Who We Are
We are a not-for-profit organization with over 200 member companies across the life science ecosystem collaborating across more than 25 projects and communities to advance science. Our members include 18 of the top 20 global pharma companies by revenue, patient-led research groups, technology and solution providers, academic institutions, publishers, and commercial research groups.
Our Mission
Our mission is to lower the barriers to innovation in Life Sciences. Our unique framework for collaboration enables organizations across the industry to work together to solve common issues thus eliminating barriers to innovation.
Advantages of Membership
Ability to collaborate, risk-free, with experts from other companies in our communities and projects to solve industry-wide issues and deliver tangible results to your user communities. Build a network of peers and mentors across the industry and across the world. Enhance your skills and career progression with professional development through involvement in our educational programs, events and programs.
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Latest Projects
Our projects transform R&D innovation through pre-competitive collaboration. We bring together the key constituents to identify the root causes that lead to R&D inefficiencies. We develop best practices and technology pilots to overcome common obstacles. If you have an idea for a project, please get in touch, by email, at projectinquiry@pistoiaalliance.org.
Project one: Clinical Trial Environmental Impact Project
The Clinical Trial Environmental Impact project wishes to develop a dynamic model that compares the carbon footprint of a clinical trial in traditional, hybrid and fully decentralised settings.
There is growing pressure from patients, healthcare payers, and governments to reduce the environmental impact of life sciences. In the future, we expect new legislation that will require pharmaceutical and contract research organizations to measure and report on the environmental impact of their operations.
The Pistoia Alliance believes that an immediate opportunity is the assessment of the impact that clinical trials have on the environment. Evaluation of the carbon footprint of clinical trials is rarely evaluated despite it being very visible. More pharmaceutical companies are moving towards the model of Decentralized Clinical Trials (DCT) and currently, it is not known if this new approach will have a greater or lesser impact on carbon footprint. A robust and accurate methodology for assessment is needed and will require collaboration amongst a broad mix of experts from both the life sciences and sustainability fields.
We propose to lead a coalition of experts to build a dynamic model that:
- Identifies the key drivers for carbon footprint in a clinical trial and develop metrics for each with estimates of each for a ‘typical’ clinical trial
- Users of the model will have the ability to turn on and off key parameters such as patient engagement, DCT, and patient diversity activities in order to see the impact of each on carbon footprint.
Project two: Natural Language Processing (NLP) Use Case Database Project
This collaborative project was launched to create a bottom-up qualitative Natural Language Processing (NLP) Use Case Database, to allow NLP practitioners in pharma companies to share successes and failures with their peers. Narrowing down successful use case scenarios will lead to less experimentation and higher success rates for new NLP initiatives.
Natural Language Processing offers great promise to improve efficiency and understanding of relationships and extract meaning from vast amounts of unstructured text. Pharma companies apply NLP methods in hopes of automation and insight generation. NLP experts have been investing significant resources in developing tools to address multiple business cases throughout the pharma industry in domains as varied as R&D, pharmacovigilance, and manufacturing, however, success seems very use case-specific.
Although Natural Language Processing algorithms have matured quite a bit during the past years, practical value for most NLP pilots tends to be poor, and very few NLP-driven projects are seen through to production. Exceptions are typically topics with good metadata quality, large training sets and willing business colleagues to verify results and a serendipitous combination of technical expertise and suitable use cases.
This type of knowledge is of value to share in a pre-competitive manner among Pistoia Alliance members. A simple database could contain characterization of use case, data characterization, pipelines & algorithms used, quality criteria, outcomes, and comments.
The team will deliver the following:
- A bottom-up qualitative NLP Success Failure Database with 50-100 Use cases
- Agreed annotations of NLP use case methods and success/failure criteria
- Collaborative insight into why NLP use cases may fail or succeed with an industry-wide view
Project Funders
Project three: IDMP Ontology Project
A well-defined ontology that bridges between regional and functional perspectives on common substance-related data objects and global and scientifically objective representations is required. The goal of our project is to build an IDMP Ontology that enables deep, semantic interoperability based on FAIR principles to enhance and augment the existing ISO IDMP standards.
The European Medicines Agency (EMA) will be the first health agency to mandate compliance with ISO IDMP (Q4, 2024), with the FDA not far behind. Governance of essential IDMP standards and implementations is not assigned to a specific, overarching governing body. Diverging implementations of IDMP across geographical regions and jurisdictional domains are already causing inconsistencies in the interpretation across implementing organizations. Given that there is no semantic alignment between regulatory bodies, there exists a risk that regulatory compliance needs will lead to large integration and interoperability costs and that the benefits from IDMP in drug safety, innovation, and other areas will not be fully realized. Rather than concentrating on the discovery of new medicines, organizations will be struggling with data issues, e.g., the need to map product data across the organization, throughout the product lifecycle.
Due to our robust framework for pre-competitive collaboration. The Pistoia Alliance was selected to manage this initiative with the goal of creating an ontology that demonstrates added value to the ISO IDMP standards for data usability across organizational boundaries and regulatory jurisdictions. We have pulled together a core team consisting of Pharmaceutical stakeholders, regulatory bodies, standards organizations, non-profit groups, and solutions providers for this project.
The key objectives for the project include:
- Provide a digital, machine-processable standard.
– The Pdf document provided by EMA is not enough as different groups implement it differently - Solve ambiguities of the ISO IDMP standards enabling feed improvements back to ISO through systematic reviews
- Bridge different views with ONE product data model between internal pharma departments and between industry groups
- Provide a vendor-agnostic, and open-source model. The ontology is fully standards-based without any proprietary aspects
- Reduce implementation effort through a common core
