Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium.

Biomodifying the 'natural': from Adaptive Regulation to Adaptive Societal Governance.

Biomodifying technologies-such as gene editing, induced pluripotent stem cells, and bioprinting-are being developed for a wide range of applications, from pest control to lab-grown meat. In medicine, regulators have responded to the challenge of evaluating modified 'natural' material as a therapeutic 'product' by introducing more flexible assessment schemes. Attempts have also been made to engage stakeholders across the globe on the acceptable parameters for these technologies, particularly in the case of gene editing.

eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain.

Integrative drug safety research in translational health informatics has rapidly evolved and included data that are drawn in from many resources, combining diverse data that are either reused from (curated) repositories, or newly generated at source. Each resource is mandated by different sets of metadata rules that are imposed on the incoming data. Combination of the data cannot be readily achieved without interference of data stewardship and the top-down policy guidelines that supervise and inform the process for data combination to aid meaningful interpretation and analysis of such data.

Controversies between regulations of research ethics and protection of personal data: informed consent at a cross-road.

This paper explores some key discrepancies between two sets of normative requirements applicable to the research use of personal data and human biological materials: (a) the data protection regime which follows the application of the European Union General Data Protection Regulation (GDPR), and (b) the Declaration of Helsinki, CIOMS guidelines and other research ethics regulations. One source of this controversy is that the GDPR requires consent to process personal data to be clear, concise, specific and granular, freely given and revocable and therefore has challenged the concept of 'broad consent', which has been widely applied in the context of biobanking. Another source of controversy is the interplay between regulations of research ethics and protection of personal data related to the secondary use of personal data and biological materials.

'Leading by Science' through Covid-19: the NHS Data Store & Automated Decision-Making.

The UK government announced in March 2020 that it would create an NHS Covid-19 'Data Store' from information routinely collected as part of the health service. This 'Store' would use a number of sources of population data to provide a 'single source of truth' about the spread of the coronavirus in England. The initiative illustrates the difficulty of relying on automated processing when making healthcare decisions under the General Data Protection Regulation (GDPR).

Ethical Issues in Consent for the Reuse of Data in Health Data Platforms.

Data platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate model for facilitating this.

Governance of research consortia: challenges of implementing Responsible Research and Innovation within Europe.

Responsible Research and Innovation ('RRI') is a cross-cutting priority for scientific research in the European Union and beyond. This paper considers whether the way such research is organised and delivered lends itself to the aims of RRI. We focus particularly on international consortia, which have emerged as a common model to organise large-scale, multi-disciplinary research in contemporary biomedical science.

Anonymity in EU Health Law: Not an Alternative to Information Governance.

Data sharing has long been a cornerstone of healthcare and research and is only due to become more important with the rise of Big Data analytics and advanced therapies. Cell therapies, for example, rely not only on donated cells but also essentially on donated information to make them traceable. Despite the associated importance of concepts such as 'donor anonymity', the concept of anonymisation remains contentious.

Gene therapy regulation: could in-body editing fall through the net?

Somatic gene therapies may be authorised for marketing in the EU under the advanced therapy medicinal product regulation. These therapeutic compounds are sufficiently novel and complex in their potential effects to require specialist evaluation. However, the current definition of gene therapy medicinal products ('GTMP') risks excluding molecules which are not manufactured through techniques involving recombination.

Five models for child and adolescent data linkage in the UK: a review of existing and proposed methods.

Over the last decade dramatic advances have been made in both the technology and data available to better understand the multifactorial influences on child and adolescent health and development. This paper seeks to clarify methods that can be used to link information from health, education, social care and research datasets. Linking these different types of data can facilitate epidemiological research that investigates mental health from the population to the patient; enabling advanced analytics to better identify, conceptualise and address child and adolescent needs.

Health Data Linkage for UK Public Interest Research: Key Obstacles and Solutions.

Introduction: Analysis of linked health data can generate important, even life-saving, insights into population health. Yet obstacles both legal and organisational in nature can impede this work.

Approach: We focus on three UK infrastructures set up to link and share data for research: the Administrative Data Research Network, NHS Digital, and the Secure Anonymised Information Linkage Databank.