Developing a Common Health Data Model for Europe

The European Medicines Agency has been holding a 2 day international workshop in London [11th -12th December 2017] to define  opportunities and challenges for a common health data model in Europe. The expected outcome of the workshop was agreeing guiding principles for the development of such a Common Data Model (CDM) in Europe, including key criteria for validation in the context of regulatory decision-making.

See more about the workshop
 

A common data model could help harmonise healthcare data across multiple data sets and provide a mechanism to conduct pan-European studies in a timely manner to address regulatory questions. At the same time, applying a common model to European data has multiple challenges. The meeting brought together regulators with academia, data holders and the pharmaceutical industry.

Sessions included talks from experts from North America and the European region discussing lessons learned and current challenges in very large current clinical data resources, regulatory verification and related issues. Common data model case studies  included Sentinel – the Harvard-based FDA system for accessing patient data from health data partners across the USA and CNODES (the Canadian Network for Operational Drug Effect Studies) which can access data on 100 million patients – a similar scale to Sentinel.

The U.S. Food and Drug Administration's (FDA) Sentinel Initiative uses a common health data model to improve the FDA’s ability to identify safety issues for medical products. Sentinel actively surveys pre-existing electronic healthcare data from multiple sources.

Themes at the workshop included ensuring the relevance of CDMs to health policy, keeping timelines short, inter-operability, consent and related ethical issues, and careful internal and external validation of clinical definitions, data, software and analytical models.

From the perspective of health professionals, policy makers, regulators and the public, key future questions include whether clinical outcomes from common data models will be generalisable or only relevant to specific sub-populations based on geography, genetics, demographics and/or complex co-morbidity.  In the era of precision medicine there is the clear need is to avoid “right” answers from the wrong clinical populations and “wrong” answers from the right populations.
Further key points to consider include the cost of CDMs and who should pay; and whether updating existing databases will be sufficient or will new, more robust databases be needed.

 Future EACPT Congresses will be held in:
- 2019 Stockholm
- 2021 Athens
- 2023 Rotterdam

The EACPT was founded in 1993 - 24 years ago - and now includes as members all major national organisations for clinical pharmacology in Europe, as well as organisations from further afield internationally. The EACPT aims to provide educational and scientific support for the more than 4000 individual professionals interested in clinical pharmacology and therapeutics throughout the European region, with its congresses attended by a global audience. The EACPT also advises policy makers on how the specialty can contribute to human health and wealth.

Clinical Therapeutics, the Official Journal of EACPT

Opportunities from Big Data for safer medicines

14-15 November, 2016: The European Medicines Agency is hosting a web-casted workshop in London on identifying opportunities from "Big Data" in development and regulation of medicines. There has been such strong interest that a much larger venue is being used than available at its usual Canary Wharf centre, with perspectives from EU and USA policy makers, regulators, academia, health professionals and industry.

The EMA note: "Rapid developments in technology have led to the generation of vast volumes of data, which have the capability to transform the way the benefit-risk of medicinal products is assessed over their entire life cycle. However, it is recognised there are multiple challenges in the exploitation of these data. These range from the fundamental need to establish methods to enable the access to, integration and analysis of heterogeneous datasets to understanding the limitations in its use. Importantly, robust and transparent mechanisms to protect patient confidentiality are key to secure patient trust. It is important for the European Medicines Agency and the European Union medicines regulatory network to gather information on the latest developments in big data from the perspective of all stakeholders in order to identity how and when the multitude of data sources may contribute to medicinal product development, authorisation and post-marketing surveillance."

Some key threads and discussion points:
- the importance of the FAIR principles (data should be Findable, Accessible, Interoperable and
- Reusable)
- access for health professionals and researchers to the European Open Science Cloud
- a major EU initiative to promote data curation
- the power of the Cloud for cross-platform data sharing
- Big Data applied to precision medicine and pharmacogenomics
- bias in datasets
- Big Data and new EU General Data Protection Regulations - from May 2018, replacing Directive 95/46
- machine-learning for chemogenomics
- challenges to implementing applications to precision medicines in 'time poor' clinical practice
- OHDSI comumity - access to international health record data sources
- twitter not designed as a health app but may provide complementary insight into unexpected adverse effects of medicines to that obtained through traditional pharmacovigilance routes
- transferable learning - e.g. from use of Big Data in transport networks
- case studies in the EU and USA
- trade-offs: methods might be rapid, unbiased and accessible/usable by the inexperienced: but not all three
- challenges in the European Region to maximise learning from Big Health Data when there are 28 independent national health care systems with barriers and challenges to data-sharing

All talks are due to be made available on the EMA website for public access.