Big pharma experts join forces to drive automation of data workflow

By Nick Taylor

- Last updated on GMT

(Feodora Chiosea/iStock via Getty Images Plus)
(Feodora Chiosea/iStock via Getty Images Plus)

Related tags: Merck kgaa, Bayer, Novartis, Roche, Glaxosmithkline, Automation

Leaders from some of the industry’s most notable companies are working together to streamline and automate IDMP workflow and come up with various standards.

Experts from Bayer, Novartis, Roche, GlaxoSmithKline, and Merck KgaA have joined forces to drive the semi-automation of the Identification of Medicinal Products (IDMP) workflow.

IDMP is a suite of the International Organization for Standardization standards intended to enable the identification of medicinal products. Starting next year, companies will need to include IDMP structured data when sending post-authorization variation applications to the European Medicines Agency (EMA).

The EMA’s use of IDMP has highlighted concerns about differences in the terminology used to describe products and active substances. With the inconsistencies making it hard to correctly align information, the not-for-profit pre-competitive collaboration organization the Pistoia Alliance has begun working with a clutch of leading pharma companies on a new IDMP ontology.

Gerhard Noelken, project lead, Pistoia Alliance

Currently, a considerable amount of manual work and data processing is required to meet the IDMP mandate – redirecting scientists away from development. This new IDMP ontology will help to semi-automate the IDMP workflow, supporting R&D organizations in standardizing data and terminology​,” said Gerhard Noelken, project lead of the Pistoia Alliance.

 By creating the ontology, Noelken thinks the Pistoia Alliance and its collaborators at Bayer, Novartis, Roche, Merck KGaA, and GSK can ensure everyone is speaking the same language and that information held in existing data sources is fully compatible.

The first step toward the realization of that goal is already underway, with the Pistoia Alliance and the pharma company experts now developing a minimal viable product (MVP) to demonstrate the value of having an ontology-based on the IDMP standard. Noelken hopes to have the MVP ready in the third quarter of 2022 and to use it as a launchpad for the realization of the ultimate goal of the project.

The project's end goal is a common ontology that will power the automation of IDMP to be used across the industry. This will increase semantic alignment between regulatory bodies and development organizations, decrease integration and interoperability costs, and allow the best use of data for patient safety​,” Noelken said.

In working toward that end goal, the Pistoia Alliance will draw on its experience with similar data implementation projects, such as its FAIR Toolkit to improve data management and data sharing, and the framework for pre-competitive collaboration that is at the heart of its operations.

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