The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Characteristics and challenges of the clinical pipeline of digital therapeutics
Open accessAbstract
In this Comment, we characterize the current pipeline of digital therapeutics and offer a clinical perspective into the advantages, challenges, and barriers to implementation of this treatment modality for patient care, which we hope will inform future regulatory policy, prescribing decisions, and scope of real-world evidence collection.
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“Although mobile apps targeting treatment adherence have been understudied, several recent examples have shown promise: AiCure uses a HIPAA-compliant and scalable AI platform to monitor treatment adherence 86,87 ; Mango Health and Health Prize are incentive-based apps to improve access and adherence to prescribed treatments 88,89 ; Medisafe is an app that provides reminders and alerts for users to”
From Digital health technologies and major depressive disorder (2023) · cites this paper as [86]
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Cites
Quinn, C. C., Shardell, M. D., Terrin, M. L., Barr, E. A., Ballew, S. H., & Gruber-Baldini, A. L. (2011) · Diabetes Care · doi:10.2337/dc11-0366 · Cited by 650
Kollins, S. H., DeLoss, D. J., Cañadas, E., Lutz, J., Findling, R. L., Keefe, R. S. E., Epstein, J. N., Cutler, A. J., & Faraone, S. V. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30017-0 · Cited by 385
Christensen, H., Batterham, P. J., Gosling, J. A., Ritterband, L. M., Griffiths, K. M., Thorndike, F. P., Glozier, N., O'Dea, B., Hickie, I. B., & Mackinnon, A. J. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00536-2 · Cited by 365
Internet-delivered treatment for substance abuse: a multisite randomized controlled trial
Campbell, A. N. C., Nunes, E. V., Matthews, A. G., Stitzer, M., Miele, G. M., Polsky, D., Turrigiano, E., Walters, S., McClure, E. A., Kyle, T. L., et al. (2014) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2014.13081055 · Cited by 263
Blockchain vehicles for efficient Medical Record management
Vazirani, A. A., O’Donoghue, O., Brindley, D., & Meinert, E. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0211-0 · Cited by 245
Merchant, R. K., Inamdar, R., & Quade, R. (2016) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2015.11.022 · Cited by 221
Adding an Internet-delivered treatment to an efficacious treatment package for opioid dependence.
Christensen, D. R., Landes, R. D., Jackson, L., Marsch, L. A., Mancino, M. J., Chopra, M. P., & Bickel, W. K. (2014) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0037496 · Cited by 149
Algorithms on regulatory lockdown in medicine
Babic, B., Gerke, S., Evgeniou, T., & Cohen, I. G. (2019) · Science · doi:10.1126/science.aay9547 · Cited by 123
Ronquillo, J. G., & Zuckerman, D. M. (2017) · Milbank Quarterly · doi:10.1111/1468-0009.12278 · Cited by 86
Modernizing and designing evaluation frameworks for connected sensor technologies in medicine
Coravos, A., Doerr, M., Goldsack, J., Manta, C., Shervey, M., Woods, B., & Wood, W. A. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0237-3 · Cited by 82 · cited 1×
“…of cybersecurity and data rights are preconditions for the mass adoption of DTx. Similar to prior work regarding connected sensors in medicine 16 , as DTx transfer information over the internet, risks of unauthorized access and manipulation of these products and underlying data could…”
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Toledo‐Rodriguez, M., & Boillat, T. (2022) · Health informatics · doi:10.1007/978-3-030-94212-0_13 · Cited by 2
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“Digital mental health services have evolved rapidly, aiming to enhance the efficiency and quality of health care services, including diagnosis, monitoring, treatment, and data management, through digital communication technologies [10,11].”
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Stegemann, L. (2025) · Lecture notes in information systems and organisation · doi:10.1007/978-3-031-80125-9_36 · Cited by 1
Teledentistry and Digital Therapeutics (DTx) for dentistry
Park, S.-Y. (2022) · Journal of Clinical Advances in Dentistry · doi:10.29328/journal.jcad.1001029 · Cited by 1
“Third, medical practice using this technology is effective for data collection for future research purposes, and AI learning or cloud-based data integration can provide personalized medical care based on more accurate research [27,28].”
BackgroundDû, K. L., Septans, A.-L., Maloisel, F., Vanquaethem, H., Schmitt, A., Legoff, M., Clavert, A., Zinger, M., Bourgeois, H. P., Dupuis, O., et al. (2022) · doi:10.2196/preprints.38619
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Seneviratne, O. W. (2012) · Women in engineering and science · doi:10.1007/978-3-030-93592-4_1
Tapia, J. L., & Duñabeitia, J. A. (2022) · doi:10.31234/osf.io/6khfu
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Tan, R. K. J., Neo, P. H. M., Lim, J. M., & Ong, S. E. (2023) · Springer eBooks · doi:10.1007/978-3-030-96778-9_54-1
Pearls of wisdom from the past 5 years of working in telehealth
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Kim, Y., Park, S., Kim, D., Kim, B., & Lee, J.-H. (2023) · Research Square · doi:10.21203/rs.3.rs-2756192/v1
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Jin, W. H., Mohan, S., Adams, M., Hoffe, S. E., & Robinson, E. J. (2022) · Applied Radiation Oncology · doi:10.37549/aro1313
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Digital Therapeutics Evolution What kind of Research Will Make the Difference in this Area?
Mayora, O., Bert Arnrich, A., Guerreiro, T., Ferreira-Brito, F., Luštrek, M., & Gjoreski, H. (2023) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3594739.3605109
“The new era of DTx [3] can find an important tool in artificial intelligence through which a more personalized form of healthcare can emerge thanks to the capability to dynamically adapt to patients’ individual clinical needs, goals, and lifestyles [4].”
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“It is an evidence-based medical approach used to treat, manage, or prevent diseases [18].”
BackgroundGißke, C., Weimann, T. G., & Schlieter, H. (2024) · IEEE Conference on Business Informatics · doi:10.1109/cbi62504.2024.00035
“The medical focus of DTx has been particularly on managing behavior-modifiable diseases such as obesity, diabetes, cardiovascular diseases, or mental disorders [6].”
DigiTher : An Open AI-Based Platform for Digital Therapeutics Intervention
Eccher, C., Zorzi, A., Bailoni, T., Poggianella, S., & Dragoni, M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-95841-0_26
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Takefuji, Y. (2025) · International Journal of Healthcare Management · doi:10.1080/20479700.2025.2546530
“Patel et al. clearly stated that ‘considerations of cybersecurity and data rights are preconditions for the mass adoption of Digital therapeutics defined by the Digital Therapeutics Alliance’ [10].”
Kim, J., Kim, J., Lee, C., Lobos, M. A., & Kim, N. (2025) · International Journal of Mental Health Promotion · doi:10.32604/ijmhp.2025.064617 · Cited by 1
Lee, J., & Kim, J. (2025) · American Journal of Health Promotion · doi:10.1177/08901171251391600 · Cited by 1
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Cesario, A., Gorini, M., & D’Amario, D. (2025) · Springer eBooks · doi:10.1007/978-3-032-01272-2_3
Sing, M., & Chen, P.-T. (2026) · doi:10.2196/preprints.92689
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Almohammadi, A. A. (2026) · Annals of Movement Disorders · doi:10.4103/aomd.aomd_101_25
Maggio, M. G., Ettorre, P., Benenati, A., Ciancarelli, I., Iulio, F. D., Iosa, M., Calabrò, R. S., & Morone, G. (2026) · Frontiers in Pediatrics · doi:10.3389/fped.2026.1764054
“Digital intervention is becoming increasingly common in pediatrics, and the FDA authorization of EndeavorRx has further increased clinical interest in prescription digital therapeutics for ADHD (19, 20).”
Digital therapeutics in cancer management and the emerging role of digital phenotyping
Cong, B., Xu, B., Chen, X., Ou, Y., Li, X., Liu, K., Zhang, S., Fu, C., Fan, J., Liu, Z., et al. (2026) · Displays · doi:10.1016/j.displa.2026.103502
Ferrara, F., & Berardinis, F. D. (2026) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-026-02398-5
Mhyellah, J. H., Rweyendera, A., Gwahula, G., Vedastus, Y., Mkama, M., Welema, E., Kiritta, R. F., & Jaka, H. (2026) · BMC Artificial Intelligence · doi:10.1186/s44398-026-00028-7
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Yang, M., Shao, J., Peres, M., & Liu, K. (2026) · International Journal of Pain Research · doi:10.11648/j.ijpr.20260202.11
Albitar, J., Ulisse, K., Feghali, C., van Oppen, D., Zell, M., & Elswick, D. E. (2026) · Brain Sciences · doi:10.3390/brainsci16060576
“Post-market surveillance systems remain limited, particularly for software products that undergo frequent updates, which hinders monitoring of real-world safety and effectiveness [68,69].”
Kim, M., & Kim, G. (2026) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580261467451
Liu, Y., Liang, S., Liang, A., Guo, Y., Ma, X., Li, Q., Wang, R., Zhao, X., Wang, S., Chu, P., et al. (2026) · BMC Medicine · doi:10.1186/s12916-026-05080-8
“Recognized as ‘an emerging class of medicines’ [3], DTx have received approval from regulatory authorities such as the U.S. Food and Drug Administration [4].”
AI- and Generative AI-Driven Digital Therapeutics: A Critical Narrative Review of Emerging Evidence
Giansanti, D., & Lastrucci, A. (2026) · AI · doi:10.3390/ai7080296
Choi, S., & Zo, H. (2026) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2026.106647
Realdon, O., Borgnis, F., Blasi, V., Mavrodiev, P. A., Palumbo, E., Saresella, M., Mantovani, F., Amato, M. P., & Baglio, F. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-26235-6_3
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“As a result, digital mental health tools have gained growing attention as potential means to expand access to care (Patel and Butte, 2020; Yang et al., 2023).”
Angelone, L. M., Nguyen, T., & Koustova, E. (2026) · Substance Use & Misuse · doi:10.1080/10826084.2026.2748450
Metadata
- Authors
- Patel, N. A., & Butte, A. J.
- Affiliations
- University of California, San Francisco (US)
- Corresponding author
- Patel, Nisarg A.
- Venue
- npj Digital Medicine
- Published
- 2020-12-11
- Volume
- 3
- Issue
- 1
- Pages
- 159-159
- ISSN
- 2398-6352 (ISSN-L)
- PMC
- PMC7733514
- OpenAlex
- W3110865436
- Cited by
- 143
- References
- 16
- Citations by year
- 2026: 18 · 2025: 20 · 2024: 27 · 2023: 40 · 2022: 26 · 2021: 11
- FWCI
- 17.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- npj Digital Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- digital therapeutics, regulatory policy, prescribing decisions, real-world evidence, implementation barriers, digital health products
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