Building Confidence Early through Intelligent Lead Optimization
The Discovery UGM at Certainty will focus on how modern cheminformatics is evolving to support confident decision-making at the very start of drug discovery. Focusing on intelligent lead optimization, the sessions will highlight how the combined capabilities of Chemaxon cheminformatics solutions and D360 enable scientists to evaluate, prioritize, and optimize compounds as new drug modalities reshape the discovery paradigm. The track will explore what it takes for informatics solutions to keep pace with increasing molecular complexity and data diversity – while helping teams build confidence in compound quality from day one.
Designed for discovery scientists and R&D informatics professionals, the Discovery UGM will appeal to attendees seeking to understand the latest advancements in cheminformatics and how they can be applied in real-world discovery workflows.
Through thought leadership presentations and hands-on tutorials, this track will provide:
- Insight into how emerging drug modalities are changing discovery strategies and informatics needs
- Practical examples of how Chemaxon and D360 can be used to support intelligent lead optimization
- A clearer understanding of how modern cheminformatics tools help de-risk early discovery and accelerate confident decision-making
Tuesday, April 14, 2026
Agenda
7:15 – 8:15
Breakfast & Badge Pick Up
8:15 – 8:30
Welcome to Certainty
Our Certainty theme in 2026 is “Right from the start”. Together, we’ll delve into how the how AI enabled modeling and simulation supported by digital data flows is improving decision making at every stage of R&D and bringing the best new medicines to patients.
8:30 – 9:15
Sheila Rocchio, Matt Rizk
The Innovation Circle: Driving Outcomes in R&D
Ideas, actions, and collaborations driving productivity, insight generation and a faster, more flexible and patient centric approach to medicine discovery and development. This session will share insights from leaders in drug discovery and development responsible for driving digital transformation and integration to driver, faster and more agile decision making.
Panel Moderator: Sheila Rocchio
Panelists:
Matt Rizk, PhD, Associate Vice President, Translational Sciences & Outsourcing
Department of Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics, Merck
9:15 – 10:00
Chris Bouton
Right from the Start: AI Enabled Science and Scientists: Introducing Certara Nexus for faster, model-informed decision making that regulators Trust
This session will showcase how AI is changing drug discovery and development focusing on insights and speed that democratize modeling and simulation insights earlier to speed the most promising new medicines to patients. An early look at new capabilities coming soon to the Certara portfolio will be demonstrated in this session.
Speaker: Chris Bouton, PhD, Certara CTO
10:00 – 10:30
Morning Break - Demo Bar
10:30 – 11:00
Pat Walters
OpenADMET: Raising The Bar on ADMET Prediction with Open Science
Potency optimization is rarely the primary bottleneck in drug discovery. Instead, the majority of medicinal chemistry resources are consumed by the complex task of balancing pharmacokinetics with the mitigation of off-target interactions. Challenges such as cytochrome P450-mediated drug-drug interactions and hERG-induced cardiotoxicity remain persistent hurdles that can derail a program in its final stages.
Unlike potency optimization, where computational tools like Free Energy Perturbation (FEP) provide a rigorous framework for decision-making, ADMET optimization has historically relied on empirical heuristics and trial-and-error. To formalize this challenge, Mark Murcko and James Fraser recently coined the term “Avoidome”, a collective map of the targets and biological pathways that drug candidates must navigate around to ensure safety and efficacy.
OpenADMET addresses the Avoidome through a systematic, integrated approach that synthesizes three critical pillars: targeted data generation, high-resolution structural insights from X-ray crystallography and cryo-EM, and predictive machine learning. This framework moves beyond the frustrating, reactive “whack-a-mole” cycle by providing a deeper understanding of the molecular determinants of off-target binding. By shifting from empirical trial-and-error to a proactive strategy grounded in structural and data science, OpenADMET enables the development of reusable design principles to navigate off-target space and accelerate the path to the clinic.
11:00 – 11:30
Adrian Stevens
Enabling AI-driven Modeling and Simulation-based Decision making in Discovery Towards Increased Clinical Drug Candidate Success
This session will highlight how an integrated, AI-enabled modeling and simulation platform can deliver deeper predictive insights and workflows from across the drug discovery process, with the aim of improving clinical success rates for compounds in discovery.
Speaker: Adrian Stevens, PhD, Chief Product Officer, Certara Chemaxon
11:30 – 12:15
Adrian Stevens, David Lowis
Aligning the early-stage discovery strategies across Chemaxon and Certara
Certara’s vision is to deliver an integrated biosimulation experience that accelerates Model-Informed Drug Discovery and Development. Our strategy centers on connecting applications across our portfolio to create seamless workflows. In this session, we’ll share recent progress in drug discovery software development and outline plans to unify key products and services. By building an informatics ecosystem that links chemistry, biology, and data science, we aim to enable smarter candidate selection and improve clinical trial outcomes. We’ll highlight enhancements in small molecule and sequence-based informatics—boosting performance, expanding entity support, and strengthening interoperability.
Speakers:
Adrian Stevens, PhD, Chief Product Officer, Certara Chemaxon
David Lowis, DPhil, Executive Director, Scientific Informatics, Certara D360
12:00 – 12:30
Coming Soon
12:30 – 1:00
Rajarshi Guha
Developing Predictive Models by Sharing Predictions
The development of high‑quality predictive models in drug discovery is frequently limited by the cost and scarcity of experimental data, especially for key pharmacokinetic endpoints. We describe the use of the Student–Teacher modeling framework, that enables multiple pharmaceutical companies to collaboratively build predictive models without sharing proprietary data or internal methodologies. In this approach, participating organizations train internal teacher models and generate predictions for a shared public compound set. A neutral honest broker aggregates and anonymizes these predictions, which are then used to train a single student model that captures the collective knowledge of all contributors.
Using volume of distribution at steady state (Vdss) as a case study we show that the resulting student model consistently outperforms individual teacher models and demonstrates strong performance on an external benchmark. Model performance improves as additional contributors participate, without reliance on any single model.
This simple, low‑cost, and model‑agnostic workflow illustrates how structured precompetitive collaboration can unlock greater value from existing data, accelerate model development, and expand the effective use of predictive modeling earlier in the drug design cycle.
Speaker: Rajarshi Guha, Senior Director, Data & Computational Sciences, Vertex Pharmaceuticals
1:00 – 2:00
Lunch & Demos
2:00 – 2:30
Ania Hajdukiewicz
Coming Soon
2:30 – 3:00
Krista Gipson, Cen Gao
Data Standardization and Visualization in Small Molecule Drug Discovery for the Laboratory of the Future
The rapid evolution of artificial intelligence (AI) and automation technologies is reshaping the landscape of small molecule drug discovery. As research workflows become increasingly digitized and integrated, the need for robust data standards and effective visualization methods has never been greater. This talk will explore the critical role that data standardization plays in enabling seamless data integration, sharing, and interpretation across multidisciplinary teams and advanced laboratory environments. We will showcase visualization tools and techniques that empower researchers to extract actionable insights from complex, high-dimensional datasets generated in AI-driven labs.
Speakers:
Krista Gipson, PhD, Senior Scientist, Takeda Pharmaceuticals
Cen Gao, Head of Computational Chemistry, Takeda
3:00 – 3:30
Coming soon
3:30 – 4:00
Afternoon Break
4:00 – 5:00
David Fajgenbaum, MD
Keynote Presentation
5:00 – 5:15
Close of Day
Wednesday, April 15, 2026
7:30 – 8:30
Breakfast & Badge Pick Up
8:30 – 9:00
Sean McGee
From Protocol to Submission: A Certara Workflow
Like a decathalon, a clinical study is a series of challenges. Selecting the right endpoints. Drafting a protocol. Setting up data collection. All this needs to happen before the first patient visit. From there, it’s wave after wave of data validation and analysis, reporting and table-creation, and the million-and-one checkpoints of submission.
How much time, cost, and pain might be saved by relying on a suite of interconnected solutions, each purpose-built for its task? Find out in this fast-paced demonstration of Certara capability from protocol to submission. In 30 minutes, you’ll see how our increasingly AI-driven technology supports your organization right from start, when a study is little more than a justified hope. Sean McGee will present solutions for endpoint selection, optimal trial design, data standardization, analysis, reporting, and more. Live 5-plus years of the trial life in a half-hour, all with Certara by your side.
9:00 – 9:30
David Lowis
D360 Peptide Support
9:30 – 10:00
József Kozma
Compound Registration as a Data Quality Gateway: Evolving for Multi-Modality Support
Compound Registration serves as a critical filter to ensure consistency, accuracy, and traceability across small molecules and emerging modalities. As our portfolio evolves to support biologics and sequence-based entities, the product is expanding its capabilities to meet new demands. Recent and upcoming enhancements include significant performance improvements in registration workflows and structure-based searches, both duplicate detection and substructure matching, as well as support for peptides and oligonucleotides. This presentation will outline how Compound Registration aligns with broader portfolio directions.
Speaker: József Kozma, Associate Product Manager Compound Registration, Certara
10:00 – 10:30
Jan Christopherson, Jeremy Malerich
Chemaxon Portfolio Update
10:30 – 11:00
Morning break
11:00 – 11:30
Luca Szabó
The Sketcher That Stays Out of Your Way: Marvin in the Modern Research Environment
Every chemist knows the small annoyances that add up over a day: switching between tools, reformatting structures for a report, hunting for the right template, wondering whether that stereocenter is correctly encoded. Solving these inconveniences is the promise behind the new Marvin.
The best drawing tool is the one you stop thinking about. It works in your ELN, in your registration system, in your Word document, behaving consistently and getting out of the way so you can focus on the science.
In this session we explore how this future can be achieved. We look at migration experiences from earlier versions and the integration of Marvin into existing environments: what worked, and where the new capabilities made a genuine difference. We also look at what comes next: the push toward broader modality support means that the same tool chemists rely on today for small molecules is being extended to serve a wider scientific community.
11:30 – 1:00
Jeremiah Malerich, Jan Christopherson
Introducing Chemaxon Python API
This tutorial will walk through two of our exciting technologies, the upcoming Python API and Design Hub. With options for hands-on participation or simple audience observation, we will familiarize you with the Chemaxon Python API which will soon come out of its Beta phase, culminating in the creation of a new predictive Machine Learning model. We’ll then incorporate that model into the hypothesis and compound design features of Design Hub, where you’ll also learn about the other capabilities that make it an ideal platform for collaboration in Med Chem teams.
Speakers:
Jeremiah Malerich, PhD, Solution Consultant, Certara
Jan Christopherson, Senior Solutions Consultant, Certara
1:00 – 2:00
Lunch & Demos
Reserve your spot
Reserve your spot for the Certainty US 2026 customer event for exclusive access to the Certara community of experts, industry leaders, and peers as we collectively explore the latest innovations and opportunities to bring greater certainty to drug discovery and development.
