Data sharing: a healthier you, a better society?

Driven by digitalization and AI, clinical trials are shifting. Clinical trials produce massive amounts of data. Integrating diverse Health data into trials can accelerate research and enhance their impact, benefiting both research and society.

Shared data can help identify which treatments work best for specific groups of people. By incorporating a wide range of data, from genetics to lifestyle habits, researchers can create more inclusive trials that better reflect the diverse needs of real-world patients.

Whether it is tailoring dosage based on genetic markers or adjusting protocols to accommodate lifestyle preferences, personalized medicine becomes the new standard in clinical trials, improving efficacy, and reducing adverse effects.

Avoiding harmful reactions to medication is crucial in any clinical trial. With data, for example from wearable devices or genetic risk assessments, researchers can identify and mitigate potential risks before they become serious. Here, artificial intelligence can identify underlying patterns or signals faster, ensuring the well-being of every participant.

Data sharing also empowers patients, as they have access to their own Health Data, enabling active participation in monitoring symptoms, tracking progress, and making informed decisions about treatment options.

By sharing health data, patients and individuals contribute to their own treatment and to the collective understanding of diseases, treatments, and outcomes. This collective knowledge can lead to new discoveries and improvements in healthcare.

And even before a trial starts, researchers could use advanced analytics and AI to identify promising drug candidates more quickly and efficiently, thus reducing the time required for the traditional trial schedule.

Access to a larger pool of data also allows for the development of so-called virtual arms. Virtual arms are control groups, which do not receive the experimental treatment. Instead, a virtual arm is constructed using historical data, real-world data, or data from other studies, which matches the baseline characteristics of the experimental group patients.

To ensure virtual arm integrity, data must be of high quality, relevant, and comparable to the data collected from the traditional trial. In this scenario, virtual clinical trials can be less expensive and quicker to run, as recruiting and managing patients for the control group may not be necessary.

The approach also addresses an ethical challenge: Virtual arms allow all participants to receive potentially beneficial treatments, which can be particularly important in trials for life-threatening conditions. Healthcare authorities such as the FDA in the US and EMA in the EU are still developing guidelines and frameworks for the use of virtual arms in clinical trials.

Who has access to the data, and could it be exposed without consent or through data breaches? Can data be misused for other purposes? Does the patient have control over it, and will anonymity be maintained?

Such concerns of patients and individuals about data sharing are valid: However, strong data protection frameworks, such as the Federal Act on Data Protection in Switzerland and the EU’s General Data Protection Regulation (GDPR), ensure the rights and privacy of everyone whose personal data is processed.

Newer policy frameworks such as the European Health Data Space (EHDS) go one further and build upon the rights laid out in the GDPR: Patients are granted greater control and autonomy over their Health Data, for example with the option to get instant copies of their health records or the control over who can and cannot look at their health records.

Roche launched a new clinical data-sharing policy in 2013. It has now more than ten years experience with sharing and safely handling clinical trial data and other study information, with patient privacy as a key factor. The company goes beyond the mandatory sharing of clinical trial data with Health Authorities and also shares anonymised patient level clinical research information and data, for example, with the scientific community.

For these use cases, Roche has published robust policies, for example, on sharing of clinical study information, on responsible sharing of scientifically credible information or on data ethics. There is also essential technical knowledge, particularly about the need for safe data platforms and processes. And most of all, Roche has established collaborations with patient groups.

A competitive edge

Data sharing is also a question of politics and the regulatory environment. For example, the EU’s upcoming European Health Data Space (EHDS) will change the way that data is reused to gain new insights for clinical research, R&D and policymaking. By creating a common data space that spans EU borders and disciplines, the EHDS is supposed to foster collaboration, facilitate access, and open up new avenues for innovation and discovery.

In Switzerland, which is lagging behind in the digitalization of healthcare, the current focus is on “Digisanté”. This federal programme also aims at fostering a database healthcare system, including the secondary use of healthcare data. Recognising the digital transformation urgency, the Federal Assembly has approved almost 400 million Swiss francs as funding.

Data sharing is here to stay

Digitalization and artificial intelligence are transforming daily life, and sharing Health Data is no exception. Sharing data can improve lives, including your own, contribute to a healthier society, and drive economic growth. These reasons alone make sharing Health Data a worthwhile endeavour.

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