Join us for another IDMP Ontology webinar where we discuss important achievements of our IDMP-O project such as industry IDMP-O survey key findings, updates on the EMA PMS Data Alignment Proof of Concept and the CMC Batch Tracking, Site, and Product Data Proof of Concept. These sessions are designed to improve data alignment and interoperability across the pharmaceutical industry.
Agenda
IDMP-O Survey Report Discussion: Analysis of industry insights and feedback on IDMP-O – Dominik Gigli/ Raphael Sergent
EMA PMS Data Alignment Proof of Concept Update – Fabian Muttach / Raphael Sergent
CMC Batch Tracking, Site, and Product Data Proof of Concept Update
Phase 4 Plans (2025): Outline of future initiatives for the year 2025 – Aditya Tyagi
The report examines the status of the implementation of Identification of Medicinal Products (IDMP) standards in global pharma and the role of the IDMP Ontology in accelerating digital transformation.
The European Medicines Agency (EMA) continues to advance the implementation of IDMP standards, a regulatory framework that will become mandatory across the EU, with the FDA likely to follow close behind. Failure to implement IDMP could lead to a number of risks including regulatory penalties, inefficiencies in operations and threats to patient safety.
Key findings from the report:
43% of companies said they plan to implement IDMP Ontology this year
89% of companies recognize the long-term value of IDMP beyond compliance
Pharmacovigilance is no longer seen as key to the success of IDMP even though it was its original purpose
The survey was conducted by the Pistoia Alliance, ACCURIDS and MAIN5 and supported by the award-winning IDMP Ontology project with participants from Abbvie, Amgen, AstraZeneca, Boehringer Ingelheim, Bayer and Novartis.
Information exchange within and across organizations in the pharmaceutical industry is hampered by insufficient or ambiguous asset descriptions. These descriptions should ideally allow for validation, facilitation of discovery and promotion of interoperability. All of these have the potential to deliver significant gains for data exploitation and value delivery in the drug development pipeline, ultimately bringing better treatments to patients.
The remit of PGO, rather than mandate the use of a resource over another, is to enable clarity when declaring which controlled terminologies are used and why.
True to the FAIR principles of data management [1] and their use in the Pharmaceutical Industry [2], the PGO aims to reuse existing semantic resources (ontologies and controlled terminologies) as well as open source community software, rather than creating new ones.
The initial goal of PGO is to provide enough coverage to represent essential entities, most frequently used or referred to when exchanging data.
To create value and guide strategic decision-making in pharmaceutical and healthcare organisations, data needs to be Findable, Accessible, Interoperable and Reusable (FAIR) both by humans and machines. The objective of the Pistoia Alliance FAIR implementation Community of Experts (CoE) is to enable the implementation of FAIR data principles in the life sciences
As the life science industry increasingly relies on data-driven approaches, the adoption of ontologies has emerged as a strategic imperative to harness the full potential of data for enhancing efficiency and effectiveness. A key strategic priority of the Pistoia Alliance, a non-profit organization fostering collaboration in life sciences and healthcare, is to Deliver Data Driven Value. As part of this effort, the Alliance leads multiple projects targeting semantic data with oversight and governance provided by in-house experts to provide a holistic view and ensure that deliverables are aligned and interoperable. This poster outlines some of these initiatives: IDMP-O, CMC Process Ontology, Clinical Operations Ontology, and Pharma General Ontology
This project aimed to establish best practices for data visualization, support life science research, and identify opportunities for communicating and implementing these best practices.
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 FAIR Maturity Matrix is a descriptive (self-)assessment instrument for Leadership and Communities of FAIR data practitioners evolving in the life-sciences. It provides a frame for actionable conversations, aligning stakeholders towards shared FAIR implementation goals.
To create value and guide strategic decision-making in pharma and Life Science companies, data needs to be Findable, Accessible, Interoperable and Reusable (FAIR) both by humans and machines. The objective of the Pistoia Alliance FAIR implementation project , from its inception in 2019 to today, is to enable precompetitive instruments for the implementation of FAIR data principles.
Our project aims to develop a pharmaceutical (CMC) process ontology, based on the ISA88/95 framework. This ontology will serve to standardize laboratory and plant production process recipes, and in turn, establish standardized definitions. It will also facilitate digital technology transfers, and integrate with execution systems to capture structured process data for material lot genealogy tracking. This will lead to streamlined technology transfers, advanced process analytics, and ultimately, enhance efficiency and transparency throughout the pharmaceutical production lifecycle.
The Pistoia Alliance has successfully completed the Methods Database project enabling digital transfer of analytical High-Performance Liquid Chromatography (HPLC) methods and results between chromatography data systems (CDS) via the ZONTAL central data storage system using a standardized machine-readable data format which transforms methods from paper documents to digital instructions. During this webinar we will revisit the project and look at how implementation of the Methods Db is going as well as demo the workflow:
Agenda
An update on the Implementation of the Methods Database at GSK
Virtual combinatorial chemical spaces have become valuable in drug discovery. This study examines the composition of the recently published “eXplore” space, which includes around 3.9 trillion virtual product molecules. Several methods, such as FTrees, SpaceLight, and Space-MACS, were used to evaluate the utility of eXplore in retrieving novel chemistry around approved drugs and common Bemis-Murcko scaffolds. A subset of 55 million virtual compounds, representing a commercially attractive and diverse selection of eXplore, was fully enumerated. AI-assisted tools, including ligand-, target-, and fingerprint-based searches, were applied to this subset, revealing new insights into chemical diversity around clinical and lead compounds. Further chemical space analysis, including 2D fingerprints, 3D shape, and electrostatic analyses, demonstrated that eXplore offers a highly diverse chemical space compared to other vendor sets.
Speaker
Peter Maas, Director of Scientific Consulting, eMolecules
Peter E.M. Maas graduated from the Rotterdam University of Applied Sciences in Organic Chemistry. He joined eMolecules (formerly Specs) after completing his internship at Shell Research and Technology Centre, Amsterdam, on the synthesis of ligands for homogeneous catalysis. At eMolecules he specialized in cheminformatics, medicinal chemistry, and early drug discovery. He coordinated numerous research collaborations with universities, pharmaceutical and biotech companies involving chemical and spectral data, solubility, stability for software development, and drug discovery on diverse targets and diseases topics. As Manager Lead Development, he was responsible for all services and expertise within eMolecules to develop lead candidates for drug discovery: library design, medicinal chemistry, formulation studies and patents. This led to the filing of several patents and the establishing of two spin-off companies. In September 2024, he assumed the position of Director of Scientific Consulting.