Artificial Intelligence in Chemistry


Friday, 15th June 2018


Royal Society of Chemistry at Burlington House, London, UK



Registration is closed


Twitter hashtag - #RSC_AIChem


Downloads and Links
Please send an e-mail to the Secretariat to be kept informed about next year's event.


Post-event report, written by bursary awardees

Second announcement and call for posters

First announcement and call for abstracts

Directions to the venue
RSC website


Artificial Intelligence is presently experiencing a renaissance in development of new methods and practical applications to ongoing challenges in Chemistry. We were pleased to announce that the Biological & Medicinal Chemistry Sector (BMCS) and Chemical Information & Computer Applications Group (CICAG) of the Royal Society of Chemistry organised a one-day conference entitled Artificial Intelligence in Chemistry which presented the current efforts in applying these new methods.  We combined aspects of artificial intelligence and deep machine learning methods to applications in chemistry.


Programme   Where presentation titles are highlighted in blue, you may download the .pdf of the presentation

Where presenter names are highlighted in orange, you may download the .pdf of the poster


Registration, refreshments, and exhibition



Session chair:  Phil Jones, BioAscent


Self-driving synthesis planning
Marwin Segler, Benevolent AI, UK


Chemical topic modelling - an unsupervised approach to organize and explore chemical information
Nadine Schneider, Novartis, Switzerland


Flash presentations (15 x two-minute)


Application of AI to REAL space: a step ahead to expand the synthetically feasible chemical space
Andrii Buvailo, Enamine,Ukraine (P03)


ML-driven pathway design and validation in automated synthesis
Connor Coley, Massachusetts Institute of Technology, USA (P05)


Active search for computer-aided drug design
Jonathan Hirst, University of Nottingham, UK (P07)


Virtual screening with protein family-specific models using convolutional neural networks and transfer learning
Fergus Imrie, University of Oxford, UK (P08)


Deep learning based protein-ligand relative affinity prediction
José Jiménez, University Pompeu Fabra, Spain (P09)


Combining molecular dynamics simulations with Markov-state models to predict binding pose for fragment on the target protein
Aniket Magarkar, Boehringer Ingelheim Pharma GmbH & Co KG, Germany (P11)


A rule-based artificial intelligence technology for the generation of synthetically-enabled lead analogue idea space for AI-driven drug discovery
Greg Makara, ChemPass Ltd, Hungary (P12)


Deep learning for de novo drug design applied to lead optimization
Quentin Perron, Iktos, France (P14)


“Found in Translation”: neural machine translation models for chemical reaction prediction
Philippe Schwaller, IBM Research GmbH, Switzerland (P15)


AI for chemistry optimisation: combining machine learning and domain knowledge
Matthew Segall, Optibrium Limited, UK (P16)


Machine learning in quantum chemistry
Robert Shaw, University of Sheffield, UK (P17)


Deep generative models for structure based drug design
Miha Skalic, University Pompeu Fabra, Spain (P18)


Development of topological descriptors for understanding intermolecular interactions
Lee Steinberg, University of Southampton, UK (P19)


Word embedding approach for enhanced molecular generative models
Hamza Tajmouati, Iktos, France (P20)


Molecular Dynamics Fingerprints (MDFP): combining MD and machine learning to predict physicochemical properties
Shuzhe Wang, ETH Zurich, Switzerland (P21)


Refreshments, exhibition and posters



Session chair:  Nathan Brown, AIBenevolent


Keynote: What I learned about machine learning - revisited
Bob Sheridan, Merck, USA


Lunch, posters and exhibition



Molecular de novo design through deep learning
Ola Engkvist, AstraZeneca, Sweden


Scaling de novo design, from single target to disease portfolio
Willem van Hoorn, Exscientia, UK


Refreshments, posters and exhibition



Session chair:  Chris Swain, Cambridge MedChem Consulting


Investigating clusters in solvent data using K-means
Ella Gale, University of Bristol, UK


Deep learning and chemical data

Colin Batchelor, Royal Society of Chemistry, UK


Automation, analytics and AI
Darren Green, Molecular Design UK, RD Platform Technology & Science, GlaxoSmithKline, UK


Networking drinks reception




Who should attend

This meeting was of interest to scientists of any level of experience from academia and industry.

Call for Papers

Applications for poster presentations were welcomed. Posters were displayed throughout the day and applicants were asked if they wished to provide a two-minute flash oral presentation when submitting their abstract. Closing date was 13th April for poster submissions.


Registration and Bursaries

Please send an e-mail to the Secretariat to be kept informed about next year's event.


Registration fees were:
£120 RSC member
£145 Non-member
  £90 RSC student* member
£110 Student* non-member
* Student is undergraduate or post-graduate, not post-doc
Member is a paid-up member of the RSC. A late fee of £30 will apply to payments received from 11th May onwards.

A number of RSC-BMCS and RSC-CICAG student bursaries were available up to a value of £250, to support registration, travel and accommodation costs for PhD and post-doctoral applicants studying at European academic institutions. The closing date for bursary applications was 3rd May. 


There was a small, relevant trade exhibition – the charge was £500 including one full delegate.  The exhibition was held in the same rooms as the catering (refreshments and lunch) and posters, and the exhibition package included:
• stand space for maximum of two 1 m wide roller panels
• one table measuring 0.8 m deep x 1.6 m wide x 0.725 m high (optional) and chair

• electrical and wi-fi access
• the option to include a promotional page for your organisation in the delegate handbook
• logo acknowledgement in the delegate handbook.

Those companies wishing to have a trade stand were asked to apply early to avoid disappointment as space was limited.  The exhibition fee of £500 included one full delegate's attendance.   Exhibition is fully booked - sorry.


Delegate pack inserts could be booked at £150, comprising no more than two pages of A4 fixed together.


Cancellation Policy
In the event of cancellation before 1st June 2018, 80% of the fee paid will be refunded. Cancellations must be received in writing. Refunds will not be possible after that date although substitutions are possible at any time.

In the unlikely event of cancellation of the meeting, fees paid will be refunded in full. Registration acknowledgements will be sent within two weeks.

Venue and Travel
Library, Royal Society of Chemistry at Burlington House, Piccadilly, London, W1J 0BA, UK.   Directions to venue.

Situated in central London, the RSC is easily accessible by public transport, and close to Green Park tube station.

Wheelchair access to Burlington House is available - please contact the team in London via and they will be able to advise in more detail.


This first symposium was organised by the RSC BMCS (Biological and Medicinal Chemistry Sector) and the RSC CICAG (Chemical Information and Computer Applications Group).  Sponsors were sought to support the low registration fees offered for this first event.


We are grateful to our confirmed sponsors,






We are grateful to EFMC and COMS for supporting this event


Organising Committee
Nathan Brown, BenevolentAI (chairman)
Phil Jones, BioAscent

Chris Swain, Cambridge MedChem Consulting


Secretariat Contact
Maggi Churchouse, 3 East Barn, Market Weston Road, Thelnetham, Diss IP22 1JJ, UK
Telephone: +44 (0)1359 221004


To contact the secretariat, please send an e-mail.


Registration is closed



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