Analyses of neurobehavioral screening data: Dose–time–response modeling of continuous outcomes

De-risking in Tier I CNS safety assessments is the primary function of study design and technical training of laboratory staff observers

Derisking is not a pharmaceutical industry strategy to reduce time, effort, or costs in drug development. Derisking strategies originated within the National Institutes of Health as a predicate to good science. There is a growing sentiment within drug development programs to diminish the importance of behavioral measures in toxicological studies and in the Tiered Safety assessment plans of the U.S. Regulatory Agencies and the International Commission on Harmonization. The validity and reliability of the Functional Observational Batter (FOB) is critically dependent on consistency and technical quality in each risk assessment plan. US Federal and International drug approval organizations have universally adopted the concept of principles of test construction rather than delineating specific behavioral assay endpoints for inclusion of the FOB in nonclinical safety protocols. The validity and reliability of behavioral observations in standardized neurotoxicity screening is critically dependent on the FOB developed by the Study Director with the Sponsor throughout all stages of testing.. The individual risk factors selected for observation to be included in the early Tier 1 safety program should be determined by the mechanism and mode of action of the test article. The results of Tier I testing are the basis for Tier II testing designs. Critical to the compliance with Good Laboratory Practices is the documentation of training of the operational staff scheduled to conduct all aspects of the established protocol.

Dose-Time-Response Cumulative Multinomial Generalized Linear Model

In toxicological and pharmaceutical experiments, a type of quantal bioassay experiment is designed in which a response, such as mortality, in a group of animals is recorded over time points under different dose levels in the course of the experiment. The application of the typical logit and probit analyses is no longer valid in this situation because it neglects the dependency on time and also the possible interaction of time and dose concentration on the response in the experiment. In this paper, a dose-time-response model is proposed for this type of experiment and a cumulative multinomial generalized linear model that incorporates time and the other experimental conditions as covariates is developed by the theory of maximum likelihood estimation. Both the point estimator and confidence bands for ED50(t), the concentration of a toxicant that will kill 50% of the animals by a specific time, t; as well as LT50(d), the time to 50% mortalities for a specific concentration, d, is then formulated in closed form from the newly proposed dose-time-response model. Finally, the newly proposed model is considered for a real data set to demonstrate the application.

Neurological Effects of White Spirit: Contribution of Animal Studies during a 30-Year Period*

Numerous studies have suggested that long-term occupational exposure to white spirit may cause chronic toxic encephalopathy (WHO 1996). This review summarizes the chronic nervous system effects of white spirit in animal studies during a 30-year period. First, routine histopathology was consistently unable to reveal adverse peripheral or central nervous system effects after inhalation of white spirit. Second, neurobehavioural studies in animals showed no adverse effect after inhalation of white spirit with a high content of aromatics in contrast to what was found with products with a low content. Third, white spirit with a high content of aromatics induced adverse neurochemical changes at inhalation of 400 ppm and possibly already at 100 ppm. In the studied parameters, white spirit with a low content of aromatics showed no clear adverse neurochemical effects at inhalation of 400 ppm, but the neurophysiological tests showed adverse effects at this level. Fourth, neurophysiological methods may be more sensitive than histopathological, neurobehavioural and neurochemical methods. Overall, white spirit with a high and a low content of aromatics showed no overt difference in long-term effects in animals, taking all studied end-points into account. The differences in sensitivity of the test methods should be taken into consideration if new toxicological studies are conducted on this type of solvents.

Analyses of neurobehavioral screening data: Benchmark dose estimation

Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose-time-response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240-255) have recently applied dose-time-response models to longitudinal or time-course neurotoxicity data, and have illustrated the modeling process using continuous data from a functional observational battery (FOB). Following the work of these authors, the purpose of this paper is to show that the benchmark dose (BMD) method for single time point dose-response data can be generalized and applied to longitudinal data such as those generated in neurotoxicity studies. We propose a statistical procedure called bootstrap method for computing the lower confidence limits for the BMD. We demonstrate the method using three previously published FOB datasets of triethyltin (Moser, V.C., Becking, G.C., Cuomo, V., Frantik, E., Kulig, B., MacPhail, R.C., Tilson, H.A., Winneke, G., Brightwell, W.S., DeSalvia, M.A., Gill, M.W., Haggerty, G.C., Hornychova, M., Lammers, J., Larsson, J., McDaniel, K.L., Nelson, B.K., Ostergaard, G., 1997a. The IPCS study on neurobehavioral screening methods: results of chemical testing. Neurotoxicology 18, 969-1056.) and the models of Zhu et al. (Zhu, Y., Wessel, M., Liu, T., Moser, V.C., 2005. Analyses of neurobehavioral screening data: dose-time-response modeling of continuous outcomes. Regul. Toxicol. Pharmacol. 41, 240-255).