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. 2025 Jun 3;11(1):83.
doi: 10.1038/s41537-025-00599-w.

Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program

Johanna T W Wigman  1 Ann Ee Ching  2   3 Yoonho Chung  4   5 Habiballah Rahimi Eichi  4   5 Erlend Lane  6 Carsten Langholm  6 Aditya Vaidyam  6 Andrew Jin Soo Byun  6 Anastasia Haidar  7 Jessica Hartmann  3 Angela Nunez  8 Dominic Dwyer  2   3 Adibah Amani Nasarudin  2   3 Owen Borders  7 Isabelle Scott  2   3 Zailyn Tamayo  8 Priya Matneja  9 Kang-Ik Cho  5   7 Jean Addington  10 Luis K Alameda  11 Celso Arango  12 Nicholas J K Breitborde  13   14 Matthew R Broome  15   16 Kristin S Cadenhead  17 Monica E Calkins  18 Eric Yu Hai Chen  19 Jimmy Choi  20 Philippe Conus  11 Cheryl M Corcoran  21 Barbara A Cornblatt  22   23 Covadonga M Diaz-Caneja  12 Lauren M Ellman  24 Paolo Fusar-Poli  25   26 Pablo A Gaspar  27 Carla Gerber  28 Louise Birkedal Glenthøj  29 Leslie E Horton  30 Christy Lai Ming Hui  19 Joseph Kambeitz  31 Lana Kambeitz-Ilankovic  31 Matcheri S Keshavan  5   6 Sung-Wan Kim  32   33 Nikolaos Koutsouleris  25   34 Kerstin Langbein  35 Daniel Mamah  36 Daniel H Mathalon  37   38 Vijay A Mittal  39 Merete Nordentoft  40   41 Godfrey D Pearlson  42   43 Jesus Perez  4   44   45 Diana O Perkins  46 Albert R Powers 3rd  8   47 Jack Rogers  48 Fred W Sabb  49 Jason Schiffman  50 Jai L Shah  51   52 Steven M Silverstein  53 Stefan Smesny  35 Walid Yassin  5   6 William S Stone  5   6 Gregory P Strauss  54 Judy L Thompson  55   56 Rachel Upthegrove  15 Swapna Verma  57 Jijun Wang  58 Daniel H Wolf  18 Phillip Wolff  59 Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ)Laura M Rowland  60 Simon D'Alfonso  61 Ofer Pasternak  7 Sylvain Bouix  7   62 Patrick D McGorry  2   3 Rene S Kahn  21 John M Kane  22   23 Carrie E Bearden  63 Scott W Woods  8 Martha E Shenton  5   7 Barnaby Nelson  2   3 Justin T Baker #  4   5 John Torous #  64   65
Affiliations

Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program

Johanna T W Wigman et al. Schizophrenia (Heidelb). .

Abstract

Although meta-analytic studies have shown that 25-33% of those at Clinical High Risk (CHR) for psychosis transition to a first episode of psychosis within three years, less is known about estimating the risk of transition at an individual level. Digital phenotyping offers a novel approach to explore the nature of CHR and may help to improve personalized risk prediction. Specifically, digital data enable detailed mapping of experiences, moods and behaviors during longer periods of time (e.g., weeks, months) and offer more insight into patterns over time at the individual level across their routine daily life. However, while novel digital health technologies open up many new avenues of research, they also come with specific challenges, including replicability of results and the adherence of participants. This paper outlines the design of the digital component of the Accelerating Medicines Partnership® Schizophrenia Program (AMP SCZ) project, a large international collaborative project that follows individuals at CHR for psychosis over a period of two years. The digital component comprises one-year smartphone-based digital phenotyping and actigraphy. Smartphone-based digital phenotyping includes 30-item short daily self-report surveys and voice diaries as well as passive data capture (geolocation, on/off screen state, and accelerometer). Actigraphy data are collected via an Axivity wristwatch. The aim of this paper is to describe the design and the three goals of the digital measures used in AMP SCZ to: (i) better understand the symptoms, real-life experiences, and behaviors of those at CHR for psychosis, (ii) improve the prediction of transition to psychosis and other health outcomes in this population based on digital phenotyping and, (iii) serve as an example for replicable and ethical research across geographically diverse regions and cultures. Accordingly, we describe the rationale, protocol and implementation of these digital components of the AMP SCZ project. **Link to video interview: https://vimeo.com/1060935583 *.

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Conflict of interest statement

Competing interests: Celso Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. Dominic Dwyer has recieved honorary funds for one educational seminar for CSL Sequiris.John Kane has served as a consultant to or receives honoraria and/or travel support and/or speakers bureau: Alkermes, Allergan, Boehringer-Ingelheim, Cerevel, Dainippon Sumitomo, H. Lundbeck, HealthRhythms, HLS Therapeutics, Indivior, Intracellular Therapies, Janssen Pharmaceutical, Johnson & Johnson, Karuna Therapeutics/Bristol Meyer-Squibb, LB Pharmaceuticals, Mapi, Maplight, Merck, Minerva, Neurocrine, Newron, Novartis, NW PharmaTech, Otsuka, Roche, Saladax, Sunovion, Teva. Paulo Fusar-Poli has received research funds or personal fees from Lundbeck, Angelini, Menarini, Sunovion, Boehringer Ingelheim, Proxymm Science, Otsuka, outside the current study Rachel Upthegove has received speaker fees at non promotional educational events: Otsuka: Consultancy for Viatris and Springer Healthcare. Honoary General Secretary British Association for Psychopharmacology (unpaid). Rene Kahn reports consulting: Alkermes, Boehringer-Ingelheim. John Torous reprots being an dvisor to Percison Mental Wellness. Research support from Otsuka. Joseph Kambeitz reports speaking or consulting fees from Janssen, Boehringer Ingelheim, ROVI and Lundbeck. Eric Yu Hai Chen report speaker fees at non-promotional educational events. Covadonga M. Diaz-Caneja has received grant support from Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation and honoraria or travel support from Angelini, Janssen, and Viatris. All other authors report no biomedical financial interests or potential conflicts of interest.

Figures

Fig. 1
Fig. 1. Example of raw, primary, and secondary features inside the Cortex platform, which is a software pipeline that transforms digital phenotyping raw data into meaningful features.
In this figure, raw data (on the far right) is GPS and primary features are trips and secondary locations. Secondary features are derived from primary features and, in this example include home time, trip distance, and similarity measures of mobility patterns across different weeks.

References

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