Problem Statement
In vivo efficacy studies generate critical data for drug discovery, but the absence of agreed standards leads to fragmented, inconsistent, and difficult-to-reuse data sets. Current approaches rely on bespoke formats across pharma, CROs, and technology providers, making integration, regulatory submission, and AI-driven analysis inefficient and error-prone. While CDISC SEND provides a proven framework for toxicology studies, no equivalent exists for efficacy studies — leaving a standards gap that slows research and reduces the value of pre-clinical data.
Idea Proposal and Value Proposition
By advancing practical, pre-competitive standards for in vivo efficacy data — aligned with CDISC SEND and piloted across real-world data sets — the project will improve data quality, interoperability, and regulatory and analysis readiness.
Contributing organisations will share costs and risks, gain early access to streamlined processes, enable more effective analytics (including AI), and be recognised as industry leaders shaping the future of preclinical R&D data standards
Patient Opportunity: faster translation of insights provides a quicker path to clinical research and potential patient benefit.
Help Shape the Future of Preclinical Data
Join leading industry partners in defining shared standards for in vivo efficacy studies. Connect with John Wise, Project Manager, to explore how your organisation can participate.
Targeted Outputs
- Establish a cross-industry community of practice on in vivo data standards.
- Define minimum data elements, terminology, and metadata for efficacy studies.
- Develop and pilot a draft data model aligned with CDISC SEND.
- Document use cases, benefits, and gaps to support eventual CDISC adoption.
- Position pharma, CROs, and vendors for more efficient data integration and regulatory submissions.
Example Use Case(s)
- Mapping in vivo Efficacy data to SEND format
- AI/ML-enabled meta-analysis of efficacy data across multiple studies.
- Regulatory submission of preclinical studies in harmonised format.
Critical Success Factors
- Funding
- An experienced, domain-aware, project manager
- Multi-company commitment (pharma, CROs, tech providers).
- Alignment with CDISC and regulators.
- Sustained community engagement.
Why This Is a Good Idea / Why Now
- More consistent representation of data in the in vivo efficacy domain – enabling FAIRness and better AI-enabled analytics and quicker regulatory submissions.
- AI/ML models are only as good as the data, now is the moment to address this gap before adoption accelerates.
Author
John Wise
Date Submitted
September 8, 2025
Strategic Priority
Deliver Data-Driven Value
Idea Originators
- Chris Butler, AbbVie
- Tim Letby & Simon Marriott, AstraZeneca
- Andrew Smith, Benchling
- Caroline Pfanzelt, Boehringer-Ingelheim
- Ben Sefing, Merck
- Stefanie Wanka, Novartis
- Anastasios Moresis and Olivier Roche, Roche
- Julie Morrison, Rockstep Solutions
- Sasker Grootjans, UCB