While cosmetics companies are not obliged by law to test for efficacy, claims made about product performance cannot be misleading to the consumer and have to be supported with data of some kind.
But, as efficacy testing is not a legal requirement, there are no official regulatory guidelines as to how to go about the research and how to translate the findings into product claims.
Definition of a cosmetic
At the recent HBA show in New York, Head of R&D at Lipo Chemicals, Nava Dayan, explained that one of the challenges facing companies embarking on efficacy testing, is the official definition of a cosmetic.
According to the FDA’s definition, a cosmetic product, unlike a drug, does not change the structure or function of the skin. This leaves cosmetic companies trying to find a way to convince the consumer that the product works, without saying anything that suggests the products could alter skin structure and function.
“The FDA is monitoring the claims you make…if a cosmetics company is making a drug-like claim, saying that the product is changing in some way the structure and function of the skin then the FDA can go back to the company and say ‘if it really does that, take the drug route and submit a drug master file, and if it doesn’t then withdraw it from the market and change the claims’,” Dayan told CosmeticsDesign.com USA.
Functional claims are challenging
However, some tests do show functional changes related to cosmetic products, and these are very difficult to translate into claims.
“As science is evolving, and we are finding more and more ways to test things, claims are becoming more complicated,” she said
Dayan highlighted data at the DNA level, which is increasingly being used to highlight the mechanism of an ingredient or product, as being particularly difficult to translate into a claim acceptable to the consumer and the regulatory bodies.
Regarding data collection, Dayan said it is important to bear in mind that study design must reflect the objective. For example, study participants should reflect the eventual users of the product, and study size should be designed to yield statistically significant results.