New Topical Formulation for Hair Loss Shows Promise
For some individuals, the emotional aspects of living with hair loss can be substantial and ultimately damage one’s self-esteem and lead to depression. Medical advancements made in recent decades have offered hope to millions of people that are affected, but not all patients experience results with the products currently available. One major reason for this is scalp hair loss is caused by a lot of different factors. Genetics, disease, hormonal changes, and aging are all possible contributors to an individual’s thinning hair. Scientists and researchers have made a lot of progress in understanding these causes, but there are still undiscovered pathways.
The most well-known treatments available today are non-invasive, painless, and are applied topically. These products have worked for a lot of people, but for others the results were minimal or the product has been completely ineffective. Also becoming more popular in recent years is hair transplantation, which is substantially more invasive and expensive than topical treatments.
For patients that have experienced little or no results from these treatments, there could soon be a new product available. Researchers at the University of Kansas have created a formula they are calling Murikal. The invention has shown in laboratory studies hair growth density of 80% greater than the most prominently available products. Like other topically applied treatments, Murikal is painless, non-invasive, and is easy to use. The research has also shown Murikal is safe and has no adverse effects when used at high doses, making it an ideal alternative to the products available in the marketplace today.
The University of Kansas applied for an international patent in January. The next step for the inventors of Murikal is to find partners to help fund future research.
If you are interested in learning more, a summary of this new technology is available. To view the laboratory test results of Murikal, please fill out the form below to access the data.