Recommendations for harmonization of data collection and analysis of developmental neurotoxicity endpoints in regulatory guideline studies: Proceedings of workshops presented at Society of Toxicology and joint Teratology Society and Neurobehavioral Teratology Society meetings.

The potential for developmental neurotoxicity (DNT) of environmental chemicals may be evaluated using specific test guidelines from the US Environmental Protection Agency or the Organisation for Economic Cooperation and Development (OECD). These guidelines generate neurobehavioral, neuropathological, and morphometric data that are evaluated by regulatory agencies globally. Data from these DNT guideline studies, or the more recent OECD extended one-generation reproductive toxicity guideline, play a pivotal role in children's health risk assessment in different world areas. Data from the same study may be interpreted differently by regulatory authorities in different countries resulting in inconsistent evaluations that may lead to inconsistencies in risk assessment decisions internationally, resulting in regional differences in public health protection or in commercial trade barriers. These issues of data interpretation and reporting are also relevant to juvenile and pre-postnatal studies conducted more routinely for pharmaceuticals and veterinary medicines. There is a need for development of recommendations geared toward the operational needs of the regulatory scientific reviewers who apply these studies in risk assessments, as well as the scientists who generate DNT data sets. The workshops summarized here draw upon the experience of the authors representing government, industry, contract research organizations, and academia to discuss the scientific issues that have emerged from diverse regulatory evaluations. Although various regulatory bodies have different risk management decisions and labeling requirements that are difficult to harmonize, the workshops provided an opportunity to work toward more harmonized scientific approaches for evaluating DNT data within the context of different regulatory frameworks. Five speakers and their coauthors with neurotoxicology, neuropathology, and regulatory toxicology expertise discussed issues of variability, data reporting and analysis, and expectations in DNT data that are encountered by regulatory authorities. In addition, principles for harmonized evaluation of data were suggested using guideline DNT data as case studies.

Repeated-measure analyses: Which one? A survey of statistical models and recommendations for reporting.

Repeated-measure analysis of variance is a general term that can imply a number of different statistical models used to analyze data from studies in which measurements are taken from each subject on more than one occasion. Repeated-measure analyses encompass univariate models (with or without sphericity adjustment), multivariate models, mixed models, analysis of covariance, multilevel models, latent growth models, and hybrids of these models. These models are based on different assumptions, especially regarding correlations (sphericity) between within-subject factors, which comprise the variance-covariance matrix. Violation of this assumption may lead to misleading and erroneous conclusions. Because many papers do not provide enough information about what analysis was really conducted, and about why it was done, the reader is unable to evaluate the validity of the analysis. Here a brief overview of several of the most commonly used models for analyzing data from repeated-measure designs is provided, and guidance is suggested for describing the statistical approach employed. The goals of this paper are (1) to give authors an overview of the diversity of commonly used models and associated assumptions, and (2) to facilitate reporting sufficient information about the tests to allow the reader to evaluate the validity of the tests and the credibility of the inferences made by the authors. Among the available approaches to repeated-measure analyses, the mixed model is recommended for its flexibility in handling different covariance structures and its insensitivity to missing data. Whether or not it is used, the overall guiding principles in reporting should always be Accuracy, Completeness, and Transparency (ACT principles): tell the reader precisely all what you did and why.

DNA damage repair genes controlling human papillomavirus (HPV) episome levels under conditions of stability and extreme instability.

DNA damage response (DDR) genes and pathways controlling the stability of HPV episomal DNA are reported here. We set out to understand the mechanism by which a DNA-binding, N-methylpyrrole-imidazole hairpin polyamide (PA25) acts to cause the dramatic loss of HPV DNA from cells. Southern blots revealed that PA25 alters HPV episomes within 5 hours of treatment. Gene expression arrays identified numerous DDR genes that were specifically altered in HPV16 episome-containing cells (W12E) by PA25, but not in HPV-negative (C33A) cells or in cells with integrated HPV16 (SiHa). A siRNA screen of 240 DDR genes was then conducted to identify enhancers and repressors of PA25 activity. Serendipitously, the screen also identified many novel genes, such as TDP1 and TDP2, regulating normal HPV episome stability. MRN and 9-1-1 complexes emerged as important for PA25-mediated episome destruction and were selected for follow-up studies. Mre11, along with other homologous recombination and dsDNA break repair genes, was among the highly significant PA25 repressors. The Mre11 inhibitor Mirin was found to sensitize HPV episomes to PA25 resulting in a ∼5-fold reduction of the PA25 IC50. A novel assay that couples end-labeling of DNA to Q-PCR showed that PA25 causes strand breaks within HPV DNA, and that Mirin greatly enhances this activity. The 9-1-1 complex member Rad9, a representative PA25 enhancer, was transiently phosphorylated in response to PA25 treatment suggesting that it has a role in detecting and signaling episome damage by PA25 to the cell. These results establish that DNA-targeted compounds enter cells and specifically target the HPV episome. This action leads to the activation of numerous DDR pathways and the massive elimination of episomal DNA from cells. Our findings demonstrate that viral episomes can be targeted for elimination from cells by minor groove binding agents, and implicate DDR pathways as important mediators of this process.

Development and validation of novel enzyme activity methods to assess inhibition of matrix metalloproteinases (MMPs) in human serum by antibodies against enzyme therapeutics.

This paper summarizes the development and validation of five enzyme activity methods to assess the specific inhibition of human endogenous matrix metalloproteinases MMP-1 (interstitial collagenase), MMP-2 (gelatinase A), MMP-3 (stromelysin 1), MMP-8 (collagenase 2) and MMP-13 (collagenase 3) by anti-Collagenase Clostridium histolyticum (CCH) antibodies in human serum. These MMPs are of interest since antibodies against a therapeutic enzyme may cross-react with, and inactivate, the MMPs. The validated methods utilize spiked exogenous individual MMPs added to serum to determine if the serum inhibits MMP enzyme activity. Factors evaluated and optimized during development include pH, reaction time and temperature, inhibitor concentration for the positive control, and substrate and serum concentration. Characteristics established during validation for each MMP activity inhibition method included intra- and inter-assay precision and recovery, recovery in the pooled normal human serum samples, bench-top stability at room temperature and on wet ice, and assay cut-point determination. Precision results ranged from ~1 to 12% CV, recoveries of the activities of the exogenous MMPs ranged from ~84 to 90% and cut-point values ranged from 67 to 91%.

Rank-based estimate of four-parameter logistic model.

During drug development, the calculation of inhibitory concentration that results in a response of 50% (IC50) is performed thousands of times every day. The nonlinear model most often used to perform this calculation is a four-parameter logistic, suitably parameterized to estimate the IC50 directly. When performing these calculations in a high-throughput mode, each and every curve cannot be studied in detail, and outliers in the responses are a common problem. A robust estimation procedure to perform this calculation is desirable. In this paper, a rank-based estimate of the four-parameter logistic model that is analogous to least squares is proposed. The rank-based estimate is based on the Wilcoxon norm. The robust procedure is illustrated with several examples from the pharmaceutical industry. When no outliers are present in the data, the robust estimate of IC50 is comparable with the least squares estimate, and when outliers are present in the data, the robust estimate is more accurate. A robust goodness-of-fit test is also proposed. To investigate the impact of outliers on the traditional and robust estimates, a small simulation study was conducted.

Influence of molecular flexibility and polar surface area metrics on oral bioavailability in the rat.

The relationship of rotatable bond count (N(rot)) and polar surface area (PSA) with oral bioavailability in rats was examined for 434 Pharmacia compounds and compared with an earlier report from Veber et al. (J. Med. Chem. 2002, 45, 2615). N(rot) and PSA were calculated with QikProp or Cerius2. The resulting correlations depended on the calculation method and the therapeutic class within the data superset. These results underscore that such generalizations must be used with caution.

Biophysical characterization of a large conductance anion channel in hypodermal membranes of the gastrointestinal nematode, Ascaris suum.

Patch-clamp recordings from muscle- and cuticle-facing hypodermal membranes of the gastrointestinal nematode Ascaris suum reveal a high-conductance, voltage- sensitive Ca(2+) -dependent Cl(-) channel. The hypodermal channel has a conductance of 195 pS in symmetrical 160 mM NaCl. The open probability of the channel is highly voltage-sensitive, and channel activity is not observed when Ca(2+) is reduced to <100 microM. The channel is permeable to organic anions that are major end-products of carbohydrate metabolism in A. suum, including acetate, butyrate and 2-methylvalerate. The conductances and relative permeabilities of these organic anions are inversely related to size, with 2-methylvalerate being only approximately 3% as permeable as Cl(-). The diameter of the channel pore was 12.3+/-0.2 A, calculated from the relative permeability coefficients of Cl(-) and the organic anions. Results of this study are consistent with the hypothesis that the large conductance anion channel in A. suum hypodermal membranes provides a low energy pathway for organic anion excretion from the hypodermal compartment, followed by diffusion across the aqueous channels of the cuticle matrix.

Predicting drug absorption: how nature made it a difficult problem.

Significant recent work has focused on predicting drug absorption from structure. Several misperceptions regarding the nature of absorption seem to be common. Among these is that intestinal absorption, permeability, fraction absorbed, and, in some cases, even bioavailability, are equivalent properties and can be used interchangeably. A second common misperception is that absorption, permeability, etc. are discrete, fundamental properties of the molecule and can be predicted solely from some structural representation of the drug. In reality, drug absorption is a complex process dependent upon drug properties such as solubility and permeability, formulation factors, and physiological variables, including regional permeability differences, pH, lumenal and mucosal enzymology, and intestinal motility, among others. This article will explore the influence of these different variables on drug absorption and the implications with regards to attempting to develop predictive drug absorption algorithms.