Where life science
Collaborates
We are a global, not-for-profit members’ organization working to lower barriers to innovation in life science and healthcare R&D through pre-competitive collaboration.
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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.
To support the implementation of the FAIR guiding principles for the data management cycle by Life Science industry, through sharing best practices and provision of a FAIR Toolkit.
As the life sciences industry continues to transform digitally, the sector needs clear and practical guidance on how data and relevant metadata is captured and managed to foster greater collaboration and more effective partnerships. The FAIR guiding principles help to meet this need, but many companies are struggling to implement the guiding principles as discussed by Wise and co-authors (DOI:10.1016/j.drudis.2019.01.008). This practical need will be addressed by the development of the FAIR Toolkit which will consist of relevant methods and case studies.
The Pistoia FAIR Toolkit will include methods and case studies to support the implementation of the FAIR data management life cycle by life science industry. The methods will include selected tools, tips, FAQs, training materials and change management which will be illustrated by relevant case studies. The FAIR Toolkit will be assembled together on a user-friendly and freely accessible web site.
The project team will collect candidate content in a simple wiki and select the most relevant content to support implementation of FAIR by scientists in life science industry. This will lead to the specification, design and implementation of a FAIR Toolkit web site serving as a “one-stop shop”. This is expected to work much like the Pistoia UXLS Toolkit (uxls.org), which will be a useful reference for building the FAIR Toolkit website.
Method recapitulation is difficult and time consuming, within a company and even more across collaborating partners. A solution to store, search and retrieve a digital version of a method will improve scientist’s ability to retain institutional knowledge, reduce time for method development and improve method execution
Reproducibility of methods is expected to be significantly improved while time and resources to re-establish a method in a different lab will be drastically reduced.
From a cyber security perspective, a centralized storage location will create a much more resilient environment.
The project will achieve:
The transformation of text-based method descriptions into digital instruction sets for different analytical methods and instrument types, including a common digital format and an ontology for analytical chemistry methods.
The HPLC experts have identified a common set of HPLC parameters across different CDS and HPLC’s.
Semantic experts have built the common parameters into a semantic Data Model. The Allotrope Data Format is used to bring semantic description, result data and files together in one universal HDF5 container.
Pistoia Alliance announces start-up of a Centre of Excellence (CoE) in Artificial Intelligence and Machine Learning (AI/ML). This development is driven by our desire to support our members in the understanding and pursuit of innovative new AI/ML applications and solutions within Life Sciences R&D & Health.
The Pistoia Alliance believes that AI/ML has the potential to transform large aspects of the Life Sciences and Health workflows. On the other hand we believe that this transformation won’t replace the human mind required in the research scenario. Science requires interdisciplinary expertise and judgement that a machine cannot provide.
The Pistoia Alliance is currently working to establish the steps needed to turn the widespread adoption of AI/ML into a reality. We want to see how the greater community can help the industry overcome many of the obstacles it is currently facing.
The Centre of Excellence is organising events, webinars, and hackathons, which will cover a range of challenges aimed at kicking off AI projects or prototype AIs. This will help us to work out where the main challenges are, and to establish an adoption strategy that serves these needs. The Pistoia Alliance’s community also provides a virtual and physical co-working space, enabling life science professionals to share best practice and learn how best to apply AI, machine, and deep learning to R&D – wherever they are in the world.
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