Schedule

Coffee and light breakfast will be provided.

Patients and their communities are not just beneficiaries of scientific progress—they are active drivers of discovery. Through their lived experience, advocacy, and ability to mobilize data and resources, they play a crucial role in shaping research, policy, and funding. This session explores the impact of patient-led initiatives and highlights how partnerships with patient organizations are transforming open science and drug discovery. Linda Lafontaine - Patient advocate for Hereditary Spastic Paraplegia Jason Karamchandani - Associate Professor in the Department of Pathology, a Neuropathologist at The Montreal Neurological Institute and Hospital, and Director of C-BIG Inspired by the promise of open science, Linda Lafontaine, a patient with the rare neurological disorder Hereditary Spastic Paraplesia (HSP), decided to donate data and biospecimens to Clinical, Biospecimen, Imaging, and Genetic (C-BIG) Repository, The Neuro's open science repository. While a powerful choice in itself, Linda went further and rallied the HSP community to do the same, creating a crucial cohort within C-BIG that will enable further HSP research and will help lead to further treatments. She will take the stage to tell us her story of how patients can be a driving force in enabling and accelerating research.

Keynote

Coffee and pastries will be provided.

Are you working in computational drug discovery and would love to connect with peers and learn about what they pay attention to? Join us for this strategic networking session. The first hour will be structured speed networking, allowing participants to meet multiple peers in short, focused conversations. Afterward, the discussion will continue in an open networking format. Intended audience: People working or investing in computational drug discovery. Space is limited, so please indicate your attendance on the registration form. Session designed and facilitated by Lauriane Gorce, Senior Manager, Partnerships at Conscience.

Networking

The traditional view has long been that drug development follows a single viable model, with open science and global access efforts confined to the pre-competitive space. This session challenges that assumption, featuring speakers and projects demonstrating new models that are actively driving drug discovery today. Medicines for Kids (M4K) Pharma: Discovering Drugs with Open Science and Without Patents Max Morgan - CEO of the Agora Open Science Trust & General Counsel of the Structural Genomics Consortium ASAP Discovery: Balancing Open Science and Intellectual Property to Discover and Develop Medicines Ed Griffen - ASAP Discovery Project Lead on Lead Optimization & Technical Director, MedChemica Drug discovery organizations typically recoup their investment by filing patents, granting them monopolies on drug manufacturing and sales, allowing them to control pricing and distribution. This creates global access issues. Alternatively, in an "Open Science" approach, R&D organizations publish all information about a drug without patents, enabling anyone to use it but without control over its pricing or distribution. In a pandemic, this lack of control can hinder rapid drug development and access, while patents can lead to price distortions. Here we share and discuss the ASAP AViDD Centre’s model that balances innovation with global fairness by using "maximally permissive licenses" and "minimally defensive patents." This model prioritizes affordable pricing and global equitable access while maintaining control over the most crucial aspects of drug development. We will discuss our experience in developing and using this model.

Thematic session

Lunch will be provided.

This session highlights leading projects and organizations developing open data assets and explores why transparency and accessibility are essential to the future of drug discovery. AIRCHECK: Powering AI-Driven Drug Discovery with Open Science Benjamin Haibe-Kains - Head of Data Science at the Structural Genomics Consortium AIRCHECK (Artificial Intelligence-Ready CHEmical Knowledge base) overcomes obstacles in small molecule hit discovery - including fragmented datasets, limited reproducibility, and inefficient computational models - by integrating cutting-edge experimental techniques—including DNA-Encoded Libraries (DEL), and Enantiomer-selective Affinity Selection Mass Spectrometry (EAS-MS)—with machine learning (ML) and AI-driven analytics. Built on Google Cloud, AIRCHECK provides a scalable, open-access data platform that enhances hit identification, benchmarking, and reproducibility through MLOps workflows. By curating high-quality datasets and developing robust baseline AI models, AIRCHECK ensures that predictive insights translate into experimentally validated drug candidates. This presentation will provide an overview of AIRCHECK’s vision, mission, and technological framework, detailing how it leverages large-scale datasets and computational models to streamline drug discovery. We will also discuss the AIRCHECK roadmap, its role in accelerating AI-driven pharmaceutical research, and its long-term impact on enhancing reproducibility, reducing costs, and democratizing access to high-quality drug discovery data. Recursion's public RxRx cell image datasets Oren Kraus - Associate Director of Machine Learning at Recursion Toronto Cellular imaging-based screening, often referred to as High Content Screening, is a powerful technology used in drug discovery to identify novel mechanisms of action and prioritize drug candidates. Recursion has spent over a decade building the largest dataset of cell imaging data, spanning over 21 petabytes and covering millions of genetic and chemical perturbations. This talk will cover the key datasets that Recursion has released publicly, including RxRx1 and RxRx3/RxRx3-core (more info at rxrx.ai ) and how they've been used by the data science and computational biology communities to accelerate drug discovery.

Thematic session

With three completed and three ongoing challenges, the CACHE Challenges have sparked a diverse range of strategies for tackling selected drug discovery targets. In this session, standout participants will share their approaches, insights, and key takeaways—offering a behind-the-scenes look at how they tackled the challenges and what others can learn from their methods. Karina Machado - Associate Professor, Universidade Federal do Rio Grande (FURG) Daniel Cole - Reader & UKRI Future Leaders Fellow in Computational Chemistry, Newcastle University Francesco Gentile - Assistant Professor, Department of Chemistry and Biomolecular Sciences, University of Ottawa Mykola Protopopov - Head of Computational Chemistry at Chemspace

Thematic session

It’s 2040 - open science and breakthrough technologies like AI and quantum computing have transformed drug discovery, bringing treatments to rare and infectious diseases at scale. We’re gathered as the key stakeholders who helped make this future a reality to discuss how we can better support each other. After two days of talks and discussions, this open discussion will be your key takeaway: What role will you play in shaping the future of open drug discovery? Space is limited, so please indicate your attendance on the registration form. Session designed and facilitated by Lauriane Gorce, Senior Manager, Partnerships at Conscience.

Open discussion