Santa Cruz, CA, April 2017 – SomaGenics presented recent progress in its wound healing therapeutic program at the joint meeting of the Symposium on Advanced Wound Care and the Wound Healing Society (SAWC/WHS) in San Diego. Brian Johnston, Ph.D., CEO of SomaGenics discussed SomaGenics’ use of its sshRNA® (synthetic short hairpin RNA) platform to treat chronic wounds in a diabetic animal model in a talk entitled “Treating chronic diabetic wounds: A small RNA approach.”
“We are excited to present results which clearly demonstrate the ability of SomaGenics’ sshRNA® therapeutic candidates to accelerate wound healing,” stated Dr. Johnston, “We have identified effective inhibitors of key regulators of the wound healing pathway whose administration resulted in a therapeutically significant increase in rate of wound closure in diabetic mice.”
SomaGenics’ NIH-funded project to accelerate wound healing in diabetic patients aims at restoring the normal wound-healing response, which is impaired in diabetics. In healthy people, tissue injury induces a healing response that involves repair of the tissue and formation of new blood vessels. A factor called HIF-1αpromotes this response. Inhibition of the enzyme PHD2, a crucial cellular oxygen sensor, stabilizes expression of HIF-1α to restore the wound healing process in diabetics. The research was performed in collaboration with LayerBio, Inc. of Arlington, MA, and the laboratory of Dr. Geoffrey Gurtner of Stanford University School of Medicine.
SomaGenics is a privately held biotech company with offices and laboratories located in Santa Cruz, Calif. It specializes in developing innovative technologies that focus on RNA molecules as therapeutic agents and targets as well as biomarkers. The company's therapeutic platform includes sshRNA therapeutic candidates for viral hepatitis as well as for wound healing. SomaGenics’ RNA analysis platforms include miR-ID®, a novel circularization-based RT-qPCR method, miR-Direct™ for microRNA analysis directly from blood samples, and the RealSeq™ family of technologies for non-biased small RNA library construction for next-generation sequencing (NGS).