Legal And Ethical Challenges Of Data-Driven Healthcare Innovation

• Published date: 12 March 2021
• Subject Matter: Corporate/Commercial Law, Intellectual Property, Food, Drugs, Healthcare, Life Sciences, Privacy, Corporate and Company Law, Data Protection, Privacy Protection, Patent
• Law Firm: Appleyard Lees
• Author: Ms Claire Devine and Parminder Lally

In the present climate it is clear that there is enormous pressure on healthcare systems across the globe. An increasingly aging population leads to a number of healthcare challenges including that people are living longer generally with one or more chronic conditions. However, artificial intelligence (AI), machine learning (ML) and "big data" have the potential to revolutionise the healthcare space. Developments in these technologies may help to streamline medical diagnoses and identify which therapies a patient will respond to, allowing the adoption of targeted therapies in an efficient manner.

Although the use of these technologies will likely have positive impacts on patients via, for example, earlier diagnoses of serious illnesses and faster drug development, companies developing and commercialising these technologies may have to deal with additional legal and ethical challenges. In this article, we take a look at how companies could navigate these challenges.

Data Protection, Privacy & Security

Machine learning diagnostics are currently being developed for use in a variety of fields including oncology, pathology and rare disease. Examples of ML diagnostics include using algorithms to recognise cancerous tissues, using image recognition to identify cancerous cells in microscope images, and using facial recognition to detect phenotypes linked to genetic diseases. ML and AI are also used in personalised medicine to identify subjects with certain biomarker signatures. This approach relies on the analysis of large datasets to identify biomarkers that are indicative of certain diseases or of a response to therapy.

It is clear that these data-driven approaches rely on access to and analysis of large amounts of our personal data. In recent years, there has been a huge accumulation of personal, health-related data due to a shift towards digital health monitoring. Patient data is now kept in digital records in hospitals, which means the data stored in those records can be harvested and analysed more easily to identify trends or patterns that may aid medical diagnoses. Patients may also wear or use medical devices that are able to monitor patient health and transmit data to another party, such as a healthcare professional for analysis. But are patients fully aware of where their data is being sent, how it is being stored and who may be accessing it? Furthermore, many of us, knowingly or unknowingly, also collect huge amounts of data about our health and...