RapMixTox: Rapid and automated prediction of complex mixture toxicity by nontarget instrumental analysis

Understanding the toxicity of real-world complex mixtures, and identification of the most toxic chemicals is an essential starting point for intelligent design of water treatment solutions.

Previous experience shows that only a small fraction of chemical mixture toxicity can be explained by known chemical contaminants monitored by targeted analytical methods.

The reason is that there are over 350,000 chemicals registered for use globally,1 and only a few hundred of these have ever been monitored in the environment.

Moreover, evaluating the toxicity of newly recognized contaminants is expensive and slow, and therefore often lags behind their environmental detection.

In this proposed research, we will develop and validate a novel methodology to accurately predict the whole mixture toxicity as well as pinpoint known and unknown chemicals contributing most to mixture toxicity, baseline toxicity and receptor-based.

Our approach relies on estimated physicochemical properties and empirical spectral information acquired rapidly in nontarget liquid chromatography (LC) high-resolution mass spectrometry (HRMS) instrumental analysis, and subsequent rapid toxicity modelling.

With this novel approach developed in RapMixTox, it will become possible to accurately identify toxic mixtures, to pinpoint the responsible compounds, and thus to implement rapid treatments or alternative manufacturing processes without the delay and expense of structural characterizations or animal testing.