Location: The Broad Hub

1:30pm to 2:15pm - Informatizing the DMTA Cycle
Presenters: David Lowis, DPhil, Executive Director, Scientific Informatics, Certara; Adrian Stevens, PhD, Chief Product Officer, Chemaxon, Xin Zhang, Senior Director of Cheminformatics and Platform Integration, Cellarity

The four stages of the Design-Make-Test-Analyze cycle in discovery are deeply interconnected. Insights from Structure Activity Relationships uncovered in the Analyze stage drive iteration of Design. Design must look ahead to chemical inventory to prioritize which compounds to Make. All the while, scientists need to monitor Test results so they can continue Analysis.

Informatizing the DMTA cycle—that is, ensuring the standardization, accessibility, and connectivity of data within and between these stages—can accelerate the pace of discovery. In this session, the scientific leaders of D360 and Chemaxon will explain how Certara’s solutions are leading the way to informatics that close gaps in the DMTA cycle, freeing scientists to focus on promising leads, not data logistics.

2:15 - 2:45 - Deep Learning in Discovery
Presenter: Sean McGee, MS, Director of Product, Certara.AI, Certara

GPTs and machine learning are poised to accelerate and inform the DMTA cycle. From automating the discovery of compound data in files, lab reports, and more with optical structure recognition, to simplifying the building and maintenance of property prediction models, AI will guide your identification of more promising leads.

Examine these and other concrete applications with Sean McGee, MS, Director of Product, Certara.AI.

2:45-3:00 - From Chemical Structure to PBPK
Presenter: Iain Gardner, PhD, VP, Head of Translational DMPK Services, Certara

Could a SMILES string alone help us predict pharmacokinetics? Equipped with the right PhysChem property predictors and an in silico model of PK, discovery and translational scientists can now look ahead to animal and human ADME from the earliest stage of compound design. Explore the existing tools and what’s on the horizon with Iain Garder, PhD, Sr. Scientific Advisor and Head of Translational Science.

Location: The Pavilion Hub East

1:30-1:45 Welcome, Goals, and Session Overview
Piet van der Graaf, PharmD, PhD, Senior Vice President, Quantitative Systems Pharmacology

MIDD has become a continuum of various modeling approaches impacting decisions throughout the drug development life cycle. Organizations are looking to optimize resources and industrializing MIDD has a role to play in optimizing processes. This track shares different approaches across the MIDD spectrum highlighting how strategy, expertise, technology and insights together deliver value for development organizations large and small.

1:45 – 2:00 Evolving regulatory landscape for MIDD – Impact of the draft ICH M15 guidance
Rik de Greef, MSc, Senior Vice President, Global Quantitative Sciences Services, Certara Drug Development Solutions

The recent draft ICH M15 guidance for MIDD outlines the regulatory expectations for use of MIDD throughout program lifecycles. What does this mean for your program? We will discuss the importance of Regulatory Interaction, Model Evaluation, Model Analysis Reporting, and Documentation for regulatory interactions and submissions.

2:00 – 2:30 Leveraging QSP and PBPK Modeling to Guide Development Strategy
Amitava Mitra, Executive Director Clinical Pharmacology, Kura Oncology

Mechanistic modeling approaches, including Quantitative Systems Pharmacology (QSP) and Physiologically-Based Pharmacokinetic (PBPK) modeling, offer valuable tools for dose guidance in novel combination oncology therapies. By integrating pharmacokinetics, pharmacodynamics, and tumor biology, these models enable the prediction of optimal dosing regimens, minimizing toxicity while maximizing therapeutic efficacy. This talk will present case studies demonstrating how QSP and PBPK modeling inform dose selection and support clinical decision-making in the development of innovative cancer treatments.

2:30 – 3:00 Regulatory experience with PBPK in DDI evaluation of a novel TROP2-directed antibody-drug conjugate, datopotamab deruxtecan
Akiko Watanabe, Director, Daiichi Sankyo

Physiologically based pharmacokinetic (PBPK) modeling has proven instrumental in assessing drug-drug interaction (DDI) risks for antibody-drug conjugates (ADCs) sharing the same cytotoxic payload. By integrating preclinical and clinical data, PBPK models can predict the pharmacokinetics of the released payload, enabling the evaluation of potential DDIs without the need for dedicated clinical trials.

Location: The Forum

1:30-2:00 Increasing Productivity of Pharma R&D by Breaking Down Data Silos
Presenter: Martin Snyder, President, Certara Data Science Software

Low incoming data quality is the top pain point for pharmaceutical companies when testing and researching new drugs. This problem is only getting worse because the amount of raw data collected during clinical research is exploding. Incoming data – from automatic collection like smart watches to self-assessments to medical imaging – is all being produced and delivered by different sources, causing a unification problem. Creating a coherent data stream from all the noise drastically slows down the pharma R&D process, but it is a necessary step before researchers can get to the analytics stage. Martin Snyder will break down the problem and how the industry can address it by validating data early and often, creating data transfer agreements between vendors and sponsors, and breaking down barriers that prevent the free flow of data between stakeholders.

2:00-2:45 Optimizing Clinical Metadata Management: Sponsor Benefits of Pinnacle 21 Enterprise CMDR for Statistical Programming
Presenters: Himaja Surapaneni, MS, Principal Statistical Programmer, SDTM SME, Alnylam Pharmaceuticals ; Radhika Kale, MS, Associate Director, Statistical Programming Standards, Alnylam Pharmaceuticals; Andy Illidge, Director Technical Solutions, Data Science, Statistics and Epidemiology, Alnylam Pharmaceuticals

The implementation of Pinnacle 21 Enterprise (P21E) Clinical Metadata Repository (CMDR) provides significant advantages for sponsors in managing clinical study metadata, particularly in the realm of data standards and statistical programming. CMDR centralizes metadata specifications, ensuring consistency across studies and improving traceability, version control, and governance of standard definitions. By streamlining specification management, sponsors can enhance compliance with CDISC standards while reducing inefficiencies in study setup and execution. The repository enables seamless updates to metadata, mitigating risks associated with version discrepancies and ensuring alignment with regulatory expectations.

CMDR’s API integration capabilities enhance automation and interoperability across statistical programming environments. By leveraging APIs, sponsors can access metadata directly using SAS, R, or other statistical software and use that metadata in dataset generation. The ability to programmatically interact with CMDR empowers sponsors to maintain high data integrity while expediting analysis and submission timelines, ultimately driving operational efficiencies in clinical trial execution.

This presentation primarily focuses on the sponsor-developed processes using Specification Management functionality for the development of SDTM and CT Custom Standard Specs, metadata governance, and API Integration for use in SDTM macros.

Location: The Pavilion Hub West

1:30pm-2:05pm | Navigating Evolving Expectations and the Totality of Evidence
Presenters: Fran Brown, PhD, Global Head of Drug Development Science, Certara; Geoff Fatzinger, PhD, Vice President, Regulatory Strategy, Certara

Regulatory agencies are increasingly emphasizing a Totality of Evidence (ToE) approach in drug development, shaping expectations for data integration and submission strategies. This session will provide an overview of recent guidance documents and policies that incorporate ToE principles, highlighting their implications for development strategy. Attendees will gain key insights into how these evolving regulatory expectations influence study design, evidence generation, and approval pathways, ensuring a more informed and strategic approach to drug development.

2:05pm-2:35pm | A Transformative Approach to Drug Development
Presenters: Noopur Singh Vice President, Marketing & Patient Affairs, Xentria; Tom Matthews, Vice President, Clinical Development , Xentria; Elliot Offman, BSc Pharm, MSc, PhD, Vice President, Clinical Pharmacology & Translational Medicine, Certara

In rare disease drug development, the limited patient population and ethical constraints often require a shift from traditional clinical trial paradigms to a more integrated approach—leveraging the totality of evidence. This session explores how translational research bridges preclinical insights with clinical application by incorporating diverse data sources, including in silico modeling, real-world evidence, and biomarker-driven strategies. Experts will examine how modeling and simulation informed dose selection, how non-traditional endpoints guided regulatory interactions, and how a learn-and-confirm framework streamlined development. Through the case study of XTMAB-16 for pulmonary sarcoidosis, panelists will discuss the challenges and opportunities of this approach, providing actionable insights for organizations navigating the complexities of rare disease drug development.

2:35-3:00pm | Leveraging Non-Traditional Data for Regulatory Success in Rare Disease Drug Development
Presenters: Jon Monteleone, Executive Director, Clinical Pharmacology & Safety Sciences, CPQP Lead for Approved Complement Medicines & LCM, Alexion, AstraZeneca Rare Disease Unit; Rajesh Krishna, PhD, Distinguished Scientist, Global Head of Certara Centers of Excellence

In rare disease drug development, the limited availability of traditional clinical data presents a unique challenge. This session explores how non-traditional data sources—such as real-world evidence, modeling and simulation, and patient registries—can be leveraged to drive regulatory success. Through a compelling case study, we will demonstrate how these innovative approaches played a pivotal role in achieving key development milestones and securing regulatory approval. Join us to discover how harnessing unconventional data can accelerate drug development and improve outcomes for patients with rare diseases.