A collaborative project with Allotrope Foundation to replace manual, error-prone descriptions of analytical methods with standardized, machine-readable digital methods. The digital methods will be built as a reusable, vendor-neutral Allotrope Simple Model (ASM) so they can be exchanged between systems, automated, and linked directly to their results.
Develop and maintain a community-governed, open-source library of converters that transform laboratory instrument outputs into recognized open data standards, eliminating duplicated effort across the industry, advancing FAIR data, and accelerating AI/ML-enabled R&D
A multi‑stakeholder initiative to create a SEND‑aligned, FAIR‑ready framework that harmonizes in vivo efficacy data across pharma, CROs, and technology providers. The project will deliver interoperable, analysis‑ready, AI/ML‑enabled datasets that address a critical standards gap in non-clinical R&D.
Develop comprehensive benchmarks for Natural Language data mining and Scientific Chat applications to facilitate the rigorous evaluation of Large Language Model (LLM) performance across key stages of the data-to-insight pipeline in pharmaceutical R&D, ultimately supporting more effective deployment of AI in drug discovery.
The Chemical Exchange Format Committee provides a neutral forum where pharma companies, software vendors, and standards owners can collaboratively tackle chemical data formats and drive standardization.
The aim of the Minimal MetaData Set (MNMS) project is to establish a collaborative platform connecting biopharma companies, researchers, vendors, and regulatory bodies. This initiative aims to demonstrate that sharing a harmonised minimal metadata set (MNMS) together with raw locomotion data enables fully reproducible analyses across several pharmaceutical partners. We remove biological and protocol variability and focus on the value that rich, FAIR‑compliant metadata bring to data reuse.
PS2 is an open, vendor-neutral standards initiative for life sciences safety management spanning pharmacovigilance, vaccine safety, and medical device vigilance, designed to cut implementation costs, ease regulatory compliance, and drive innovation through modular, interoperable technology ecosystems.
In Vitro Noval Alternative Methods (NAMs) are human cell-based assays and systems used in biomedical research which represent human physiology, predict clinical outcomes and and reduce, replace or refine the requirements for animal testing in drug discovery.
This project built a solution for Informed Consent in clinical trials and implemented key components of decentralized digital identities
This project established best practices and tool recommendations for the application, management and mapping of ontologies in life sciences
This project developed and published best practice guidelines for the storage of collected sensor-generated data from remote modelling technologies
This project generated novel Ab structures and addressed the need for improved Ab structural data sharing to accelerate drug discovery