• Article: Integrating synthetic accessibility with AI-based generative drug design
• Article: Molecular assays simulator to unravel predictors hacking in goal-directed molecular generations
• Article: Exploring isofunctional molecules: Design of a benchmark and evaluation of prediction performance

• Article: MELLODDY: Cross Pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR Without Compromising Proprietary Information
• Article: A molecular assays simulator to unravel predictors hacking in goal-directed molecular generations
• Article: On the frustration to predict binding affinities from protein–ligand structures with deep neural networks
• Article: Key points to succeed in Artificial Intelligence drug discovery projects
• Article: Deep generative models for ligand-based de novo design applied to multi-parametric optimization

• Article: Integrating synthetic accessibility with AI-based generative drug design
• Article: Designing small molecules for therapeutic success: A contemporary perspective

• ACS Spring:

Structure-based generative AI for de novo drug design 

Presenter: Matthew Medcalf

• ACS Spring:

Molecule generation under the constraint of synthesizability

Presenter: Brian Atwood

• CHI Drug Discovery Chemistry:

Makya and modern virtual hit-finding: Ultra-large libraries, scaffold-hopping, and ensuring synthesizability with Spaya

Presenter: Brian Atwood

• Anglonordic Life Science Conference 2023:

Panel Discussion: How artificial intelligence is transforming drug discovery, design, and development

Presenter: Yann Gaston-Mathé

• GGMM 2023:

The power of active learning in drug discovery: How DockAI can revolutionize hit discovery

Presenter: Maud Jusot

• 3rd RSC Anglo-Nordic Medicinal Chemistry Symposium:

Yes, you should use AI for medicinal chemistry!

Presenter: Quentin Perron

• Summer School in Cheminformatics:

AI exploration in chemoinformatics

Presenter: Brice Hoffmann

• 2nd Targeted Protein Degradation Conference:

AI-driven de novo PROTAC design and synthetic planning

Presenter: Hideyoshi Fuji

• ACS Fall:

From chatbots to cures: Unlocking the potential of AI for medicinal chemists

Presenter: Matthew Medcalf

• SLAS 2022:

Accelerating the drug discovery process with AI-driven automation technologies: De novo design, retrosynthesis and scheduling

Presenter: Rohit Arora

• ACS Spring:

Interpreting quantitative structure-activity relationship models to guide drug discovery

Presenter: Rohit Arora

• ACS Spring:

Evaluating, benchmarking, and comparing computer-aided synthesis planning software tools

Presenter: Brian Atwood

• ACS Spring:

Structure-guided de novo drug design using deep generative modeling

Presenter: Brian Atwood

• CHI: Drug Discovery Chemistry:

AI for de novo drug design: Real-life applications of compound generation under synthetic constraints for drug discovery

Presenter: Quentin Perron

• SLAS Europe:

Synergetic drug design using AI and automation

Presenter: Sree Vadlamudi

• 8th Strasbourg Summer School in Chemoinformatics:

Representing, predicting, and generating simple and complex peptides

Presenter: Brice Hoffman

• 2nd Edition “AI and Medicine: Promises and Limits” Symposium

How can medicine benefit from AI?: Drug Discovery

Presenter: Nicolas Do Huu

• Boulder Peptide Symposium

Representing, predicting, and generating simple and complex peptides

Presenter: Massina Abderrahmane

• 7th Annual Drug Discovery Summit

Generative Models to Novel Compounds: Multi-Parametric Optimisation and Synthetic Accessibility

Presenter: Sree Vadlamudi

• SMR:

The reality of Artificial Intelligence in drug discovery

Presenter: Quentin Perron

• Spaya Webinar:

AI-enhanced retrosynthesis webinar: Spaya for chemists

Presenters: Quentin Perron, Brian Atwood

• 3rd AI-ML in Drug Discovery and Development :

Generative models and multi-parametric optimization: drug discovery in the context of de novo drug design, AI and ML

Presenter: Sree Vadlamudi

• COMP Together Virtual Meeting:

High-throughput retrosynthesis: Constraining molecular generators to realistically synthesizable molecules

Presenter: Brian Atwood

• Drug Discovery Chemistry 2021:

Artificial intelligence- Drug discovery

Presenter: Quentin Perron

• NIH Virtual Workshop on Reaction Informatics:

Spaya API for high-throughput retrosynthesis: constraining molecular generators to synthesisable molecules

Presenter: Brian Atwood

• Iktos conference – AI for de novo drug design:

Predictors hacking during generation

Presenters: Joseph-André Turk, Philippe Gendreau

• Iktos conference – AI for de novo drug design:

Spaya workshop

Presenter: Brian Atwood

• Iktos conference – AI for de novo drug design:

Makya workshop

Presenter: Rohit Arora

• Iktos conference – AI for de novo drug design:

Structure-guided de novo drug design using deep generative modeling, a case study

Presenter: Brice Hoffmann

• Iktos conference – AI for de novo drug design:

Generative AI, a long journey…

Presenter: Quentin Perron

• Iktos conference – AI for de novo drug design:

Retrosynthetic analysis using Chemspace chemistry

Presenter: Hamza Tajmouati

• APAC Digi-Tech Pharma Webinar Series 2021:

Deep generative models, multi-parametric optimization and synthetic accesability

Presenter: Sree Vadlamudi

• ACS Meeting – Fall:

Makya: AI-driven de novo drug design platform focused on multi- parametric optimization

Presenter: Rohit Arora

• ACS Meeting – Fall:

Spaya and the spaya API: AI enhanced retrosynthesis planning

Presenter: Brian Atwood

• EFMC-ISMC 2021 – XXVI EFMC International Symposium on Medicinal Chemistry:

Fragment growing with reaction prediction for hit discovery

Presenter: Quentin Perron

• Congrès GGMM (Groupe de Graphisme et de Modélisation Moléculaire) – SFCI (Société Française de Chemoinformatique) 2021:

Structure-guided de novo drug design using deep generative modeling, a case study

Presenter: Brice Hoffmann

• Congrès GGMM (Groupe de Graphisme et de Modélisation Moléculaire) – SFCI (Société Française de Chemoinformatique) 2021:

Understanding structure-activity relationship with interpretability methods for molecular activity and chemical property prediction

Presenter: Joseph-André Turk

• Discovery series UK – Oxford Global:

Multi-parametric optimization and synthetic accesability: Generative models to novel compounds

Presenter: Sree Vadlamudi

• Discovery series UK – Oxford Global:

Collaboration in drug design – Technologies and AI applied to drug design

Presenter: Sree Vadlamudi

• SLAS 2021: AI-Powered Drug Discovery Symposium:

Generative AI: Application to drug discovery

Presenter: Sree Vadlamudi

• SLAS 2021: AI-Powered Drug Discovery Symposium:

Collaborations In drug design – AI platform technogies applied to drug design

Presenter: Sree Vadlamudi

• 4th AI in Pharma Summit:

Generative models to novel compounds: Multi-parametric optimization and synthetic accessibility

Presenter: Sree Vadlamudi

• Discovery Chemistry – Oxford Global:

Generative AI for de novo drug design: A look back and a look forward, lessons learned and prospects for the future

Presenter: Quentin Perron

• Proventa – Biology & Medicinal Chemistry Strategy Meeting:

AI in drug discovery- Roundtable discussion

Presenters: Yann Gaston-Mathé, Alessandro Monge

• Spaya Webinar:

AI for retrosynthesis- Spaya

Presenters: Quentin Perron, Hamza Tajmouati

• International Conference on Innovative Solutions: Cancer, Aging & Genetic diseases:

AI for novel drug design – perspective and case studies

Presenter: Yann Gaston Mathé

• Makya Webinar:

Everything you ever wanted to know about generative modeling… but were afraid to ask

Presenter: Quentin Perron

• Drug Discovery Chemistry 2019:

Deep learning for ligand-based de novo design in lead optimization: a real life case study

Presenter: Yann Gaston-Mathé

• Merck Seminar:

AI approaches to NCE de novo drug design & synthesis planning

Presenter: Quentin Perron

• Pharma AI Summit:

Introduction to AI applied to chemistry

Presenters: Philippe Gendreau, Adam Skiredj