S02 Remembering the lab in computational molecular material discovery
Kim Jelfs, Imperial College London, UK

14:30O03 Hybrid Alchemical Free Energy/Machine-Learning Methodologies for Drug Discovery
Julien Michel, University of Edinburgh, UK
15:00Refreshments, exhibition, posters and networking
Session 3:
Chair: Kathryn Giblin, AstraZeneca, UK
15:30S04 Machine Learning for Toxicity Prediction - Applications BASF
Miriam Mathea, BASF, Germany
16:00O05 Socioeconomic, Environmental, and Scientific Considerations for the Recent Technological Shift in Cheminformatics and Computational Chemistry
Daniel Probst, École Polytechnique Fédérale de Lausanne, Switzerland
16:30Panel Discussion
Chair: Garrett M. Morris, University of Oxford, UK
18:15Walk to conference dinner
19:00Reception and conference dinner at Trinity Hall

Friday 2nd September

Session 4:
Chair: Chris Swain, Cambridge MedChem Consulting, UK
9:30Keynote 2: The power and pitfalls of machine learning in early stage drug discovery
Charlotte Deane, MBE, University of Oxford, UK
Session 5:
Chair: Chris Swain, Cambridge MedChem Consulting, UK
11:00O06 De novo Molecular Design in 3D using Available Reagents, Reactions, and Docking in Deep Reinforcement Learning for SARS-CoV-2 Main Protease
An Goto, University of Oxford, UK
11:30O07 Forecasting Vaping Health Risks Through Neural Network Model Prediction of e-liquid Flavour Pyrolysis Reactions
Donal O’Shea, Royal College of Surgeons in Ireland, Ireland
12:00S08 Models of Chemical Reactivity to Inform Molecular Design
Conor Coley, Massachusetts Institute of Technology, USA
12:30Lunch, Exhibition, poster session and networking
Session 6:
Chair: Nathan Brown, Healx, UK
14:00Keynote 3: Machine Learning for Accurate Energies and Forces in molecular systems. Uses in conformational searches and free energy calculations
Adrian Roitberg, University of Florida, USA

15:00S09 Machine learning-based predictions of ADME properties in pharmaceutical industry
Raquel Rodriguez Perez, Novartis, Switzerland

15:30Refreshments, exhibition and networking
Session 7:
Chair: Garrett M. Morris, University of Oxford, UK
16:00O10 3D Pride Without 2D Prejudice: Bias-Controlled Multi-Level Generative Models for Structure-Based Ligand Design
Lucian Chan, Astex, UK

16:30O11 MoLeR: Creating a Path to More Efficient Drug Design
Krzysztof Maziarz, Microsoft Research, UK
17:00Closing remarks
Garrett M. Morris, University of Oxford, UK

*Programme timings subject to change

Conference Dinner
The conference dinner will take place on Thursday 1st September at Trinity Hall and is included within the delegate registration fee. Trinity Hall is home to a friendly community of undergraduate and postgraduate students, tucked away on a beautiful riverside site by the city centre. It is one of the oldest colleges of Cambridge University, founded in 1350. It is a semi-formal evening and is a great time to come together to enjoy a three-course meal.

In person registration is now closed.
In person registration deadline: Monday 29th August 17:00 (BST)
Online attendance registration will remain open throughout the duration of the meeting.

Registration Fees** In person registration is now closed
In person attendance rate 
RSC Member* £330
Non-member £400
RSC Student** Member* £165
Student** Non-member £220

Online only rate
RSC Member* £220
Non-member £267
RSC Student** Member* £110
Student** Non-member £147

* Member is a paid-up member of the RSC
** Student rates apply to undergraduate and post-graduate students only, but not post-doctoral students.

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.

Student Bursaries

The RSC-BMCS and RSC-CICAG are offering a small number of student 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. The bursary value for this event is up to £600 and applicants have to fill either an RSC-BMCS or RSC-CICAG application form . The bursary application closing date is 14th July.

Exhibitor/Sponsorship Opportunities

Registrations are now closed

– A six foot trestle table and chair(s);
– Access to electricity and Wi-fi;
– Logo inclusion in delegate handbook and rolling slides;
– Exhibitors promotional page in the printed delegate handbook;
-One exhibitor stand staff with access to the technical sessions and conference dinner (Excluding accommodation)

£98.50 Accommodation per person, per night
£150 Delegate pack inserts

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.

We are grateful to our confirmed sponsors for their valued support.

We are grateful to our confirmed exhibitors for their valued support.

Organising Committee
Nathan Brown, Healx
Samantha Hughes, AstraZeneca (Co-Chair)
Garrett M. Morris, University of Oxford (Co-Chair)
Chris Swain, Cambridge MedChem Consulting (Interim Treasurer)

Secretariat Contact
Hg3 Conferences Ltd
+44 (0)1423 529333