Virtual Patients and In Silico Clinical Studies Improve Blue Light Treatment for Psoriasis

A new study supports the use of virtual patients and in silico clinical studies to evaluate the effectiveness of blue light to reduce the symptoms of psoriasis. Researchers also demonstrated that this in silico approach can be used to improve the treatment response of patients with psoriasis to blue light by modifying the settings of the therapeutic protocol, as reported in the study published in Systems Medicine, an open access journal from Mary Ann Liebert, Inc., publishers. Click here to read the full article free on the Systems Medicine: Journal of Medical Systems Biology and Network Medicine website through September 5, 2019.

"In silico Clinical Studies on the Efficacy of Blue Light for Treating Psoriasis in Virtual Patients" was coauthored by Zandra Félix Garza, Peter Hilbers, and Natal van Riel, Eindhoven University of Technology, The Netherlands, and Joerg Liebmann and Matthias Born, Philips Electronics Netherlands BV, Eindhoven. The researchers note that the current computational model for studying the efficacy of blue light therapy only reproduces the response in the average patient in clinical trials and does not take into account individual variations amongst patients. Use of a computational model combined with a refined pool of virtual patients can adequately capture the patient variability in the response to treatment with blue light and the decrease in disease severity seen in previous clinical investigations. The authors suggest that a minimum of 2,500 virtual patients, which they refined down from an initial pool of 500,000 virtual patients, are needed to reproduce the responses seen in clinical investigations.

"This is a highly promising approach towards using statistical learning on virtual patient populations to draw actionable clinical conclusions on real patients, and thus a major step forward to precision medicine," says Co-Editor-in-Chief Prof. Dr. Jan Baumbach from Technical University of Munich.

Most Popular Now

Research Shows AI Technology Improves Pa…

Existing research indicates that the accuracy of a Parkinson's disease diagnosis hovers between 55% and 78% in the first five years of assessment. That's partly because Parkinson's sibling movement disorders...

Who's to Blame When AI Makes a Medi…

Assistive artificial intelligence technologies hold significant promise for transforming health care by aiding physicians in diagnosing, managing, and treating patients. However, the current trend of assistive AI implementation could actually...

First Therapy Chatbot Trial Shows AI can…

Dartmouth researchers conducted the first clinical trial of a therapy chatbot powered by generative AI and found that the software resulted in significant improvements in participants' symptoms, according to results...

DMEA sparks: The Future of Digital Healt…

8 - 10 April 2025, Berlin, Germany. Digitalization is considered one of the key strategies for addressing the shortage of skilled workers - but the digital health sector also needs qualified...

DeepSeek: The "Watson" to Doct…

DeepSeek is an artificial intelligence (AI) platform built on deep learning and natural language processing (NLP) technologies. Its core products include the DeepSeek-R1 and DeepSeek-V3 models. Leveraging an efficient Mixture...

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...