Summary The recent advent of microphysiological systems – microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro – is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-five experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale.

Abstract-Although it is well known that estrogenic steroidal hormones are able to affect the sexual development and reproduction of fish at low concentrations, no data on environmental effects of the class of progestogenic hormones are available yet. Synthetic gestagens (progestins) are a component in oral contraceptives. Upon their use, a fraction of the progestins will be excreted via urine into the aquatic environment. On the basis of their pharmacological action in mammals, it is supposed that fish reproduction is the most sensitive endpoint for the progestin treatment. In order to test this assumption, the effects of two progestins currently marketed in contraceptive formulations, levonorgestrel (LNG) and drospirenone (DRSP), were investigated in adult fathead minnows (Pimephales promelas) following an Organization for Economic Cooperation and Development 21-d fish reproduction screening assay draft protocol with additional end points. Levonorgestrel was tested at measured concentrations of 0.8, 3.3, and 29.6 ng/L, and DRSP at concentrations of 0.66, 6.5, and 70 mg/L. Both tested progestins caused an inhibition of reproduction. For LNG, this occurred at concentrations of $0.8 ng/L, no no-observed-effect concentration (NOEC) could be defined. Higher concentrations resulted in masculinization of females with de novo synthesis of nuptial tubercles. Drospirenone treatment, however, affected the reproductive success of fathead minnow at concentrations of 6.5 mg/L and higher with a clear dose-response relationship and a NOEC of 0.66 mg/L, which is above environmentally relevant concentrations.

purpose. The application of fluid flow (dynamic) for the physiological nutrition of the tissues and the creation of microenvironmental biomolecular gradients and relevant mechanical cues (e.g., shear stress) is a major aspect of these systems, differentiating them from conventional (static) cell and tissue cultures. This review uses the term MPS exclusively for microfluidic sys- Introduction Definitions and terminologyMicrophysiological systems (MPS) are microfluidic devices capable of emulating human (or any other animal species') biology in vitro at the smallest biologically acceptable scale, defined by t 4 Workshop Report*

Up to now, publicly available data sets to build and evaluate Ames mutagenicity prediction tools have been very limited in terms of size and chemical space covered. In this report we describe a new unique public Ames mutagenicity data set comprising about 6500 nonconfidential compounds (available as SMILES strings and SDF) together with their biological activity. Three commercial tools (DEREK, MultiCASE, and an off-the-shelf Bayesian machine learner in Pipeline Pilot) are compared with four noncommercial machine learning implementations (Support Vector Machines, Random Forests, k-Nearest Neighbors, and Gaussian Processes) on the new benchmark data set.

In silico prediction tools for Ames mutagenicity (Salmonella typhimurium reverse mutation assay) represent a costeffective high throughput approach for the prioritization of compounds before submission to experimental testing. Various modeling approaches have been pursued in this field during the last few years. However, the publicly available data sets used for modeling are mostly very limited in terms of size and chemical coverage. Hence, a reasonable comparison of the different modeling methodologies is so far -as for most QSAR problems -impossible.In this work we describe a collection of about 6000 nonconfidential compounds together with their biological activity in the Ames mutagenicity test. This very large, unique and valuable data set built from public sources is made available in machine-readable form (smiles strings) to be used as a benchmark by other researchers. Based on these data we built three statistical prediction models for Ames mutagenicity based on CORINA and DRAGON descriptors. The methods used are a support vector machine, a random forest and Gaussian processes. All three approaches are evaluated within the same cross-validation setting. To facilitate this valuable benchmark, the exact validation protocol including the exact random splits will be made publicly available. The results show that all three methods yield satisfactory results, reaching sensitivity and specificity values of greater than 70% or 80%, respectively. The application of Gaussian processes, previously not applied to Ames mutagenicity prediction proves slightly superior to the other two methods.

Although lack of efficacy is an important cause of late stage attrition in drug development the shortcomings in the translation of toxicities observed during the preclinical development to observations in clinical trials or post-approval is an ongoing topic of research. The concordance between preclinical and clinical safety observations has been analyzed only on relatively small data sets, mostly over short time periods of drug approvals. We therefore explored the feasibility of a big-data analysis on a set of 3,290 approved drugs and formulations for which 1,637,449 adverse events were reported for both humans animal species in regulatory submissions over a period of more than 70 years. The events reported in five species - rat, dog, mouse, rabbit, and cynomolgus monkey - were treated as diagnostic tests for human events and the diagnostic power was computed for each event/species pair using likelihood ratios. The animal-human translation of many key observations is confirmed as being predictive, such as QT prolongation and arrhythmias in dog. Our study confirmed the general predictivity of animal safety observations for humans, but also identified issues of such automated analyses which are on the one hand related to data curation and controlled vocabularies, on the other hand to methodological changes over the course of time.

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Nephrogenic systemic fibrosis (NSF) is a potentially severe systemic disease typically characterized by fibrosis of the skin and connective tissues. The etiology of NSF is still unknown but is likely to be multifactorial. Specific triggers under scientific evaluation have included surgery and/or the occurrence of thrombosis or other vascular injury, proinflammatory state, the administration of high doses of erythropoietin, and more recently the use of gadolinium-based contrast agents (GBCAs). The aim of this review is to summarize knowledge regarding the pathogenesis of NSF and the potential role of GBCAs in its pathology, with a focus on animal experiments. The potential role of complex stability of GCBAs will be highlighted by results from several in vitro and in vivo experiments in rodent models of NSF.