Ensuring confidence in predictions: A scheme to assess the scientific validity of in silico models

The use of in silico tools within the drug development process to predict a wide range of properties including absorption, distribution, metabolism, elimination and toxicity has become increasingly important due to changes in legislation and both ethical and economic drivers to reduce animal testing. Whilst in silico tools have been used for decades there remains reluctance to accept predictions based on these methods particularly in regulatory settings. This apprehension arises in part due to lack of confidence in the reliability, robustness and applicability of the models. To address this issue we propose a scheme for the verification of in silico models that enables end users and modellers to assess the scientific validity of models in accordance with the principles of good computer modelling practice. We report here the implementation of the scheme within the Innovative Medicines Initiative project “eTOX” (electronic toxicity) and its application to the in silico models developed within the frame of this project

Hurdles and signposts on the road to virtual control groups—A case study illustrating the influence of anesthesia protocols on electrolyte levels in rats

Introduction: Virtual Control Groups (VCGs) represent the concept of using historical control data from legacy animal studies to replace concurrent control group (CCG) animals. Based on the data curation and sharing activities of the Innovative Medicine Initiatives project eTRANSAFE (enhancing TRANSlational SAFEty Assessment through Integrative Knowledge Management) the ViCoG working group was established with the objectives of i) collecting suitable historical control data sets from preclinical toxicity studies, ii) evaluating statistical methodologies for building adequate and regulatory acceptable VCGs from historical control data, and iii) sharing those control-group data across multiple pharmaceutical companies. During the qualification process of VCGs a particular focus was put on the identification of hidden confounders in the data sets, which might impair the adequate matching of VCGs with the CCG.Methods: During our analyses we identified such a hidden confounder, namely, the choice of the anesthetic procedure used in animal experiments before blood withdrawal. Anesthesia using CO2 may elevate the levels of some electrolytes such as calcium in blood, while the use of isoflurane is known to lower these values. Identification of such hidden confounders is particularly important if the underlying experimental information (e.g., on the anesthetic procedure) is not routinely recorded in the standard raw data files, such as SEND (Standard for Exchange of Non-clinical Data). We therefore analyzed how the replacement of CCGs with VCGs would affect the reproducibility of treatment-related findings regarding electrolyte values (potassium, calcium, sodium, and phosphate). The analyses were performed using a legacy rat systemic toxicity study consisting of a control and three treatment groups conducted according to pertinent OECD guidelines. In the report of this study treatment-related hypercalcemia was reported. The rats in this study were anesthetized with isoflurane.Results: Replacing the CCGs with VCGs derived from studies comprising both anesthetics resulted in a shift of control electrolyte parameters. Instead of the originally reported hypercalcemia the use of VCG led to fallacious conclusions of no observed effect or hypocalcemia.Discussion: Our study highlights the importance of a rigorous statistical analysis including the detection and elimination of hidden confounders prior to the implementation of the VCG concept

Small Interfering RNA Efficiently Suppresses Adhesion Molecule Expression on Pulmonary Microvascular Endothelium

Background. Adhesion molecules are known to influence postoperative organ function, they are hardly involved in the inflammatory response following the ischemia-reperfusion injury. We sought to investigate the potency of small interfering RNAs to suppress adhesion molecule expression in human pulmonary microvascular endothelial cells. Methods. Human lung microvascular endothelial cells were transfected with specific siRNA followed by a stimulation of the cells with an inflammatory cytokine. Adhesion molecule expression was determined by FACS-analysis, and reduction of intracellular mRNA was determined by qRT-PCR. Furthermore, the attachment of isolated neutrophils on the endothelial layer was determined after siRNA transfection. Results. In summary, siRNA transfection significantly decreased the percentage positive cells in a single cocktail transfection of each adhesion molecule investigated. Adhering neutrophils were diminished as well. Conclusion. siRNA might be a promising tool for the effective suppression of adhesion molecule expression on pulmonary microvascular cells, potentially minimizing leukocyte-endothelial depending interactions of a pulmonary allograft

Inroads to Predict in Vivo Toxicology—An Introduction to the eTOX Project

There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison (“read-across”), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX (“electronic toxicity”) consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of in silico prediction systems for organ and in vivo toxicity. The backbone of the project will be a database consisting of preclinical toxicity data for drug compounds or candidates extracted from previously unpublished, legacy reports from thirteen European and European operation-based pharmaceutical companies. The database will be enhanced by incorporation of publically available, high quality toxicology data. Seven academic institutes and five small-to-medium size enterprises (SMEs) contribute with their expertise in data gathering, database curation, data mining, chemoinformatics and predictive systems development. The outcome of the project will be a predictive system contributing to early potential hazard identification and risk assessment during the drug development process. The concept and strategy of the eTOX project is described here, together with current achievements and future deliverables

New ideas for non-animal approaches to predict repeated-dose systemic toxicity: Report from an EPAA Blue Sky Workshop

© 2020 The Authors The European Partnership for Alternative Approaches to Animal Testing (EPAA) convened a ‘Blue Sky Workshop’ on new ideas for non-animal approaches to predict repeated-dose systemic toxicity. The aim of the Workshop was to formulate strategic ideas to improve and increase the applicability, implementation and acceptance of modern non-animal methods to determine systemic toxicity. The Workshop concluded that good progress is being made to assess repeated dose toxicity without animals taking advantage of existing knowledge in toxicology, thresholds of toxicological concern, adverse outcome pathways and read-across workflows. These approaches can be supported by New Approach Methodologies (NAMs) utilising modern molecular technologies and computational methods. Recommendations from the Workshop were based around the needs for better chemical safety assessment: how to strengthen the evidence base for decision making; to develop, standardise and harmonise NAMs for human toxicity; and the improvement in the applicability and acceptance of novel techniques. “Disruptive thinking” is required to reconsider chemical legislation, validation of NAMs and the opportunities to move away from reliance on animal tests. Case study practices and data sharing, ensuring reproducibility of NAMs, were viewed as crucial to the improvement of non-animal test approaches for systemic toxicity.U.S.Environmental Protection Agency (EPA); Agency for Science, Technology and Research ( A*STAR), Singapor

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity

GATA2 Mediates Thyrotropin-Releasing Hormone-Induced Transcriptional Activation of the Thyrotropin β Gene

Thyrotropin-releasing hormone (TRH) activates not only the secretion of thyrotropin (TSH) but also the transcription of TSHβ and α-glycoprotein (αGSU) subunit genes. TSHβ expression is maintained by two transcription factors, Pit1 and GATA2, and is negatively regulated by thyroid hormone (T3). Our prior studies suggest that the main activator of the TSHβ gene is GATA2, not Pit1 or unliganded T3 receptor (TR). In previous studies on the mechanism of TRH-induced activation of the TSHβ gene, the involvements of Pit1 and TR have been investigated, but the role of GATA2 has not been clarified. Using kidney-derived CV1 cells and pituitary-derived GH3 and TαT1 cells, we demonstrate here that TRH signaling enhances GATA2-dependent activation of the TSHβ promoter and that TRH-induced activity is abolished by amino acid substitution in the GATA2-Zn finger domain or mutation of GATA-responsive element in the TSHβ gene. In CV1 cells transfected with TRH receptor expression plasmid, GATA2-dependent transactivation of αGSU and endothelin-1 promoters was enhanced by TRH. In the gel shift assay, TRH signal potentiated the DNA-binding capacity of GATA2. While inhibition by T3 is dominant over TRH-induced activation, unliganded TR or the putative negative T3-responsive element are not required for TRH-induced stimulation. Studies using GH3 cells showed that TRH-induced activity of the TSHβ promoter depends on protein kinase C but not the mitogen-activated protein kinase, suggesting that the signaling pathway is different from that in the prolactin gene. These results indicate that GATA2 is the principal mediator of the TRH signaling pathway in TSHβ expression

Biology-inspired microphysiological systems to advance patient benefit and animal welfare in drug development

The first microfluidic microphysiological systems (MPS) entered the academic scene more than 15 years ago and were considered an enabling technology to human (patho)biology in vitro and, therefore, provide alternative approaches to laboratory animals in pharmaceutical drug development and academic research. Nowadays, the field generates more than a thousand scientific publications per year. Despite the MPS hype in academia and by platform providers, which says this technology is about to reshape the entire in vitro culture landscape in basic and applied research, MPS approaches have neither been widely adopted by the pharmaceutical industry yet nor reached regulated drug authorization processes at all. Here, 46 leading experts from all stakeholders - academia, MPS supplier industry, pharmaceutical and consumer products industries, and leading regulatory agencies - worldwide have analyzed existing challenges and hurdles along the MPS-based assay life cycle in a second workshop of this kind in June 2019. They identified that the level of qualification of MPS-based assays for a given context of use and a communication gap between stakeholders are the major challenges for industrial adoption by end-users. Finally, a regulatory acceptance dilemma exists against that background. This t4 report elaborates on these findings in detail and summarizes solutions how to overcome the roadblocks. It provides recommendations and a roadmap towards regulatory accepted MPS-based models and assays for patients' benefit and further laboratory animal reduction in drug development. Finally, experts highlighted the potential of MPS-based human disease models to feedback into laboratory animal replacement in basic life science research.Toxicolog