On 15 February 2019, the European Medicines Agency (EMA) and Heads of Medicines Agencies (HMA) published their Joint Big Data Taskforce’s summary report (available here) setting out recommendations for understanding the acceptability of evidence derived from ‘big data’ in support of the evaluation and supervision of medicines by regulators.

The Taskforce has sought to clarify the meaning of ‘big data’ within the medicines regulatory context, defining it within the report as: “extremely large datasets which may be complex, multi-dimensional, unstructured and heterogeneous, which are accumulating rapidly and which may be analysed computationally to reveal patterns, trends, and associations. In general big data sets require advanced or specialised methods to provide an answer within reliable constraints”.

The Taskforce was split into seven sub-groups, each focusing on different categories of datasets:

  1. Clinical trials and imaging;
  2. Observational (or ‘Real World’) data;
  3. Spontaneous adverse drug reports (ADR);
  4. Social media and mobile health;
  5. Genomics;
  6. Bioanalytical ‘omics (with a focus on proteomics); and
  7. Data analytics (this work is ongoing and cuts across the above six sub-groups; a further report is expected in Q1 2019).

The sub-groups were each asked, amongst other thing, to characterise their respective datasets; consider the specific areas where big data usability and applicability may add value; assess the existing competencies and expertise present across the European regulatory network regarding the analysis and interpretation of big data; and provide a list of recommendations and a ‘Big Data Roadmap’.

Collectively, the first six sub-groups produced 47 recommendations (set out in Annex III of the Summary Report), presented in order of priority (from urgent/required so that other actions can proceed, to low priority actions that typically related to immature fields or which validate other activities).

The report’s ‘urgent’ recommendations include (non-exhaustively):

  • Clinical Trial and Imaging: agreeing on data formats and standards for regulatory submissions of raw patient data; enabling the European regulatory network to have direct access to individual patient data during the assessment of marketing authorisations.
  • Observational Data: having mechanisms to drive standardisation and access to secondary care data; developing data sources in European member states that currently do not provide access to electronic health records for observational research; developing a framework to articulate for what ‘questions and contexts’ real world evidence may be acceptable for regulatory decision making across the product life-cycle.
  • Spontaneous ADR: evaluating new tools such as machine learning to leverage increased dimensions of data analysis.
  • Social Media and Mobile Health: facilitating the use of mobile health devices to record the efficacy and safety of medicines.
  • Genomics: optimising data sharing and linking of phenotypic and/or treatment parameters to genomic datasets; stimulating public sharing of genomics and clinical trial data; establishing requirements regarding data quality for regulatory submissions.
  • Bioanalytical ‘omics: providing clear guidance for validating bioanalytical methods suitable for the complexity of ‘omics’ techniques; harmonising used data (file) formats; ensuring appropriate assessment of regulatory submissions expertise in various disciplines (e.g. mathematical modeling, bio-informatics).

The Summary Report also details nine ‘core’ recommendations, which span multiple sub-groups.  These address:

  1. Data standardisation:

Promote use of global, harmonised and comprehensive standards to facilitate interoperability of data”.

  1. Data quality:

Characterisation of data quality across multiple data sources is essential to understand the reliability of the derived evidence”.

  1. Data sharing and access:

The development of timely, efficient and sustainable frameworks for data sharing and access is required. Further support mechanisms are needed to promote a data sharing culture”.

  1. Data linkage and integration:

Promote mechanisms to enable data linkage to deliver novel insights. Facilitate harmonisation of similar datasets”.

  1. Data analytics (this recommendation is provisional pending the full report by the data analytics sub-group):

Develop clear frameworks to enable the validation of analytical approaches to determine if they are appropriate to support regulatory decision making. Promote new analytical approaches for modelling of big data sets for regulatory purpose”.

  1. Regulatory acceptability of Big Data analyses:

Regulatory guidance is required on the acceptability of evidence derived from big data sources”.

  1. Medical devices and in vitro diagnostics regulation:

Ensure effective implementation of the new regulations for devices and in vitro diagnostics (IVDs) associated with the use of medicinal products and monitor its impact in delivering safe and effective devices and IVDs”.

  1. Skills and knowledge across the regulatory network:

Regulators must be equipped with the skills required for these emerging areas”.

  1. External communication and engagement:

Proactive regulatory engagement with external stakeholders relevant to the Big Data Landscape is needed in order to influence strategy and ensure regulatory needs are highlighted”.

The Taskforce has invited stakeholders and the public to provide feedback on the core recommendations until 15 April 2019.  Views on prioritisation of future actions are particularly welcomed. Further details may be found in the EMA’s press release, available here.