Post-doc - Designs for Evaluation of Digital - Paris, France - METHODS team

Description

Site web:


Poste et missions:

At-Hotel-Dieu is an ambitious public-private partnership aimed at developing an interface between public organizations (Assistance Publique - Hôpitaux de Paris and Université Paris Cité) and technology startups (Lifen, Withings, Nouveal, Nabla and Implicity).

Its objective is to accelerate the uptake of digital medicine tools, such as biometric wearable devices and AI, in both hospitals and outpatient care.

The program received 17 million Euros from the French Public Investment Bank ("Banque Publique d'Investissement" - BPI).

Within the At-Hotel-Dieu project, the METHODS team is responsible of an important research program aimed at:
Improving the development of algorithms in healthcare, especially to ensure their robustness and external validity;
Conceptualizing a new care model blending digital technologies in the current workflow of physicians and patients, through the use of participative sciences;
Developing methodological and mathematical tools for real-time personalized care and "Just-in Time Adaptive Interventions";
Refining the methods to accelerate and lower the cost of the evaluation of the effectiveness of digital health interventions

The recruited post-doctoral fellows will be part of the METHODS Team of CRESS, located at Hôtel-Dieu hospital in the center of Paris.

The team is affiliated to the Université Paris Cité and Inserm (French national health research institute).

It offers a dynamic multidisciplinary research environment with four tenured university hospital professors, two tenured INSERM research, one junior professor, two assistant professors, 5 post-docs and about 10 doctoral students.

Mission:

The following section is specific to a position aimed at systematically reviewing available methods to evaluate digital health interventions and at evaluating the strength and limitations of these methods.

According to R Califf (the former US FDA commissioner), "the traditional clinical trial (used to assess drugs and devices) is an antiquated endeavor" and an inefficient one.

In the same way, FS Collins (the director of the US NIH) notes that "most clinical studies start from scratch and require years to achieve full enrollment (and many never do)" and that "this 'one-off' approach requires repeated construction and deconstruction of the clinical research infrastructure".

The current clinical research enterprise is struggling to evaluate the few dozens of new drugs per year and is unsuited to evaluate the number of digital health products and algorithms developed each.

Furthermore, the current system is ill-adapted to the specificities of the devices and apps (e.g., rapid evolution of algorithms, features or designs that make static evaluation rapidly obsolete).

This project entails three parts: 1) systematically reviewing designs that could accelerate the evaluation of digital health interventions (e.g., Trials WIthin Cohorts (TWICs), Sequential Multiple Assignment Randomized Trials (SMARTs), Direct-To-Participant trials, or Bring Your Own Device (BYOD) trials, target trial emulation, etc.); 2) evaluating the strengths and limitations of these designs, including how regulators and researchers would trust the results of studies using these designs; and 3) conducting an international meeting consensus to develop recommendations for the evaluation of digital health interventions.

Activities:
Conducting a methodological systematic review of designs used to evaluate digital health interventions

Conducting a participative science study to assess t how regulators and researchers would trust the results of studies using these designs

Organizing an international meeting aimed at developing recommendations for the evaluation of digital health interventions


Mobilité géographique:

• Nationale
  Télétravail:
• Partiel
  Profil:

Skills:
Expertise in the conduct of systematic reviews

Excellent knowledge of designs for comparative effectiveness research

Organizational skills

Education level:
Doctoral degree in Clinical Epidemiology statistics, methods research or meta research.

Duration: 24 months (depending on the starting date)


Salary: 2 200 to 2 400 € Net /month depending on experience