Alternative models in developmental toxicology

In light of various pressures, toxicologists have been searching for alternative methods for safety testing of chemicals. According to a recent policy in the European Union (Regulation, Evaluation Authorisation and Restriction of Chemicals, REACH), it has been estimated that over the next twelve to fifteen years, approximately 30,000 chemicals may need to be tested for safety, and under current guidelines such testing would require the use of approximately 7.2 million laboratory animals []. It has also been estimated that over 80%% of all animals used for safety testing under REACH legislation would be used for examining reproductive and developmental toxicity [Hofer et al., 2004]. In addition to REACH initiatives, it has been estimated that out of 5,000 to 10,000 new drug entities that a pharmaceutical company may start with, only one is finally approved by the Food and Drug Administration at a cost of over one billion dollars []. A large portion of this cost is due to animal testing. Therefore, both the pharmaceutical and chemical industries are interested in using alternative models and in vitro tests for safety testing. This review will examine the current state of three alternative models - whole embryo culture (WEC), the mouse embryonic stem cell test (mEST), and zebrafish. Each of these alternatives will be reviewed, and advantages and disadvantages of each model will be discussed. These models were chosen because they are the models most commonly used and would appear to have the greatest potential for future applications in developmental toxicity screening and testing.     

REACH: next step to a sound chemicals management

REACH is the new European Regulation for Registration, Evaluation, Authorisation and Restriction of Chemicals. It entered into force on 1st June 2007 to streamline and improve the former legislative framework on new and on existing chemical substances of the European Union. Companies which manufacture or import more than 1 tonne of a substance per year will be required to register the substance at the new EU Chemicals Agency located in Helsinki. REACH places greater responsibility on industry to manage the risks that chemicals may pose to the health and the environment and to provide safety information that will be passed down the supply chain. In principle, REACH applies to all chemicals as such, as components in preparations and as used in articles. REACH is a radical step forward in the EU chemicals management. The onus will move from the authorities to industry. In addition, REACH will allow the further evaluation of substances where there are grounds for concern, foresees an authorisation system for the use of substances of very high concern and a system of restrictions, where applicable, for substances of concern. The Authorisation system will require companies to switch progressively to safer alternatives where a suitable alternative exists. Current use restrictions will remain under REACH system.     

REACH and reproductive and developmental toxicology: still questions

Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) is a new chemicals regulation law in the European Union (EU). The law is supplemented by tens of thousands of pages of guidance documents, and the implementation of REACH is still a work in progress. Requirements for chemical testing are based on the annual volume of a chemical or 'substance' that is produced or imported into the EU. These requirements include reproductive and developmental toxicity testing in experimental animals for an annual volume of 10 metric tonnes or more. However, under REACH, the testing in vertebrate animals may not be performed without permission, and the law encourages the use of alternative methods of filling data gaps on the toxicological properties of chemicals. These alternatives might include in vitro and structure-activity relationship studies, but the REACH technical guidance indicates that these kinds of studies are not adequate to replace reproductive and developmental toxicity testing in whole animals. The most practical opportunity for the avoidance of whole animal testing may be 'read-across,' a process in which gaps are filled using data from related compounds. A method called 'weight of evidence' under REACH may also be used to avoid whole animal reproductive and developmental toxicity testing based on existing data in regulation and non-regulation studies and based on factors such as chemical structure and anticipated exposure. It is also possible that thresholds of toxicological concerns will be accepted under REACH as a method to avoid vertebrate animal testing.     

我国化学品毒性鉴定技术规范与REACH标准比对研究

[目的]了解我国现有的《化学品毒性鉴定技术规范》（以下简称＂规范＂）与化学品注册、评估、授权和限制（REACH）标准方法之间的差异,以提高我国的化学品毒性鉴定的质量和水平。[方法]对规范、REACH中的毒性鉴定方法按照不同的毒性分类进行比较。[结果]（1）REACH和规范中使用的方法大部分都源于经济合作与发展组织（OECD）的化学品毒性鉴定及其健康效应评价指南。因此,两者间在方法本质和原则上没有很大的差别。（2）异同点比较：①方法基本相同,特别是原理、试验体系、试验指标和评判终点都一致;②REACH主要采用OECD标准中运用时间长、接受面广、相对成熟的方法;③我国的标准在技术内容上和国际是接轨的,由于考虑到整体的检验水平还不高,因此对一些具体的操作步骤做出了更详细的规定,使标准更具规范性和实用性。[结论]从REACH与我国现行毒理学方法的对比分析中发现,在整体结构和原则上,我国的分析方法与REACH的方法有高度的相似性,但在某些试验方法方面也存在着差异。只有尽快在我国建立国际通用标准的毒理学检测良好实验室规范（GLP）实验室,才能从根本上提高中国实验室的检测能力。     

The gold industry standard for risk and cost of drug and vaccine development revisited

Gold dimensions of pharmaceutical drug development indicate that it takes on average 11.9 years, with an investment around US$ 0.8 Billion, to launch one product on the market. Furthermore, approximately 22% of the drug candidates successfully complete clinical testing. These universally acknowledged proportions largely originate from one single, much cited publication; Dimasi et al. [5]. However an additional six articles describing new chemical entities (NCE) development were identified, which contain little, if any, information on vaccines. Published cumulative success rates range from 7% to 78% and investments calculations span US$ 0.8 to 1.7 Billion. Obviously this disserves further clarification?     

Application of chemical toxicity distributions to ecotoxicology data requirements under REACH

The European Union's REACH regulation has further highlighted the lack of ecotoxicological data for substances in the marketplace. The mandates under REACH (registration, evaluation, authorization, and restriction of chemicals) to produce data and minimize testing on vertebrates present an impetus for advanced hazard assessment techniques using read-across. Research in our group has recently focused on probabilistic ecotoxicological hazard assessment approaches using chemical toxicity distributions (CTDs). Using available data for chemicals with similar modes of action or within a chemical class may allow for selection of a screening point value (SPV) for development of environmental safety values, based on a probabilistic distribution of toxicity values for a specific endpoint in an ecological receptor. Ecotoxicity data for acetylcholinesterase inhibitors and surfactants in Daphnia magna and Pimephales promelas were gathered from several data sources, including the U.S. Environmental Protection Agency's ECOTOX and Pesticides Ecotoxicity databases, the peer-reviewed literature, and the Human and Environmental Risk Assessment (HERA) project. Chemical toxicity distributions were subsequently developed, and the first and fifth centiles were used as SPVs for the development of screening-predicted no-effect concentrations (sPNECs). The first and fifth centiles of these distributions were divided by an assessment factor of 1,000, as recommended by REACH guidance. Use of screening values created using these techniques could support the processes of data dossier development and environmental exposure assessment, allowing for rigorous prioritization in testing and monitoring to fill data gaps.     

Generic exposure scenarios: their development, application, and interpretation under REACH

The European Union Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) Regulation (EC 1907/2006) places significant new obligations on the manufacturers or importers (M/Is) of chemicals in Europe. It also places new responsibilities on downstream users (DUs) of these chemicals i.e. those that purchase and use chemical products. In particular, for registered classified substances, the M/I is expected to communicate how any substance can be safely used without risk to man or the environment. This communication is in the form of an exposure scenario (ES), which is included in an Annex to the REACH extended safety data sheet. DUs then have certain obligations relating to adopting the control conditions described in the ES. The REACH Technical Guidance Documents lay down the expectations for the process of risk assessment that M/Is should adopt when developing ESs. But with many thousands of chemicals in daily commerce, it is also necessary to ensure that what is communicated to DUs not only meets the requirements of REACH but is also understandable to these groups, as well as being consistent across different chemical suppliers and supply chains. In cooperation with relevant DU groups, the European solvents industry has developed generic approaches for describing how solvents are commonly used, in order that these can subsequently be used as the basis for REACH registrations and related safety data sheet communications on health risk control. The utility of these approaches (termed 'generic exposure scenarios') is acknowledged under REACH and they are now publicly available for use both by M/Is and DUs.     

The ECETOC approach to targeted risk assessment; lessons and experiences relevant to REACH

ECETOC has been developed an approach by which the health and environmental risks arising from the supply and use of chemicals can be quickly and reliably evaluated by chemical suppliers. The approach has been available as a web-based tool since 2004. During the development and implementation of the approach, ECETOC has consulted widely so that the approach is seen to meet the required levels of science while also meeting the differing needs of affected stakeholders. The consultation process has yielded a number of findings in terms of the considerations necessary for implementing successful risk-informed decision-making in a multi-stakeholder environment. Concurrently, as the European Commission's REACH legislative package has begun to take shape, it has also become apparent that the approach has a number of potential applications for aiding the process of risk assessment under REACH. This paper reviews these experiences within the broader context of the expectations that REACH places on chemical manufacturers and suppliers. In particular, it highlights the key role that REACH Exposure Scenarios have for evaluating, managing and communicating chemical risks.     

Aversion to health inequalities and priority setting in health care

Traditionally aversion to health inequality is modelled through a concave utility function over health outcomes. Bleichrodt et al. [Bleichrodt, H., Diecidue E., Quiggin J., 2004. Equity weights in the allocation of health care: the rank-dependent QALY model. Journal of Health Economics 23, 157-171] have suggested a "dual" approach based on the introduction of explicit equity weights. The purpose of this paper is to analyze how priorities in health care are determined in the framework of these two models. It turns out that policy implications are highly sensitive to the choice of the model that will represent aversion to health inequality.     

Economic benefits of using adaptive predictive models of reproductive toxicity in the context of a tiered testing program

A predictive model of reproductive toxicity, as observed in rat multigeneration reproductive (MGR) studies, was previously developed using high throughput screening (HTS) data from 36 in vitro assays mapped to 8 genes or gene-sets from Phase I of USEPA ToxCast research program, the proof-of-concept phase in which 309 toxicologically well characterized chemicals were testing in over 500 HTS assays. The model predicted the effects on male and female reproductive function with a balanced accuracy of 80%. In a theoretical examination of the potential impact of the model, two case studies were derived representing different tiered testing scenarios to: 1) screen-out chemicals with low predicted probability of effect; and 2) screen-in chemicals with a high probability of causing adverse reproductive effects. We define 'testing cost efficiency' as the total cost divided by the number of positive chemicals expected in the definitive guideline toxicity study. This would approach $2.11 M under the current practice. Under case study 1, 22% of the chemicals were screened-out due to low predicted probability of adverse reproductive effect and a misclassification rate of 12%, yielding a test cost efficiency of $1.87 M. Under case study 2, 13% of chemicals were screened-in yielding a testing cost efficiency of $1.13 M per test-positive chemical. Applying the model would also double the total number of positives identified. It should be noted that the intention of the case studies is not to provide a definitive mechanism for screening-in or screening-out chemicals or account for the indirect costs of misclassification. The case studies demonstrate the customizability of the model as a tool in chemical testing decision-making. The predictive model of reproductive toxicity will continue to evolve as new assays become available to fill recognized biological gaps and will be combined with other predictive models, particularly models of developmental toxicity, to form an initial tier to an overarching integrated testing strategy.     

Pseudo-likelihood estimates of the cumulative risk of an autosomal dominant disease from a kin-cohort study

Wacholder et al. [1998: Am J Epidemiol 148:623-629] and Struewing et al. [1997: N Engl J Med 336:1401-1408] have recently proposed a design called the kin-cohort design to estimate the probability of developing disease (penetrance) associated with an autosomal dominant gene. In this design, volunteers (probands) agree to be genotyped and one also determines the disease history (phenotype) of first-degree relatives of the proband. They used this design to estimate that the chance of developing breast cancer by age 70 in Ashkenazi Jewish women who carried mutations of the genes BRCA1 or BRCA2 was 0.56, a figure that was lower than previously estimated from highly affected families. The method that they used to estimate the cumulative risk of breast cancer, while asymptotically correct, does not necessarily produce monotone estimates in small samples. To obtain monotone, weakly parametric estimates, we consider separate piecewise exponential models for carriers and non-carriers. As the number of intervals on which constant hazards are assumed increases, however, the maximum likelihood score equations become unstable and difficult to solve. We, therefore, developed alternative pseudo-likelihood procedures that are readily solvable for piecewise exponential models with many intervals. We study these techniques through simulations and a re-analysis of a portion of the data used by Struewing et al. [1997] and discuss possible extensions.     

Permutation-based adjustments for the significance of partial regression coefficients in microarray data analysis

The aim of this paper is to generalize permutation methods for multiple testing adjustment of significant partial regression coefficients in a linear regression model used for microarray data. Using a permutation method outlined by Anderson and Legendre [1999] and the permutation P-value adjustment from Simon et al. [2004], the significance of disease related gene expression will be determined and adjusted after accounting for the effects of covariates, which are not restricted to be categorical. We apply these methods to a microarray dataset containing confounders and illustrate the comparisons between the permutation-based adjustments and the normal theory adjustments. The application of a linear model is emphasized for data containing confounders and the permutation-based approaches are shown to be better suited for microarray data.     

Statistical performance of cladistic strategies for haplotype grouping in pharmacogenetics

Haplotypes comprising multiple single nucleotide polymorphisms (SNPs) are popular covariates for capturing the key genetic variation present over a region of interest in the DNA sequence. Although haplotypes can provide a clearer assessment of genetic variation in a region than their component SNPs considered individually, the multi-allelic nature of haplotypes increases the complexity of the statistical models intended to discover association with outcomes of interest. Cladistic methods cluster haplotypes according to the estimates of their genealogical closeness and have been proposed recently as strategies for reducing model complexity and increasing power. Two examples are methods based on a haplotype nesting algorithm described by Templeton et al. (Genetics 1987; 117:343-351) and hierarchical clustering of haplotypes as described by Durrant et al. (Am. J. Hum. Genet. 2004; 75:35-43). In the context of assessing the pharmacogenetic effects of candidate genes, for which high-density SNP data have been gathered, we have conducted a simulation-based case study of the testing and estimation properties of two strategies based on Templeton's algorithm (TA), one being that described by Seltman et al. (Am. J. Hum. Genet. 2001; 68:1250-1263; Genet. Epidemiol. 2003; 25:48-58), as well as the method of Durrant et al. using data from a diabetes clinical trial. Even after adjusting for multiplicity, improvements in power can be realized using cladistic approaches with treatment group sizes in the range expected for standard trials, although these gains may be sensitive to the cladistic structure used. Differences in the relative performance of the cladistic approaches examined were observed with the clustering approach of Durrant et al. showing statistical properties superior to the methods based on TA.     

Genetic Analysis Workshop II: pedigree analysis of a binary trait without assuming an underlying liability

A model for concordance in a binary measure that does not rely on the assumption of an underlying latent liability dichotomized about a threshold has been demonstrated for twin pairs [Hannah et al, 1983]. It is extended here to pedigrees of arbitrary structure by making an assumption that is, for small incidence rates, almost equivalent to postulating that relative risks are multiplicative. The model is applied to the workshop data to determine the extent to which the known structure of the simulated models can be recovered.     

Recent progress in understanding the genetic susceptibility to osteoporosis

Family and twin studies have established a genetic contribution to the etiology of osteoporosis. The genes and allelic variants conferring osteoporotic risk are largely undefined, but the number of candidates has increased steadily in recent years (Table I). Osteoporosis is a complex disease, and allelic variation in many other candidate-genes including those that encode growth factors, cytokines, calciotropic hormones, and bone matrix proteins are likely to also play a role and warrant systematic investigation. Most family and association studies to date have focused on the genetic contributions to bone density, a major determinant of bone strength and fracture risk. Bone density is not the only determinant of skeletal fragility, however, and genetic influences on fracture risk are independent of bone density [Cummings et al., 1995]. The microarchitectural properties and overall size and geometry of bone also influence skeletal strength [Bouxsein et al., 1996], and the genetic influences on these phenotypes should be investigated more rigorously. Even fewer studies have assessed the association between candidate-gene variation and the risk of fracture, the most important clinical outcome of osteoporosis. Large-scale molecular epidemiologic studies will be increasingly necessary in the future to quantify the relative, absolute and attributable risks of fracture associated with specific genetic variants. Osteoporosis is a complex, multifactorial disease, and most candidate-gene association studies have had limited statistical power to assess gene-gene and gene-environment interaction. Although gender plays an important role in the development of osteoporosis, genetic studies have almost exclusively focused on women, and have not tested whether gender modifies the association between genetic variation and osteoporotic risk. Therefore, future genetic studies will need to recruit larger samples of individuals including men. Rapid additional progress in our understanding of the molecular basis of osteoporosis can be expected in the near future as ongoing genome-wide linkage [Spotila et al., 1996] and candidate-gene association analyses are completed. Linkage analyses in families at high-risk for rare metabolic bone diseases should also yield important clues to the pathogenesis of osteoporosis. Recent examples are the mapping of loci for both high [Johnson et al., 1997] and low [Gong et al., 1996] bone mass to chromosome 11q and osteopetrosis to chromosome 1p [Van Hul et al., 1997]. Similar ongoing studies in baboons [Rogers and Hixson, 1997] and mice [Beamer et al., 1997] may reveal additional loci whose human homologs contribute to osteoporotic risk. The improved understanding of osteoporosis that will emerge from these genetic studies should lead to better diagnosis of this disease and new treatment and prevention strategies.     

Analysis of multiple SNPs in a candidate gene or region

We consider the analysis of multiple single nucleotide polymorphisms (SNPs) within a gene or region. The simplest analysis of such data is based on a series of single SNP hypothesis tests, followed by correction for multiple testing, but it is intuitively plausible that a joint analysis of the SNPs will have higher power, particularly when the causal locus may not have been observed. However, standard tests, such as a likelihood ratio test based on an unrestricted alternative hypothesis, tend to have large numbers of degrees of freedom and hence low power. This has motivated a number of alternative test statistics. Here we compare several of the competing methods, including the multivariate score test (Hotelling's test) of Chapman et al. ([2003] Hum. Hered. 56:18-31), Fisher's method for combining P-values, the minimum P-value approach, a Fourier-transform-based approach recently suggested by Wang and Elston ([2007] Am. J. Human Genet. 80:353-360) and a Bayesian score statistic proposed for microarray data by Goeman et al. ([2005] J. R. Stat. Soc. B 68:477-493). Some relationships between these methods are pointed out, and simulation results given to show that the minimum P-value and the Goeman et al. ([2005] J. R. Stat. Soc. B 68:477-493) approaches work well over a range of scenarios. The Wang and Elston approach often performs poorly; we explain why, and show how its performance can be substantially improved.     

Brief review of the clinical effectiveness of PREVENAR against otitis media

Pre-licensure trials in Finnish and US infants demonstrated that PREVENAR was associated, respectively, with a 6% (95% CI, -4% to 16%) and an 8.9% (95% CI, 5.8-11.8%) overall reduction in clinical AOM incidence. Long-term follow-up of these cohorts revealed that there was an approximately 10-50% vaccine efficacy against recurrent otitis media or for the prevention of tympanostomy tube placement. In surveillance reports from the USA that followed infants with serious AOM, generalized PREVENAR vaccination led to an important fall in the incidence of pneumococcal otitis media, particularly for cases that would have been frequent or would have been refractory to antibiotic treatment. The rate of pneumococcal MEF isolates fell by 39% for severe otitis media [McEllistrem MC, Adams JM, Patel K, Mendelsohn AB, Kaplan SL, Bradley JS, et al. Acute otitis media due to penicillin-nonsusceptible Streptococcus pneumoniae before and after the introduction of the pneumococcal conjugate vaccine. Clin Infect Dis 2005;40(12):1738-44], by 42%, among persistent or treatment-resistant otitis media [Casey JR, Pichichero ME, Changes in frequency and pathogens causing acute otitis media in 1995-2003. Pediatr Infect Dis J 2004;23(9):824-8 [see comment]] and by 66% among severe otitis media cases or from 'otitis-prone' children [Block SL, Hedrick J, Harrison CJ, Tyler R, Smith A, Findlay R, et al. Community-wide vaccination with the heptavalent pneumococcal conjugate significantly alters the microbiology of acute otitis media. Pediatr Infect Dis J 2004;23(9):829-33 [see comment]].     

Frequency of intake and energy value of breakfast for students from selected primary schools in Warsaw

Energy value and frequency breakfast intake in Warsaw primary schools were estimated in a group of 330 children aged 7-15 years. The research was carried out in autumn 1998 year. The nutrition mode was assessed by questionnaire interviews and of 24-hour recall [4] and computer programme "Zywienie". The size of the consumed portion was determined with an album containing colour photographs of products and dishes of different size [14]. Food consumption quality was estimated using test of Bielińska modified by Kulesza et al. [8]. Frequency breakfast intake decreased at older schoolchildren. Breakfast milk and products, vegetables and fruits intake was too low; intake of fat sweets and beverages like "coca-cola" was too high. Breakfast energy value was too low compared with recommended dietary allowances.     

Linkage analysis in alcohol dependence

Alcohol dependence often is a familial disorder and has a genetic component. Research in causative factors of alcoholism is coordinated by a multi-center program, COGA [The Collaborative Study on the Genetics of Alcoholism, Begleiter et al., 1995]. We analyzed a subset of the COGA family sample, 84 pedigrees of Caucasian ancestry comprising 745 persons, 339 of whom are affected according to DSM-III-R and Feighner criteria. Using parametric and nonparametric methods, evidence for linkage was found on chromosome 1 (near markers D1S532, D1S1588, and D1S534), as well as on chromosome 15 (near marker D15S642). Other regions of the genome showed suggestive evidence for contributing loci. Related findings are discussed in recent publications investigating linkage in humans [Reich et al., 1998] and mice [Melo et al., 1996].