Current Projects
In Vitro NAM Data Standards
We propose to develop harmonized standards for describing animal alternative methods, their characterization, and develop best practices for management and analysis of data.
We propose to develop harmonized standards for describing animal alternative methods, their characterization, and develop best practices for management and analysis of data.
The goal of the system is to make it easier for regulators and other stakeholders to exchange information about substances in medicines, supporting scientific research on the use and safety of the ingredients in medicinal products.
The goal of the In Vitro Pharmacology project is to develop a shared data template that standardizes description vitro methodologies.
The use of Large Language Models such as GPT-4, presents a transformative opportunity for pharmaceutical R&D, particularly in target discovery and validation.
This project aims to convert unstructured assay protocol descriptions into a high-quality FAIR data set, and create standards for this information.
The project goal is to build an IDMP Ontology that enables deep, semantic interoperability based on FAIR principles to enhance and augment the existing IDMP standards.
This project will develop and publish key regulatory guidelines associated with the use of social media as real-world data to produce real-world evidence.
This project will provide a core framework to create interoperability between FAIR data sets across the pharmaceutical industry.
The project wishes to develop a dynamic model that compares the carbon footprint of a clinical trial in traditional, hybrid and decentralised settings.