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.
Fagherazzi
WATCH – 📺 Deep digital phenotyping for Precision Health
Projects & clinical trials
Featured team members
Scientific publications
-
Digital voice-based biomarker for monitoring respiratory quality of life – 01/10/2024
-
Dopamine Pathway and Parkinson’s Risk Variants Are Associated with Levodopa-Induced Dyskinesia – 01/01/2024
-
Sex inequalities in cardiovascular risk factors and their management in primary prevention in adults living with type 1 diabetes in Germany and France – 16/09/2024
-
Co-design of a voice-based app to monitor long COVID symptoms with its end-users – 09/09/2024
-
Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson’s disease – 06/09/2024
-
Levodopa-induced dyskinesia in Parkinson’s disease – 01/09/2024
-
The transformative role of artificial intelligence in diabetes care and research – 27/07/2024
-
Digital Vocal Biomarker of Smoking Status Using Ecological Audio Recordings – 03/07/2024
-
Mixed effects models but not t-tests or linear regression detect progression of apathy in Parkinson’s disease over seven years in a cohort – 24/08/2024
-
Heterogeneity of glycaemic phenotypes in type 1 diabetes – 23/05/2024
Related News
Job vacancies
There are no jobs matching this page at the moment. You can view all jobs via the button below.