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Commercial Diagnostics and Emerging Precision Medicine Technologies in Psoriasis and Atopic Dermatitis
- Source :
- Psoriasis: Targets and Therapy, Vol Volume 14, Pp 87-92 (2024)
- Publication Year :
- 2024
- Publisher :
- Dove Medical Press, 2024.
-
Abstract
- Kathryn Haran,1,* Allison Kranyak,1,* Chandler E Johnson,2 Payton Smith,2 Aaron S Farberg,3,4 Tina Bhutani,1 Wilson Liao1,2 1Department of Dermatology, University of California San Francisco, San Francisco, CA, USA; 2Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA; 3Baylor Scott & White Health System, Dallas, TX, USA; 4Bare Dermatology, Dallas, TX, USA*These authors contributed equally to this workCorrespondence: Kathryn Haran, Department of Dermatology, University of California San Francisco, 2340 Sutter St N414, San Francisco, CA, 94115, USA, Tel +1 (415) 944-7618, Email Kathryn.haran@ucsf.eduAbstract: While psoriasis and atopic dermatitis (AD) are two common dermatological conditions, their diagnosis and therapeutic decision-making pathways are often complex. As a result, there has been increased focus on the development of precision medicine approaches for psoriasis and AD. Two companies at the forefront of dermatology precision medicine research are Mindera Health and Castle Biosciences. Here, we review the technologies developed by these two companies using a dermal diagnostic patch and superficial skin scrapings, respectively, their research published to date, and their future research goals. Research from both companies shows promise in predicting the response of inflammatory skin disease to biologics using minimally invasive techniques. However, challenges to adoption include insurance coverage and patient trust in the technologies. While there are several differences between Mindera Health and Castle Biosciences, they have a shared goal of utilizing minimally invasive technologies to sample skin and predict response to biologic treatments using a panel of optimized biomarkers.Keywords: machine learning, genetics, technology, diagnosis
- Subjects :
- machine learning
genetics
technology
diagnosis
Dermatology
RL1-803
Subjects
Details
- Language :
- English
- ISSN :
- 2230326X
- Volume :
- ume 14
- Database :
- Directory of Open Access Journals
- Journal :
- Psoriasis: Targets and Therapy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9248ba6b91840839c96b0927c83f72b
- Document Type :
- article