European Pharmacopoeia publishes new data quality framework

A new data quality framework has been released by the European Pharmacopoeia (Ph. Eur.) to support pharma manufacturers with their digital transformations.

The new general chapter on Quality of data (5.38) appears in Issue 12.3 and is set to come into force on 1 July.

It provides a framework for managing the quality of digital data, ensuring that it is robust, reliable and well-governed across its entire life cycle.

Specifically, the new chapter addresses data of digital origin and complements existing Ph. Eur. chapters that support digital and technological transformation: Chemometric methods applied to analytical data (5.21), Multivariate statistical process control (5.28), Design of experiments (5.33), Chemical imaging (5.24) and Process analytical technology (5.25).

General chapter 5.38 introduces:

• General concepts of data, data governance and quality dimensions, such as accuracy, bias, completeness and reproducibility
• The Extract-Transform-Load (ETL) process as a framework for managing data throughout its life cycle
• The role of subject matter experts (SMEs) in ensuring data is fit for purpose, especially when used in automated decision-making systems
• An overview of data sources (eg, sensors, databases and cloud platforms) and data formats for storage, including open formats.

Publication of this latest chapter by the Ph. Eur. aligns with recent moves by the UK’s MHRA and US FDA to improve how those regulatory agencies assess data received from drug developers about their clinical trials.

The MHRA is planning to roll out a package of major changes alongside new clinical trial regulations being enforced in April. The new framework includes speeding up assessments and improving use of early safety data when evaluating studies to ensure they meet MHRA standards.

Meanwhile, new draft guidance from the US Food and Drug Administration (FDA) recommends appropriate use of Bayesian methodologies in trials, supporting more efficient studies and use of available data, ultimately shortening the time for patients to receive treatments.

This method has benefit specifically in studies focused on rare or paediatric indications, which typically have smaller patient populations. FDA has issued this guidance to fulfil its commitment in the Prescription Drug User Fee Act (PDUFA) VII.