In Silico & Predictive Toxicology

Our work

Central to the understanding of a substance’s toxicity is a consideration of its Absorption, Distribution, Metabolism and Excretion. How efficiently is a substance absorbed by the human body? How is it broken down? Which tissues does it reach and is it likely to bioaccumulate? How does the body eliminate the substance? All this comes under the general heading of toxicokinetics (TK). Generating new TK data in the laboratory involves the use of animals, is time consuming and extremely costly (particularly if radiolabels are required). It is possible, however, to make expert predictions taking into account what is already known about the toxicity of a chemical, its structure and its physico-chemical properties.

Relevant properties for absorption (and other TK) assessment

In Silico

As well as using physico-chemical properties to predict TK properties, we make use of (Q)SAR software. The US EPA’s EPISuite tool allows physico-chemical properties to be predicted for compounds where experimental data are lacking. There are several “profilers” in the OECD (Q)SAR Toolbox that predict metabolic breakdown products; we have an expert partner who can conduct a similar analysis using the Meteor Nexus software.

TK Assessment under REACH

Conducting new toxicokinetic testing is not a requirement in the EU under the REACH regulation, but above 10 tonnes per year it is necessary to provide an assessment of the existing data. Understanding the toxicokinetic properties of a substance is very useful in determining the most appropriate route of exposure for future testing, likely target organs, and bioaccumulation potential, and in informing on the hazard and risk assessment (e.g. absorption values to be used in DNEL calculations).

Find out more about our work in REACH

Some of our case studies in this area

Literature review and in silico prediction of metabolites

Case study

As part of their overall regulatory requirements, the client was asked to provide information on the known or predicted metabolites of a number of ingredients in their products. This formed part of a broader programme of work that bibra conducted for this client.