Development of an in vitro test battery for a test system to predict human drug-induced liver injury

Drug-induced liver injury (DILI) is a major concern due to its poor predictability. Recently, we have developed an in vitro/in silico test system for the prediction of human DILI in relation to oral doses and blood concentrations. Additionally, two indices, the toxicity separation index (TSI) and the toxicity estimation index (TEI) were introduced for the quantitative evaluation of a test system and its input parameters. In this PhD-thesis, I studied whether extending the in vitro test battery of the test system, so far consisting of a cytotoxicity test in primary human hepatocytes, by additional functional readouts would lead to improved performance and thus allow a more accurate prediction. In total, three different approaches that address putative DILI-relevant mechanisms were explored. In the first approach, the influence of a bile acid mix on the cytotoxicity of in total 18 compounds in cultivated primary human hepatocytes was investigated. In summary, increased and decreased susceptibility to both hepatotoxic and non-hepatotoxic substances was observed with the addition of bile acids, which did not improve the TSI (0.79 -> 0.77) nor the TEI (0.73 -> 0.69) compared to cytotoxicity without additional bile acids. In the second approach, an assay was developed and evaluated that measures the inhibition of bile acid export carriers in primary human hepatocytes. In total 36 compounds were tested with the transport inhibtion assay and the cytotoxicity assay. In conclusion, the assay is able to detect bile acid export carrier inhibition and integration into the in vitro test battery improved TSI (0.77 -> 0.89) and TEI (0.69 -> 0.83) compared to cytotoxicity. In a third approach, intracellular lipid accumulation in HepG2 cells was investigated for a total of 60 compounds. Addition of lipid droplet accumulation to cytotoxicity improved TSI (0.74 -> 0.80) and TEI (0.67 -> 0.81). In summary, three assays were developed for the in vitro test battery of a test system to predict drug-induced liver injury. Quantitative analysis revealed that two of the three assays lead to improved separation of hepatotoxic and non-hepatotoxic compounds, as well as improved estimation of in vivo relevant blood concentrations. These improvements allow more accurate prediction of DILI by the test system

Handling deviating control values in concentration-response curves

In cell biology, pharmacology and toxicology dose-response and concentration-response curves are frequently fitted to data with statistical methods. Such fits are used to derive quantitative measures (e.g. EC20 values) describing the relationship between the concentration of a compound or the strength of an intervention applied to cells and its effect on viability or function of these cells. Often, a reference, called negative control (or solvent control), is used to normalize the data. The negative control data sometimes deviate from the values measured for low (ineffective) test compound concentrations. In such cases, normalization of the data with respect to control values leads to biased estimates of the parameters of the concentration-response curve. Low quality estimates of effective concentrations can be the consequence. In a literature study, we found that this problem occurs in a large percentage of toxicological publications. We propose different strategies to tackle the problem, including complete omission of the controls. Data from a controlled simulation study indicate the best-suited problem solution for different data structure scenarios. This was further exemplified by a real concentration-response study. We provide the following recommendations how to handle deviating controls: (1) The log-logistic 4pLL model is a good default option. (2) When there are at least two concentrations in the no-effect range, low variances of the replicate measurements, and deviating controls, control values should be omitted before fitting the model. (3) When data are missing in the no-effect range, the Brain-Cousens model sometimes leads to better results than the default model

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

Interruption of bile acid uptake by hepatocytes after acetaminophen overdose ameliorates hepatotoxicity.

Background & aimsAcetaminophen (APAP) overdose remains a frequent cause of acute liver failure, which is generally accompanied by increased levels of serum bile acids (BAs). However, the pathophysiological role of BAs remains elusive. Herein, we investigated the role of BAs in APAP-induced hepatotoxicity.MethodsWe performed intravital imaging to investigate BA transport in mice, quantified endogenous BA concentrations in the serum of mice and patients with APAP overdose, analyzed liver tissue and bile by mass spectrometry and MALDI-mass spectrometry imaging, assessed the integrity of the blood-bile barrier and the role of oxidative stress by immunostaining of tight junction proteins and intravital imaging of fluorescent markers, identified the intracellular cytotoxic concentrations of BAs, and performed interventions to block BA uptake from blood into hepatocytes.ResultsPrior to the onset of cell death, APAP overdose causes massive oxidative stress in the pericentral lobular zone, which coincided with a breach of the blood-bile barrier. Consequently, BAs leak from the bile canaliculi into the sinusoidal blood, which is then followed by their uptake into hepatocytes via the basolateral membrane, their secretion into canaliculi and repeated cycling. This, what we termed 'futile cycling' of BAs, led to increased intracellular BA concentrations that were high enough to cause hepatocyte death. Importantly, however, the interruption of BA re-uptake by pharmacological NTCP blockage using Myrcludex B and Oatp knockout strongly reduced APAP-induced hepatotoxicity.ConclusionsAPAP overdose induces a breach of the blood-bile barrier which leads to futile BA cycling that causes hepatocyte death. Prevention of BA cycling may represent a therapeutic option after APAP intoxication.Lay summaryOnly one drug, N-acetylcysteine, is approved for the treatment of acetaminophen overdose and it is only effective when given within ∼8 hours after ingestion. We identified a mechanism by which acetaminophen overdose causes an increase in bile acid concentrations (to above toxic thresholds) in hepatocytes. Blocking this mechanism prevented acetaminophen-induced hepatotoxicity in mice and evidence from patients suggests that this therapy may be effective for longer periods after ingestion compared to N-acetylcysteine

Roadmap for the development of alternative test methods

Pyrrolizidine alkaloids (PA) exert their toxic effects only after bioactivation. Although their toxicity has already been studied and metabolic pathways including important metabolites were described, the quantification of the latter revealed a large unknown portion of the metabolized PA. In this study, the qualitative and quantitative metabolite profiles of structurally different PAs in rat and human liver microsomes were investigated. Between five metabolites for europine and up to 48 metabolites for lasiocarpine were detected. Proposals for the chemical structure of each metabolite were derived based on fragmentation patterns using high-resolution mass spectrometry. The metabolite profiles of the diester PAs showed a relatively good agreement between both species. The metabolic reactions were summarized into three groups: dehydrogenation, oxygenation, and shortening of necic acid(s). While dehydrogenation of the necine base is considered as bioactivation, both other routes are considered as detoxification steps. The most abundant changes found for open chained diesters were dealkylations, while the major metabolic pathway for cyclic diesters was oxygenation especially at the nitrogen atom. In addition, all diester PAs formed several dehydrogenation products, via the insertion of a second double bond in the necine base, including the formation of glutathione conjugates. In rat liver microsomes, all investigated PAs formed dehydropyrrolizidine metabolites with the highest amount formed by lasiocarpine, whereas in human liver microsomes, these metabolites could only be detected for diesters. Our findings demonstrate that an extensive analysis of PA metabolism can provide the basis for a better understanding of PA toxicity and support future risk assessment

Role of autophagy in drug induced liver injury

Pyrrolizidine alkaloids (PA) exert their toxic effects only after bioactivation. Although their toxicity has already been studied and metabolic pathways including important metabolites were described, the quantification of the latter revealed a large unknown portion of the metabolized PA. In this study, the qualitative and quantitative metabolite profiles of structurally different PAs in rat and human liver microsomes were investigated. Between five metabolites for europine and up to 48 metabolites for lasiocarpine were detected. Proposals for the chemical structure of each metabolite were derived based on fragmentation patterns using high-resolution mass spectrometry. The metabolite profiles of the diester PAs showed a relatively good agreement between both species. The metabolic reactions were summarized into three groups: dehydrogenation, oxygenation, and shortening of necic acid(s). While dehydrogenation of the necine base is considered as bioactivation, both other routes are considered as detoxification steps. The most abundant changes found for open chained diesters were dealkylations, while the major metabolic pathway for cyclic diesters was oxygenation especially at the nitrogen atom. In addition, all diester PAs formed several dehydrogenation products, via the insertion of a second double bond in the necine base, including the formation of glutathione conjugates. In rat liver microsomes, all investigated PAs formed dehydropyrrolizidine metabolites with the highest amount formed by lasiocarpine, whereas in human liver microsomes, these metabolites could only be detected for diesters. Our findings demonstrate that an extensive analysis of PA metabolism can provide the basis for a better understanding of PA toxicity and support future risk assessment

Handling deviating control values in concentration-response curves

In cell biology, pharmacology and toxicology dose-response and concentration-response curves are frequently fitted to data with statistical methods. Such fits are used to derive quantitative measures (e.g. EC[Formula: see text] values) describing the relationship between the concentration of a compound or the strength of an intervention applied to cells and its effect on viability or function of these cells. Often, a reference, called negative control (or solvent control), is used to normalize the data. The negative control data sometimes deviate from the values measured for low (ineffective) test compound concentrations. In such cases, normalization of the data with respect to control values leads to biased estimates of the parameters of the concentration-response curve. Low quality estimates of effective concentrations can be the consequence. In a literature study, we found that this problem occurs in a large percentage of toxicological publications. We propose different strategies to tackle the problem, including complete omission of the controls. Data from a controlled simulation study indicate the best-suited problem solution for different data structure scenarios. This was further exemplified by a real concentration-response study. We provide the following recommendations how to handle deviating controls: (1) The log-logistic 4pLL model is a good default option. (2) When there are at least two concentrations in the no-effect range, low variances of the replicate measurements, and deviating controls, control values should be omitted before fitting the model. (3) When data are missing in the no-effect range, the Brain-Cousens model sometimes leads to better results than the default model.publishe

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.publishe

The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds

An in vitro/in silico method that determines the risk of human drug induced liver injury in relation to oral doses and blood concentrations of drugs was recently introduced. This method utilizes information on the maximal blood concentration (Cmax) for a specific dose of a test compound, which can be estimated using physiologically-based pharmacokinetic modelling, and a cytotoxicity test in cultured human hepatocytes. In the present study, we analyzed if the addition of an assay that measures the inhibition of bile acid export carriers, like BSEP and/or MRP2, to the existing method improves the differentiation of hepatotoxic and non-hepatotoxic compounds. Therefore, an export assay for 5-chloromethylfluorescein diacetate (CMFDA) was established. We tested 36 compounds in a concentration-dependent manner for which the risk of hepatotoxicity for specific oral doses and the capacity to inhibit hepatocyte export carriers are known. Compared to the CTB cytotoxicity test, substantially lower EC10 values were obtained using the CMFDA assay for several known BSEP and/or MRP2 inhibitors. To quantify if the addition of the CMFDA assay to our test system improves the overall separation of hepatotoxic from non-hepatotoxic compounds, the toxicity separation index (TSI) was calculated. We obtained a better TSI using the lower alert concentration from either the CMFDA or the CTB test (TSI: 0.886) compared to considering the CTB test alone (TSI: 0.775). In conclusion, the data show that integration of the CMFDA assay with an in vitro test battery improves the differentiation of hepatotoxic and non-hepatotoxic compounds in a set of compounds that includes bile acid export carrier inhibitors.publishe