What are chemical signatures, and why are they essential to RIFM’s read-across process?
The Research Institute for Fragrance Materials, or RIFM, uses an internationally accepted approach called read-across to assess the safety profile of fragrance ingredients that lack sufficient data. In this process, study data on one ingredient (the “read-across analog”) can be used as a proxy for another ingredient (the “target material”) as long as the two are similar enough. RIFM has saved over half a million animals using read-across and other animal-alternative methodologies. (RIFM does not perform animal tests to ensure human health.)
But how do RIFM scientists determine that fragrance ingredients are similar enough to be used for read-across?
Chemical signatures, also referred to as structural activity groups, act like addresses for ingredients, and they capture all their essential structural features. Fragrance ingredients with identical chemical signatures or “addresses” are grouped into the same cluster (or grouping) meaning they are structurally similar enough to be used as read-across analogs for each other. The format of a chemical signature is similar to how one would denote specificity in a geographical location (e.g., continent / country / state / city / neighborhood). For example, the chemical signature of anisole (CAS # 100-66-3) is:
Oxygen-containing / ethers / mono-ether / aryloxy / cyclic / mono-cyclic / aromatic / straight-chain / saturated / C6-C13.
RIFM scientists saw the need for, and developed, a more nuanced grouping method to assist with individual fragrance ingredient safety assessments. Over many years, we have improved our processes and refined these clusters or groups to be smaller and more scientifically robust. Our current approach allows us to simply use a decision tree to figure out the chemical signature of any existing chemical.
While chemical signatures are central to the read-across selection process, they are just the first step because they only consider the materials’ chemistry. Grouping ingredients into clusters based on chemical signatures allows for easier selection of potential read-across analogs. RIFM scientists can then determine if they can use an ingredient outside the target material’s immediate cluster (i.e., with a different chemical signature) for read-across based on other factors like toxicology, metabolism, and endpoint specificity. They use data from the various toxicological endpoints and expert judgment to achieve this.
At RIFM, we strive to collaborate to further the safety of consumers. To share our work, we are currently working on a publication on the specifics of the decision tree and chemical signature process, as well as an automated tool that follows the decision tree to provide a chemical signature for any chemical.
Jake Muldoon, PhD, Senior Associate Scientist, Chemistry, supports RIFM’s computational chemistry efforts, including read-across solutions.