Wiebke Albrecht

Bio: Wiebke Albrecht is an academic researcher from Technical University of Dortmund. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 5, co-authored 19 publications receiving 155 citations. Previous affiliations of Wiebke Albrecht include Leibniz Institute for Neurobiology.

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

Abstract: 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.

Relevance of the incubation period in cytotoxicity testing with primary human hepatocytes.

Abstract: Primary human hepatocytes (PHHs) remain the gold standard for in vitro testing in the field of pharmacology and toxicology. One crucial parameter influencing the results of in vitro tests is the incubation period with test compounds. It has been suggested that longer incubation periods may be critical for the prediction of repeated dose toxicity. However, a study that systematically analyzes the relationship between incubation period and cytotoxicity in PHHs is not available. To close this gap, 30 compounds were tested in a concentration-dependent manner for cytotoxicity in cultivated cryopreserved PHHs (three donors per compound) for 1, 2 and 7 days. The median of the EC50 values of all compounds decreased 1.78-fold on day 2 compared to day 1, and 1.89-fold on day 7 compared to day 1. Median values of EC50 ratios of all compounds at day 2 and day 7 were close to one but for individual compounds the ratio increased up to almost six. Strong correlations were obtained for EC50 on day 1 and day 7 (R = 0.985; 95% CI 0.960–0.994), day 1 and day 2 (R = 0.964; 95% CI 0.910–0.986), as well as day 2 and day 7 (R = 0.981; 95% CI 0.955–0.992). However, compound specific differences also occurred. Whereas, for example, busulfan showed a relatively strong increase on day 7 compared to day 1, cytotoxicity of acetaminophen did not increase during longer incubation periods. To validate the observed correlations, a publicly available data set, containing data on the cytotoxicity of human hepatocytes cultivated as spheroids for incubation periods of 5 and 14 days, was analyzed. A high correlation coefficient of EC50 values at day 5 and day 14 was obtained (R = 0.894; 95% CI 0.798–0.945). In conclusion, the median cytotoxicity of the test compounds increased between 1 and 2 days of incubation, with no or only a minimal further increase until day 7. It remains to be studied whether the different results obtained for some individual compounds after longer exposure periods would correspond better to human-repeated dose toxicity.

Comparing in vitro human liver models to in vivo human liver using RNA-Seq

Abstract: The liver plays an important role in xenobiotic metabolism and represents a primary target for toxic substances. Many different in vitro cell models have been developed in the past decades. In this study, we used RNA-sequencing (RNA-Seq) to analyze the following human in vitro liver cell models in comparison to human liver tissue: cancer-derived cell lines (HepG2, HepaRG 3D), induced pluripotent stem cell-derived hepatocyte-like cells (iPSC-HLCs), cancerous human liver-derived assays (hPCLiS, human precision cut liver slices), non-cancerous human liver-derived assays (PHH, primary human hepatocytes) and 3D liver microtissues. First, using CellNet, we analyzed whether these liver in vitro cell models were indeed classified as liver, based on their baseline expression profile and gene regulatory networks (GRN). More comprehensive analyses using non-differentially expressed genes (non-DEGs) and differential transcript usage (DTU) were applied to assess the coverage for important liver pathways. Through different analyses, we noticed that 3D liver microtissues exhibited a high similarity with in vivo liver, in terms of CellNet (C/T score: 0.98), non-DEGs (10,363) and pathway coverage (highest for 19 out of 20 liver specific pathways shown) at the beginning of the incubation period (0 h) followed by a decrease during long-term incubation for 168 and 336 h. PHH also showed a high degree of similarity with human liver tissue and allowed stable conditions for a short-term cultivation period of 24 h. Using the same metrics, HepG2 cells illustrated the lowest similarity (C/T: 0.51, non-DEGs: 5623, and pathways coverage: least for 7 out of 20) with human liver tissue. The HepG2 are widely used in hepatotoxicity studies, however, due to their lower similarity, they should be used with caution. HepaRG models, iPSC-HLCs, and hPCLiS ranged clearly behind microtissues and PHH but showed higher similarity to human liver tissue than HepG2 cells. In conclusion, this study offers a resource of RNA-Seq data of several biological replicates of human liver cell models in vitro compared to human liver tissue.

The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods.

Abstract: Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories A unified strategy for such collaborative testing is presented It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (eg rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol) Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans Moreover, data generation was exemplified by providing results from 25 reporter assays A complete evaluation of the entire test battery will be described elsewhere A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity

A guide to the organ-on-a-chip

Abstract: Organs-on-chips (OoCs) are systems containing engineered or natural miniature tissues grown inside microfluidic chips. To better mimic human physiology, the chips are designed to control cell microenvironments and maintain tissue-specific functions. Combining advances in tissue engineering and microfabrication, OoCs have gained interest as a next-generation experimental platform to investigate human pathophysiology and the effect of therapeutics in the body. There are as many examples of OoCs as there are applications, making it difficult for new researchers to understand what makes one OoC more suited to an application than another. This Primer is intended to give an introduction to the aspects of OoC that need to be considered when developing an application-specific OoC. The Primer covers guiding principles and considerations to design, fabricate and operate an OoC, as well as subsequent assaying techniques to extract biological information from OoC devices. Alongside this is a discussion of current and future applications of OoC technology, to inform design and operational decisions during the implementation of OoC systems. Organs-on-chips are microfluidic systems containing miniature tissues with the aim of mimicking human physiology for a range of biomedical and therapeutic applications. Leung, de Haan et al. report practical tips to inform design and operational decisions during the implementation of organ-on-a-chip systems.

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

Abstract: 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.

Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer.

Abstract: Activated choline metabolism is a hallmark of carcinogenesis and tumor progression, which leads to elevated levels of phosphocholine and glycerophosphocholine in all types of cancer tested so far. Magnetic resonance spectroscopy applications have played a key role in detecting these elevated choline phospholipid metabolites. To date, the majority of cancer-related studies have focused on phosphocholine and the Kennedy pathway, which constitutes the biosynthesis pathway for membrane phosphatidylcholine. Fewer and more recent studies have reported on the importance of glycerophosphocholine in cancer. In this review article, we summarize the recent literature on glycerophosphocholine metabolism with respect to its cancer biology and its detection by magnetic resonance spectroscopy applications.