Predictive in silico modeling of emetic potency of liquid cleaning products using an historical in vivo database. (December 2020)

• Record Type: Journal Article
• Authors: Li, S.; Meli, F.; Vinson, P.; Broening, H.W.; Andrews, P.L.R.; Nash, J.F.
• Is Part Of: Food and chemical toxicology. Volume 146(2020)
• Publication Date: 2020-12
• Subjects: Emesis -- In silico -- Multivariate analysis -- Nausea -- 3Rs -- Recursive partitioning analysis -- Vomiting; Toxicology -- Periodicals; Food poisoning -- Periodicals; Food Poisoning -- Periodicals; Toxicology -- Periodicals; Toxicologie -- Périodiques; Intoxications alimentaires -- Périodiques; Food poisoning; Toxicology; Periodicals; Electronic journals; 615.9
• DOI: 10.1016/j.fct.2020.111833
• Languages: English
• ISSNs: 0278-6915

Abstract

Abstract: The induction of vomiting by activation of mechanisms protecting the body against ingested toxins is not confined to natural products but can occur in response to manmade medicinal and non-medicinal products such as liquid cleaning products where it is a commonly reported adverse effect of accidental ingestion. The present study examined the utility of an historic database (>30 years old) reporting emetic effects of 98 orally administered liquid cleaning formulations studied in vivo (canine model) to objectively identify the main pro-emetic constituents and to derive a predictive model. Data were analysed by categorizing the formulation constituents into 10 main groups followed by using multivariate correlation, partial least squares and recursive partitioning analysis. Using the ED50 we objectively identified high ionic strength, non-ionic surfactants (alcohol ethoxylate) and alkaline pH as the main pro-emetic factors. Additionally, a mathematical model was developed which allows prediction of the ED50 based on formulation. The limitations of the use of historic data and the model are discussed. The results have practical applications in new product formulation and safety but additionally the principles underpinning this in silico study have wider applicability in demonstrating the potential utility of such archival data in current research contributing to animal replacement. Highlights: Constituents causing the emetic effect of ingested liquid cleaning formulations are unknown. Recursive partitioning was used to model historic in vivo data on 98 liquid cleaning formulations. Emesis was positively associated with ionic strength, non-ionic surfactant, and high alkaline pH. The mathematical model predicted the ED50 from formulation composition. Application to product development, safety and wider assessment of emetic liability is discussed.