Mindera Health has announced positive results from its randomized, prospective MATCH clinical trial, demonstrating that its precision medicine test for psoriasis, Mind.Px, significantly improves treatment outcomes and alters physician prescribing behavior. The 16-week study, published in Dermatology and Therapy on May 11, 2025, provides Level 1 evidence supporting the test's clinical utility in personalizing biologic therapy for psoriasis patients.
The study enrolled 205 patients with moderate to severe psoriasis, randomizing them into two groups: an "informed" group where physicians had access to Mind.Px test results, and an "uninformed" group where physicians treated patients without this information. Statistical analysis revealed that physicians with access to Mind.Px results showed significantly altered prescribing behavior, with 93.1% concordance between prescribed treatments and test recommendations, compared to only 65.4% in the control group.
More importantly, patients whose physicians followed Mind.Px recommendations not only reached the clinical endpoint (PASI75) at the standard 12-week mark but achieved this milestone significantly faster, with some patients showing response as early as week 4.
Addressing a Major Healthcare Burden
Psoriasis affects more than three percent of the U.S. population, resulting in healthcare costs exceeding $110 billion annually. Current biologic treatments have a success rate of only about 52%, leading to costly trial-and-error approaches to patient care. Mind.Px aims to transform this paradigm by providing a predictive test with over 91% positive predictive value.
"The findings of the MATCH study are exciting as they demonstrate the application of a precision medicine tool in clinical practice. Demonstrating that matching up patient biology and biologic drug class can lead to faster achievement of the clinical endpoint realizes the promise of precision medicine," said lead author Bruce E. Strober, MD, PhD of Central Connecticut Dermatology and Yale University School of Medicine.
Innovative Technology Platform
Mind.Px employs a proprietary dermal biomarker patch that extracts transcriptomic information from the skin in just minutes. The collected RNA undergoes Next-Generation Sequencing, creating a genetic and transcriptomic snapshot of the patient's skin. Machine learning algorithms then analyze this data to predict which biologic drug will be most effective for that specific patient.
"This study is a large step forward for precision medicine in dermatology," noted Tobin J. Dickerson, PhD, Chief Scientific Officer and Co-founder of Mindera Health. "These findings provide Level 1 evidence and validate Mind.Px as a disruptive clinical decision support tool for psoriasis patients. We are excited to bring this innovation to broader market adoption."
Potential for Healthcare Cost Reduction
The ability to accurately predict treatment response before initiating expensive biologic therapies represents a significant advancement in psoriasis management. By reducing the trial-and-error approach currently used, Mind.Px could potentially save healthcare systems substantial costs while improving patient outcomes.
The platform's capability to collect patient data at scale creates a powerful tool for reducing healthcare expenses, particularly when applied to predicting responses to high-cost treatments. The technology captures various biomarkers, including DNA, RNA, protein, and small molecules.
Study Details and Authorship
The study, titled "Clinical Utility Findings of a Transcriptomic Psoriasis Biologic Test Demonstrate Altered Physician Prescribing Behavior and Improved Patient Outcomes," was coauthored by a team of distinguished dermatologists and researchers: Bruce E. Strober, Michael Bukhalo, April W. Armstrong, David Pariser, Leon Kircik, Brian Johnson, Paul Montgomery III, and Tobin J. Dickerson.
Mindera Health, based in the San Diego area, is a CLIA and CAP certified laboratory with ISO 13485:2016 certification. The company focuses on developing and commercializing medical technology that enables molecular-level skin analytics, with the goal of improving patient outcomes while reducing healthcare system costs.
