How to Build a Measurable Evidence Engine for Cell, Gene and RNA Therapies

As cell, gene and RNA therapies progress into later stages of development, teams face increasing difficulty assembling consistent, traceable evidence from diverse data sources to support timely program decisions. Multimodal data generated across assays, sites and platforms are frequently fragmented, forcing teams to rely on manual integration and limiting confidence in governance updates and regulatory narratives. This webinar examines how a measurable evidence approach can replace disconnected workflows and support decision-making at scale.

The featured speakers will explore how structured data ingestion, cataloging and governance can be aligned to support advanced modalities, with particular attention to trusted research environment patterns that enable controlled access, collaboration and auditability. Attendees will learn how these foundations support reproducible analysis while maintaining compliance expectations across internal and external stakeholders.

The webinar will also discuss how natural-language querying and standardized AI and machine-learning workflows can reduce time spent on data preparation and enable faster exploration across time points and modalities. Real-world use cases will illustrate how teams can move from raw data to decision-ready evidence without relying on ad hoc scripts or manual reconciliation.

Register for this webinar to learn how cell, gene and RNA therapies teams can operationalize multimodal evidence to improve decision velocity, traceability and governance readiness.

Speaker

Todd Oakland, PhD, SVP, GM Biopharma Rx/Dx, DNAnexus

Todd Oakland serves as the Senior Vice President and General Manager of Biopharma Rx/Dx. Prior to joining DNAnexus, he was Vice President and Product Lead for Precision Oncology at ConcertAI, where he led real-world data strategy and product development across pharmaceutical and diagnostics partnerships.

Before ConcertAI, Todd held multiple roles at Aitia, including Vice President of Customer Success and Executive Director of Real-World Evidence and Analytics, helping to advance the company’s causal AI platform for life sciences applications. He also spent time at Optum leading engagements on the RWE team, focusing on pharmaceutical clients with large-scale healthcare data and analytics.

Todd began his career in translational science and academia, with roles at the University of Chicago and Harvard T.H. Chan School of Public Health. He holds a PhD in Virology from the University of Chicago, an MPH in Quantitative Methods from the Harvard T.H. Chan School of Public Health, and a BS in Molecular Biology from Purdue University.

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