The CMC Process Ontology is released. But how do we get scientists to adopt it?
Building the ontology was never the hard part, but getting scientists to use it is.
AI investment hits a four-year high as life sciences labs’ biggest barrier shifts from capacity to culture, Pistoia Alliance data finds
AI is now a top investment for 76% of respondents, up from a 60–63% plateau since 2023 – as a lack of leadership prioritization overtakes workload as top barrier to digital transformation
Real recipes don’t always develop the way the standard suggests
ISA-88 says recipes flow top-down, but real development often runs bottom-up. The CMC Process Ontology has to carry both.
Building a future with streamlined preclinical data submissions
One in vitro assay, reported a dozen ways. The Pistoia Alliance is building standardized, machine-readable data structures for NAM and pharmacology assays and testing them on real data.
Is Your Organization a Data Junkyard or a Data Marketplace?
From junkyard to online store: the FAIR Maturity Matrix gives your organization a common language to measure, communicate and improve your FAIR data journey. What it is, how it works, and how to use it.
Existing toxicology data standards jumpstart in vivo efficacy standards
In vivo efficacy data still arrives in bespoke formats. The Pistoia Alliance is developing in vivo efficacy data standards that build on SEND for toxicology data. The ultimate goal? Seamless data exchange.
Start with the Workflow, Not the AI
The important question isn’t what AI can do. It’s where it removes friction. Peter Hummel on why the strongest AI opportunities start with mapping the workflow, not the technology.
Finding Our Place in the Age of AI
AI can generate 20 journey maps in a minute, but someone still decides which matters. Aspen Snow on the UX researcher’s shift from conducting research to orchestrating understanding.
How the pharma industry built a common framework for medicinal product data
The IDMP Ontology turns the implementation of ISO IDMP Standards into consistent, connected, AI-ready data. See how collaborators built this foundation with the Pistoia Alliance.
What does the FAIR data ecosystem look like in 2036?
36 pharma and life science experts mapped the future of the FAIR data ecosystem in a room in London. Here is what they found, and what it means for your data strategy.
The global landscape and regulations continue to evolve. Are you ready?
The rulebook on controlled substances keeps widening, and the supply chain keeps shifting. The success of teams responsible for compliance and shipping lies in exchange and prevention.
The Blind Spots of Explainable AI
Once anyone can spin up an AI agent, the challenge isn’t explaining how AI decides, it’s designing what role it plays. Stijn Janssen proposes a new discipline: Actor Experience.