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The Digitally Enabled PrevenTative Health (DEPTH) Research Group is focused on high-impact research in digital health. Our team is centred on issues affecting the engineering and evaluation of mobile digital solutions and integrated health data ecosystems. This work is complemented by research into critical enabling infrastructure including novel regulatory pathways, regulation, standards and intellectual property.

Healthcare translation research group

Research areas

Advanced therapeutics clinical translation and cell therapy commercialisation

Advanced therapies, such as cell and gene therapies, are a new therapeutic modality which have potential to offer treatment or cures for currently untreatable diseases. This therapeutic strategy is very young in comparison to standard chemical-based drugs, and therefore few are currently established on the market.


(Pre-) adoption and abandonment of health innovations in different settings

Evaluating facilitators and barriers influencing the uptake of digitally-delivered interventions from the perspective of different stakeholders (patients, carers, health workers, clinics, hospitals, policy makers, regulators, insurers, pharma, start-ups, medical device, biotech and technology companies, etc.).



As increasing population data is accessed by automated systems and agents, the risk exposure of assets increases. The benefits of population data insights are tempered with these risks of unauthorised access, which can have direct implications to the quality and management of health.


Intellectual property landscaping

Intellectual property (IP) is of fundamental importance to medicinal product development. IP landscaping is a method by which information about IP can be gathered, and can provide valuable insight into the activity of other research groups or the progression of research areas as a whole.


The safety and quality of digitally-delivered health interventions

Regulation, standards, validation, and assessment of the efficacy, effectiveness, and costs of digital health.


Software engineering

Requirements and product engineering using machine learning and artificial intelligence (AI) agents, where there are potential for behaviour change for positive health outcomes, workforce efficiency opportunities via robotic process automation and capabilities for improved clinical and population health insight from predictive data analytics.

Our team