The 2-year rodent bioassay in drug and chemical carcinogenicity testing: Performance, utility, and configuration for cancer hazard identification

A modular strategy for the testing and assessment of non-genotoxic carcinogens

A modular strategy is described for the testing and assessment (MoSt) of non-genotoxic carcinogenicity (NGTxC) that is suitable for regulatory applications. It utilizes and builds upon work conducted by the OECD expert group on NGTxC. The approach integrates relevant test methods from the molecular- to cellular- and further to tissue level, many of which have been recently reviewed. Six progressive modules are included in the strategy. Advice is provided for the iterative selection of the next appropriate test method within each step of the strategy. Assessment is completed by a weight of evidence conclusion, which integrates the different streams of modular information. The assessment method gives higher weight to findings that are mechanistically linked with biological relevance to carcinogenesis. With a focus on EU-REACH, and pending upon successful test method validation and acceptance, this will also enable the MoSt for NGTxC to be applied for regulatory purposes across different regulatory jurisdictions.

Setting course for a translational pharmacology and a predictive toxicology based on the numerical probability of clinical relevance

For a significant share of the chemicals, current bioassays mispredicted the outcomes in the reference methods they simulate. For any drug or chemical, and depending on the regulatory or corporate situation, three different approaches calculate the numerical probability by which agreement (or discrepancy) can be statistically expected between (1) the result of a predictive bioassay, and (2) the outcome on its reference method. If such concordance is expected with enough confidence based on a sufficient percentage probability, then specific results from that bioassay can be considered as correctly predictive. The statistical approaches analyzed in this article assist in valuable tasks, including (1) a better translation of the clinical relevance (or insignificance) of specific preclinical findings; (2) waiving unnecessary animal testing (or any other unpredictive testing; e.g., a given in vitro bioassay), and (3) in advancing only the most promising candidates in the pharmaceutical, pesticide, or chemical development process.

Applying Bayesian forecasting to predictive toxicology: the probability of innate carcinogenicity to humans of dyes synthesized from benzidine

The preclinical identification of health hazards relies on the performance (the historic agreement with the ultimate gold standard) of regulatorily recommended bioassays. However, any screening testing with less than 100% sensitivity, or 100% specificity, can deliver false results (outcomes discordant to the ultimate gold standard). Conversely, the predictive values approach (a.k.a. Bayesian forecasting) weighs (1) the performance of the predictive bioassay (battery, or framework) with (2) the prevalence of -positivity to the ultimate gold standard- in the most representative category to which the substance in evaluation can be allocated. Thus, the predictive values approach (PVA) provides the quantitative probability of toxicity to humans for substances that, circumstantially, are evaluable only through nonclinical data. Consequently, the PVA improves the predictivity of nonclinical toxicology, increasing the potential impact of hazard identifications based on preclinical data only. This article aimed to introduce the PVA through a worked example. Due to their toxicological homogeneity and public health relevance, the superfamily of colorants derived from benzidine (BZ) or some mutagenic congeners was selected (hereafter mentioned as BZ-related-colorants). For 259 BZ-related-colorants, the numeric probability of innate carcinogenicity to humans was estimated (from rodent carcinogenicity bioassays) or predicted (from alternative methods) through the PVA. A discussion was provided on (1) some limitations and implications of the PVA, and (2) the probable significance of the predictive values figured for up to 259 BZ-related-colorings.