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.
A notation plus open source editors and tools to use it
The increase in sophistication of biotherapeutics research has revealed a gap in informatics methodology whereby small-molecule technologies are too unwieldy for representing large molecules, and sequence-based technologies are incapable of representing the growing variety of biomolecular modalities that include modifications such as unnatural monomers (amino acids, nucleotides) and other chemical modifications (e.g. bioconjugates).
The project has published the HELM notation and created a suite of open-source tools all free to all: a toolkit, a webeditor and an antibody editor.
There has been wide adoption and HELM is included in the technical guidance for ISO 11238 TS 19844.
We maintain a community to tackle new challenges that arise as HELM expands its reach. We are currently developing our documentation of best practices, extending our guidance around monomer sets and ensuring all adopters are supported.
The aim of the Unified Data Model (UDM) project is to create and publish an open and freely available data format for storage and exchange of experimental information about compound synthesis and biological testing.
Without UDM there is a lack of consistency in data formats coming from different systems and this makes it difficult to share experimental information. At best, time and resource is taken up trying to interpret different data formats, at worst valuable data is ignored because it can’t be shared and understood.
We will create and publish an open and freely available data format for storage and exchange of experimental information about compound synthesis and biological testing. We aim to make UDM an industry-wide data standard used to facilitate data sharing and collaboration.
Collaboration across vendors and Pharma customers has been the key to building a set of requirements that have driven the development of UDM. The project started with the file format used by Elsevier to upload chemical reaction data into Reaxys, through listening to representation of the community at the project team, requirements were gathered and the format built .
Establishing best practices and use cases for the application and management of ontologies and their mappings for Life Science industry
Ontologies can include hierarchical relationships; taxonomies; classifications and/or vocabularies which are becoming increasingly important for support of research and development. They have numerous applications such as knowledge management, data integration and text mining where researchers need to analyse large quantities of complex data as part of their daily work.
The Ontologies Mapping Project will help users to select top performing tools, methodologies and services for mapping and visualisation of ontologies, to understand ontology structure, potential overlaps and equivalent or similar meaning. The impact of this project will be to help users to better integrate, understand and analyse their data more effectively through better usage of public ontologies and mappings between them.
The project has built a Community of Interest of considerable size and influence in the ontologies field. It has delivered a set of guidelines for use as a checklist to facilitate the selection of ontologies for application. The Ontologies Guidelines for Best Practice are available on a publicly accessible wiki:- https://pistoiaalliance.atlassian.net/wiki/display/PUB/Ontologies+Mapping+Resources
We have evaluated ontology mapping tools and algorithms through and organised the phenotype track of the Ontology Alignment Evaluation Initiative (http://oaei.ontologymatching.org). We are now collaborating with EMBL-EBI to demonstrate a prototype ontology mapping service for public ontologies in the phenotype and disease domain, which is being extended to the lab analytics domain.
