The great ISO IDMP implementation challenge: Are companies finally ready?
Even now, after a decade of run-up, pharma’s readiness to implement and harness ISO IDMP standards still varies wildly, as does companies’ relative maturity in supporting FAIR data principles, geared to making data more Findable, Accessible, Interoperable, and Reusable – ideals advocated by Pistoia Alliance, a non-profit industry coalition working to lower barriers to innovation in life sciences and healthcare R&D through pre-competitive collaboration.
The Alliance’s IDMP-Ontology (IDMP-O) project aims to create a shared ontology (a representation of data properties and the relations between them), to encourage uniform adoption of the IDMP standards and, by extension, consistent information exchange.
Given such initiatives, and with renewed regulator momentum around ISO IDMP implementation internationally (particularly in Europe, but also the US and Canada), MAIN5 recently partnered with Pistoia Alliance and data registry specialist Accurids to conduct new benchmark research around companies’ readiness to harness the standards, and surrounding frameworks, in earnest.
Ambitions are high, but barriers are higher
Large pharma companies now generally have good awareness of the value of IDMP-based product data standardisation as part of wider process digitalisation ambitions, the survey confirmed. More than 70% of those surveyed identified IDMP’s value as an enabler of cross-functional data integration; only 11% saw compliance as the primary goal of IDMP projects.
Companies generally plan to integrate IDMP data from Regulatory, Manufacturing, Pharmacovigilance, Supply Chain, and Quality functions within the next three years. Research, (pre-) Clinical, and Commercial data integration will follow in the mid-term (within five years). This phased approach indicates that companies are initially prioritising data that supports regulatory submissions and compliance, followed by broader data integration to support product development and commercial strategies to maximise the benefits of IDMP.
As things stand, however, product data management continues to pose a challenge for companies across the board. The benchmark study identified particular issues with manual data collection, data silos, and a lack of data integration across systems. An unclear source of truth and insufficient use of trusted external sources were also flagged as barriers to harnessing product data more strategically.
Those actively striving towards more seamless data integration across and between functions felt that a lack of resources and issues with ‘ownership’ were the main barriers to achieving this (indicated by 44% and 41% of respondents), beyond a current lack of data standardisation (the main obstacle, cited by 56%). Surprisingly, the quality of data (and therefore its usefulness) was ranked below these factors (cited by 33%).
Making more of master data: The perceived importance of an agreed ontology
When asked if companies currently use IDMP as the master data model for their product information, many respondents were unsure how well aligned their existing model is. Just 40% felt confident that they possess an IDMP-compatible model, although 75% use IDMP to guide product information. This is one of the gaps addressed by Pistoia Alliance’s IDMP-O project, in that it allows the exact measurement of how compatible existing data models and ambitions are with IDMP.
Promisingly, 43% of the large pharma companies taking part in the benchmark research expressed a willingness to take IDMP-O into production within their organisations within the first year of its release. Although an encouraging observation, many of the organisations that participated in the survey are inherently closer to IDMP-O than others in the industry, so the finding may not be representative.
Respondents were then invited to express, in their own words, where they anticipated deriving the most value from IDMP-O. Their open-ended responses confirmed good awareness of the ontology’s strategic benefits, including the associated scope to enhance the integration and exchange of product data - with regulators and industry partners, among other stakeholders.
Operationally, respondents recognised that the Pistoia Alliance ontology supports cross-functional alignment on data ownership, standardisation of data definitions, and adoption of a shared data model to enable system interoperability, and improve overall data quality. These factors pave the way for improved efficiencies in data management, decision-making, submissions, and compliance. There is still work to be done before companies can harness those benefits, however.
Renewing IDMP commitment in 2025
Where early enthusiasm around IDMP programmes had waned in response to slow progress from EMA in Europe towards clarifying specific requirements, reigniting momentum behind IDMP-based projects should be a priority now - both among life sciences companies, and the supporting vendor community.
A raft of recent developments will help companies define concrete next steps and avoid potential rework. These include the EMA’s go-live of the Product Lifecycle Management portal (with Product Management Services and electronic application forms), as well as improved clarity on implementing SPOR services and integrating with EMA systems and processes.
Certainly, for companies with larger product portfolios, advanced technological capabilities will be needed to efficiently prepare data in bulk for what could be thousands of registrations. Manual updates per product by re-entering data in the PMS system is not feasible.
Defining the right strategy, implementing supportive system capabilities, recruiting, and training a workforce to collect, transform, and submit data according to specific requirements is a significant undertaking that requires careful planning and execution. Doing the real work now will ultimately pave the way for a more sustainable future for healthcare, underpinned by a more consistent and efficient way of managing pharma product information.
