Atopic Dermatitis Opens the Era of Personalized Treatment
Jul 15, 2024
The development of biomarkers for diagnosing atopic dermatitis and predicting treatment outcomes has been summarized. It is expected that personalized treatment for allergic diseases such as atopic dermatitis will be accelerated.
Professor Park Chang-wook of Severance Hospital, honorary professor Lee Kwang-hoon of Yonsei University, and researcher Kim Soo-min of Yonsei University's Medical Life Sciences Department announced on the 15th that they have compiled the latest biomarkers that can be used to diagnose atopic dermatitis, observe progress, and predict treatment outcomes through international joint research with a research team at Bonn University School of Medicine in Germany.
Recently, a new drug that selectively blocks only the allergic immune response of atopic dermatitis has been developed in earnest and is actively used in the clinical field. However, there is no standard for personalized treatment strategies, such as treating only the condition of the visible lesion.
Professor Park Chang-wook's research team synthesized related papers based on clinical data accumulated by treating atopic dermatitis patients for 10 years from 2014.
Classification of diseases based on endotype (endotype), which has recently attracted attention from academia, such as race, age, and skin immune status, and test items such as blood, skin tissue, and urine derived from the classification were summarized. Furthermore, the theory and promising biomarkers that will be the basis for establishing personalized treatment strategies, such as the concept of predicting the occurrence of accompanying allergies, are covered.
Professor Park Chang-wook presented the concept and direction of biomarker research at the same time as a collection of biomarker items that were difficult for doctors in the clinical field to access"It is expected that treatment based on individual skin immune conditions, identification of risks from atopic dermatitis to asthma, and prediction of responses to specific treatments will be possible." The results of this study were published in the latest issue of the international journal 'eBioMedicine (IF 11.1)'.
Professor Park Chang-wook of Severance Hospital, honorary professor Lee Kwang-hoon of Yonsei University, and researcher Kim Soo-min of Yonsei University's Medical Life Sciences Department announced on the 15th that they have compiled the latest biomarkers that can be used to diagnose atopic dermatitis, observe progress, and predict treatment outcomes through international joint research with a research team at Bonn University School of Medicine in Germany.
Recently, a new drug that selectively blocks only the allergic immune response of atopic dermatitis has been developed in earnest and is actively used in the clinical field. However, there is no standard for personalized treatment strategies, such as treating only the condition of the visible lesion.
Professor Park Chang-wook's research team synthesized related papers based on clinical data accumulated by treating atopic dermatitis patients for 10 years from 2014.
Classification of diseases based on endotype (endotype), which has recently attracted attention from academia, such as race, age, and skin immune status, and test items such as blood, skin tissue, and urine derived from the classification were summarized. Furthermore, the theory and promising biomarkers that will be the basis for establishing personalized treatment strategies, such as the concept of predicting the occurrence of accompanying allergies, are covered.
Professor Park Chang-wook presented the concept and direction of biomarker research at the same time as a collection of biomarker items that were difficult for doctors in the clinical field to access"It is expected that treatment based on individual skin immune conditions, identification of risks from atopic dermatitis to asthma, and prediction of responses to specific treatments will be possible." The results of this study were published in the latest issue of the international journal 'eBioMedicine (IF 11.1)'.
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