Personalised digital treatment

Mental disorders, especially depression, accounts for a significant and growing proportion of disability, both nationally and internationally. Even so, few receive care, let alone evidence-based care. Although attempts have been made to mitigate this treatment gap, by the use of internet-based interventions, these have to a large degree either not been widely adopted or suffer from rigid one-size-fits-all service models. In order to truly move the field forward, Internet-based interventions must be as adaptive as face-to-face treatments.

PERSONAE aims to develop a scalable, data-driven matched adaptive care service for depression. By the use of multiple treatment modalities and intelligent data driven clinician and patient support systems, it will provide access to personalised, digital treatment for all, in a cost-effective manner.

Illustration of the treatment model

Rethinking digital treatments

In order to achieve well-performing individually tailored digital treatment, it is necessary to rethink digital treatments as much more than just an intervention. Instead, it is necessary to design a full digital service model capable of meeting the needs of each individual patient. New innovative intimate digital interventions on mobile platforms must be combined with an adaptive service design model and must be supported by intelligent data driven decision support systems. In the PERSONAE project, we propose a radical new service, which integrates a matched care service design, mobile intimate interventions and data collection, adaptive treatment content, and artificial intelligence. Only by integrating all these elements, will we be able to truly harvest the potential of digital interventions for depression.

Project aim

The aim of the PERSONAE project is to combine cutting-edge individualised mobile intervention technologies including ease of use, high-resolution data collection and adherence enhancing technologies with a matched care service design and artificial intelligence for data driven automation and decision support systems. In short: digital matched and adaptive treatment for depression.

Value propositions

  • Easy access to a scalable, personalized offer of CBT modalities
  • Flexible, digital at-home treatment
  • Faster access to treatment
  • Efficient use of clinicians’ time
  • Less time wasted on insufficient or inappropriate treatment
  • Implementation in Danish mental health services immediately after the project ends via Internetpsykiatrien
  • International commercialisation by the Danish SME, Monsenso

The project builds on:

  • The previous successes of the ENTER research project
  • Internetpsykiatrien
  • The latest evidence-based interventions for depression
  • The advances in mobile health technologies, remote patient monitoring
  • Machine learning.

The project will design, develop and validate a service that demonstrates value for patients, clinicians and health care providers.

The PERSONAE project began 1st of May 2023.

Work packages

The PERSONAE project is divided into eight work packages. Below you can read more about the individual work packages

Governance structure

WP 1: Platform innovations

The objective of this work package is to prepare the platform for delivering data-driven, digital, personalised matched care to patients and for recommending optimal care pathway to clinicians. The work will be based on the current Monsenso mobile health solution and the current sign-up and screening process being used for Internetpsykiatrien. The platform ensures the data collection fuelling the AI-algorithms, clinical and economic studies of WP 5, and 7 and it hosts the digital intervention programmes that patients are asked to follow.

Emil Kortsen

Lead by Emil Kortsen,

Product Owner

Monsenso A/S.

WP 2: Treatment Content Innovations

The main purpose of work package two, Technical adaptations, is to develop and implement treatment content based on the program for adult depression from Internetpsykiatrien and the ENTER project and to adapt the patient administrative software. Moreover, the work package focuses on designing data structures for data collection and distribution among partners.

Team Leader, Thomas Binzer,

MSc.Eng. in Product Development & Innovation

Centre for Digital Psychiatry.

Assistant Leader,

Marie Birkemose Hansen

Project Manager

Centre for Digital Psychiatry


WP 3: Machine Learning Innovations

Work package three will leverage the rich data already available on our patient cohorts and further data collected during the study. This data will be used to:

  1. Create personalised patient models that will allow us to screen patients automatically and recommend the most suitable treatment and level within our stepped model
  2. Support patients and their caregivers with adaptive treatment suggestions throughout treatment
  3. Provide visualisations to provide patients and their caretakers with the reasons for the system’s recommendations, thus creating trust in the AI technology underpinning this work package.


Pepijn Van de Ven

Lead by Pepijn Van de Ven,

Senior Lecturer,

University of Limerick.

WP 4: User-centred design process

The aim of the User Involvement work package is to ensure patients’ acceptance of and adherence to the treatment. The purpose of the user involvement is both to ensure that relevant problems are solved with the future treatment solution and to co-create how to solve the problems appropriately when designing and developing the solution.


Amalie Søgaard Nielsen

Lead by Amalie Søgaard Nielsen,

Assistant professor,

Center for Digital Psychiatry.

WP 5: Clinical study

In this work package, the novel treatment concept will be evaluated for safety (negative effects), clinical effectiveness and adherence in comparison with the standard guided iCBT treatment at Internetpsykiatrien. In addition, secondary clinical measures will be analysed e.g. the level of therapeutic alliance and the role of co-morbid anxiety and or substance use. Ph.d. student on the RCT study is Trine Therese Holmberg Sainte-Marie, Centre for Digital Psychiatry and SDU.

Kim Mathiasen

Lead by Kim Mathiasen,

Associate professor,

Centre for Digital Psychiatry and SDU.

Trine T. H. Sainte-Marie

Trine T. H. Sainte-Marie,

Research assistant

Centre for Digital Psychiatry

WP 6: Implementation and Exploitation

The overall objective of the implementation and exploitation work package is to secure transferability of D-MAC and inform exploitation and further implementation processes in real-life settings.

WP 7: Health Economic Evaluations

The objective of the economic evaluation of digital adaptive matched care (DAMC) for patients with depression is to carry out a cost-effectiveness analysis based on the clinical study with data on patient level.

Iben Fasterholdt

Lead by Iben Fasterholdt,

Senior Health Economist & Scientist in AI


Assistant leader, Nanna Bluhme

Research Assistant


WP 8: Management, Communication and Dissemination

The purpose of work package eight is to ensure coordination and timely progression of the overall project and to communicate and disseminate the activities and results of the project.

Kim Mathiasen

Lead by Kim Mathiasen,

Associate Professor,

Centre for Digital Psychiatry and SDU.

Rikke Hellum

Assistant Leader,

Rikke Hellum, 

Project Manager

Centre for Digital Psychiatry.