
deep digital phenotyping research unit
The Deep Digital Phenotyping Lab aims to leverage digital health technologies to identify digital biomarkers for enhanced disease monitoring.
activities
The digitisation of healthcare is transforming the way diseases and populations are characterised and monitored. It enables more personalised healthcare to be provided by taking into account the physiological and contextual specificities of individuals. To move towards precision health, it is necessary to develop innovative approaches that encompass digital, biological, clinical and omics data. All these data would allow for more accurate characterisation of diseases and populations.
I like to work at the interface between digital epidemiology, data science and clinical research. For me the biggest challenge is now to develop innovative approaches where digital data are combined wither other omics, biological and clinical data to deeply characterise the patients.
Guy Fagherazzi, PhD, Group Leader Deep Digital Phenotyping Research Unit, Director, Department of Precision Health
digitalisation of clinical & epidemiological research
- Digital cohorts: development of large, international and digital cohort studies where participants are monitored with digital solutions (smartphone app, web platform, connected devices…).
- Remote patient monitoring, ePROs: monitoring of patient between clinical visits, tracking of patient reported outcomes and real-life data collection.
- IT infrastructure: in-house development of secured web platforms, cloud-based data lakes and research smartphone apps for real-life health data collection.
patient & public involvement
- Patient-centered research: use of digital technologies to carry out research “with” or “by” patients/study participants rather than “about” them.
- Innovative methods for study participation improvement: mixed methods, qualitative approaches, recordings to improve study participation rate and minimise attrition over time.
devices, digital data & biomarkers
- Voice: identification and validation of digital vocal biomarkers for enhanced remote patient monitoring. Development of novel clinical endpoints to assess treatment effectiveness in real-life.
- Connected devices (Activity trackers, Continuous Glucose Monitoring devices, Pill Organisers): leveraging digital tools to collect meaningful data on lifestyle, clinical factor or key biomarkers with a limited burden for the patient/user.
- Social Media: social media listening for a better understanding of a population of interest in real life (perceptions, beliefs, concerns…) or for pharmacovigilance (side effects, weak signals…)
methodology
- Data-driven & AI-based approaches: combination of hypothesis-driven with data-driven analyses of cohort or clinical trial data (clustering methods, prediction)
- Deep Digital Phenotyping: combination of heterogeneous sources of digital, clinical, biological, omic data to deeply characterise individuals and diseases.
- Digital Twins: virtual patients/individuals with similar or close characteristics as patients seen in a consultation for whom the health status, risks of complications, and disease evolutions are known.
Projects & clinical trials
Featured team members
Scientific publications
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Beyond overweight, visceral adiposity is associated with estimation of cardiovascular risk in patients living with type 1 diabetes – 01/12/2025
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Time below range alone is insufficient to identify severe hypoglycaemia risk in type 1 diabetes—the critical role of hypoglycaemia awareness – 09/09/2025
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Nationwide Trends in Type 1 and Type 2 Diabetes in France (2010–2019) – 01/01/2025
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Geographic environments, daily activities and stress in Luxembourg (the FragMent study) – 02/09/2025
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Role of the exposome in mental disorders – 18/08/2025
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Immune cell–adipose tissue crosstalk in metabolic diseases with a focus on type 1 diabetes – 04/06/2025
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Interpretable Machine Learning for Cross-Cohort Prediction of Motor Fluctuations in Parkinson’s Disease – 22/04/2025
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Voice Assessment and Vocal Biomarkers in Heart Failure – 24/04/2025
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A Functionally-Grounded Benchmark Framework for XAI Methods – 14/07/2025
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Musculoskeletal disorders in type 1 diabetes – 23/04/2025
Related News

Job vacancies
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Master’s internship Position – AI-driven exploration of diabetes burden through patients’ perspectives (00445)
Department of Precision Health – Deep Digital Phenotyping Research Unit
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Digital Health Scientific Manager (JA/DHSM0925/GF/DDP)
Department of Precision Health – Deep Digital Phenotyping Research Unit
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Research Assistant in Voice AI & Digital Epidemiology (JA/RA0925/GF/DDP)
Department of Precision Health – Deep Digital Phenotyping Research Unit