Meet this year’s Derm Tank winner!
Contenders gave their pitches during the July 17 session and were scored for innovation, value, and commercial viability.
Sarah Antonevich, MS, and Kate Miller, BS, won this year’s annual Derm Tank competition with their concept InflammIQ, a low-cost, smart, wound-monitoring platform embedded into existing dressings to continuously detect early signs of infection and impaired healing through a visible bedside color change. The platform provides real-time, noninvasive surveillance across burns, surgical wounds, and hidradenitis suppurativa, supporting earlier clinical intervention and bedside wound assessment without the need for additional or costly specialized equipment. As this year’s winner, the team received $10,000 in seed money.
The competition included two other pitches:
Athira Sivadas, BA, presented Pandi, the patient-friendly companion dermatoscope. The highly affordable (less than $5), polarized light dermatoscope is designed to work with a patient’s smartphone to capture the types of quality images dermatologists are used to seeing in the clinic with dermatoscopes.
Michael Vittori, MD, PharmD, presented Atraumatic Forceps, a handheld surgical instrument designed for cosmetically sensitive procedures that atraumatically everts skin or soft-tissue edges, improves tissue control, and facilitates precise suture placement during wound closure.
The judges — Mark D. Kaufmann, MD, FAAD; Ashish Bhatia, MD, FAAD; and Arianne Shadi Kourosh, MD, MPH, FAAD — assessed each of the three final concepts for innovation, commercial viability, and value.
Last year, Katherine B. Lee, MD, FAAD, won the Derm Tank competition for CryoCaptures, a lightweight device adapter that records cryotherapy procedures using proprietary thermal image recognition and artificial intelligence (AI) technology. She attended the session and shared how her concept is in the pilot process in multiple dermatology clinics throughout the country. She also talked about the product’s evolution into a broader platform called c-Captures, focused on AI-driven image recognition technology.
