Pre-Competitive Real-World Benchmarking of AI Solutions
We propose establishment of a system for benchmarking of AI tools on private assets (models and data) used for a multiplicity of use cases along the drug discovery, manufacturing, and clinical research value chain. The proposed vendor-neutral system should include benchmark data sets, specifically designed for the named use cases, evaluation metrics, and infrastructure for secure compute and IP protection, that would allow for benchmarking of AI tools without disclosure of the model code and the test data sets.
Agent-Agent Communication Protocol and AI Agent Standard Specs
If team A develops an AI agent application agent-A, and team B develops an AI agent application agent-B, what is the minimal set of information that agent-A and agent-B should exchange such that these two AI agents can work together on the same project? To address this question, we need a standard AI agent-agent communication protocol.
Developing Practical Use Cases to Reduce Carbon Emissions of Pharmaceutical Clinical Trials
Following the ‘Carbon Footprint of Decentralized Clinical Trials’ project run by Pistoia Alliance members in collaboration with Sustainable Healthcare Coalition members in the industry Low Carbon Clinical Trials (iLCCT) consortium, the first version of the Clinical Trial Carbon Calculator “Eco Design” tool is to be finalized by the end of 2024 and will be accessible to pharma companies and suppliers.
Minimal Metadata Set for Repurposing Non-Clinical In Vivo Data for Biomedical Research
In the field of biomedical in vivo research, data sharing and repurposing are not commonly practised. One critical element for enabling data sharing and repurposing is the provision of metadata that well describes the raw or primary data.
BAO Update
The current ontologies available to support annotation of experiments and assays (BAO,AFO) don't suffice yet to enable experiment data interoperability and their reusability.
Standard API Protocol For Ontology
Organisations are increasingly working to standardised ontologies and terminologies to increase the interoperability of data as part of their FAIR data strategy.
Synthetic Data in Medical Imaging
Artificial Intelligence (AI) models have been shown to have impressive capabilities in the medical image analysis domain with potential to assist clinicians in their everyday tasks, from the diagnosis to disease monitorisation and surgical planning procedure, thereby enhancing patient care.
Instruments and Equipment Inventory Ontology
The problem to be solved is the lack of an ontology and/or standard vocabularies in instruments and equipment inventories, which makes the categorizing and querying of these systems difficult.