scholarly journals Interactions of anti-COVID-19 drug candidates with hepatic transporters may cause liver toxicity and affect pharmacokinetics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Csilla Ambrus ◽  
Éva Bakos ◽  
Balázs Sarkadi ◽  
Csilla Özvegy-Laczka ◽  
Ágnes Telbisz
Keyword(s):  
Liver Toxicity ◽  
Basolateral Membrane ◽  
Venous Blood ◽  
Viral Disease ◽  
Blood Stream ◽  
Drug Induced ◽  
Drug Candidates ◽  
General Drug ◽  
Canalicular Transporters

AbstractTransporters in the human liver play a major role in the clearance of endo- and xenobiotics. Apical (canalicular) transporters extrude compounds to the bile, while basolateral hepatocyte transporters promote the uptake of, or expel, various compounds from/into the venous blood stream. In the present work we have examined the in vitro interactions of some key repurposed drugs advocated to treat COVID-19 (lopinavir, ritonavir, ivermectin, remdesivir and favipiravir), with the key drug transporters of hepatocytes. These transporters included ABCB11/BSEP, ABCC2/MRP2, and SLC47A1/MATE1 in the canalicular membrane, as well as ABCC3/MRP3, ABCC4/MRP4, SLC22A1/OCT1, SLCO1B1/OATP1B1, SLCO1B3/OATP1B3, and SLC10A1/NTCP, residing in the basolateral membrane. Lopinavir and ritonavir in low micromolar concentrations inhibited BSEP and MATE1 exporters, as well as OATP1B1/1B3 uptake transporters. Ritonavir had a similar inhibitory pattern, also inhibiting OCT1. Remdesivir strongly inhibited MRP4, OATP1B1/1B3, MATE1 and OCT1. Favipiravir had no significant effect on any of these transporters. Since both general drug metabolism and drug-induced liver toxicity are strongly dependent on the functioning of these transporters, the various interactions reported here may have important clinical relevance in the drug treatment of this viral disease and the existing co-morbidities.

scholarly journals Interactions of Anti-COVID-19 Drug Candidates With Hepatic Transporters May Cause Liver Toxicity and Affect Drug Metabolism

2021 ◽  
Author(s):  
Csilla Ambrus ◽  
Éva Bakos ◽  
Balázs Sarkadi ◽  
Csilla Özvegy-Laczka ◽  
Ágnes Telbisz
Keyword(s):  
Drug Metabolism ◽  
Liver Toxicity ◽  
Basolateral Membrane ◽  
Venous Blood ◽  
Viral Disease ◽  
Blood Stream ◽  
Drug Induced ◽  
Drug Candidates ◽  
Canalicular Transporters

Abstract Transporters in the human liver play a major role in the metabolism of endo-and xenobiotics. Apical (canalicular) transporters extrude compounds to the bile, while basolateral hepatocyte transporters promote the uptake or expel various compounds into the venous blood stream. In the present work we have examined the in vitro interactions of some key repurposed drugs advocated to treat COVID-19 (lopinavir, ritonavir, ivermectin, remdesivir and favipiravir), with the relevant key transporters in the hepatocytes. These transporters included the ABCB11/BSEP, ABCC2/MRP2, and MATE1 in the canalicular membrane, as well as ABCC3/MRP3, ABCC4/MRP4, OCT1, OATP1B1, OATP1B3, and NTCP, residing in the basolateral membrane. Lopinavir and ritonavir in low micromolar concentrations inhibited the ABCB11/BSEP and MATE1 exporters, as well as the OATP1B1/1B3 uptake transporters. Ritonavir had a similar inhibitory pattern, also inhibiting OCT1. Remdesivir strongly inhibited ABCC4/MRP4, OATP1B1/1B3, MATE1 and OCT1. Thus, these agents may cause severe drug-drug interactions and drug-induced liver injury. Favipiravir had no significant effect on any of these transporters. Since both general drug metabolism and drug-induced liver toxicity are strongly dependent on the functioning of these transporters, the variable interactions reported here may have important clinical relevance in the drug treatment of this viral disease and the existing co-morbidities.

scholarly journals Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

2020 ◽  
Author(s):  
Robert Ancuceanu ◽  
Marilena Viorica Hovanet ◽  
Adriana Iuliana Anghel ◽  
Florentina Furtunescu ◽  
Monica Neagu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Injury ◽  
Computational Models ◽  
Liver Toxicity ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Drug Induced ◽  
Reference Drug ◽  
Drug Induced Liver Injury

Drug induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized drugs and candidate drugs and predicting hepatotoxicity from the chemical structure of a substance remains a challenge worth pursuing, being also coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016 a group of researchers from FDA published an improved annotated list of drugs with respect to their DILI risk, constituting “the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans”, DILIrank. This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A number of 78 models with reasonable performance have been selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

scholarly journals Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset

2020 ◽  
Vol 21 (6) ◽  
pp. 2114
Author(s):  
Robert Ancuceanu ◽  
Marilena Viorica Hovanet ◽  
Adriana Iuliana Anghel ◽  
Florentina Furtunescu ◽  
Monica Neagu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Injury ◽  
Computational Models ◽  
Liver Toxicity ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Drug Induced ◽  
Reference Drug ◽  
Drug Induced Liver Injury

Drug-induced liver injury (DILI) remains one of the challenges in the safety profile of both authorized and candidate drugs, and predicting hepatotoxicity from the chemical structure of a substance remains a task worth pursuing. Such an approach is coherent with the current tendency for replacing non-clinical tests with in vitro or in silico alternatives. In 2016, a group of researchers from the FDA published an improved annotated list of drugs with respect to their DILI risk, constituting “the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans” (DILIrank). This paper is one of the few attempting to predict liver toxicity using the DILIrank dataset. Molecular descriptors were computed with the Dragon 7.0 software, and a variety of feature selection and machine learning algorithms were implemented in the R computing environment. Nested (double) cross-validation was used to externally validate the models selected. A total of 78 models with reasonable performance were selected and stacked through several approaches, including the building of multiple meta-models. The performance of the stacked models was slightly superior to other models published. The models were applied in a virtual screening exercise on over 100,000 compounds from the ZINC database and about 20% of them were predicted to be non-hepatotoxic.

Development and Application of a Transcriptomic Signature of Bioactivation in an Advanced In Vitro Liver Model to Reduce Drug-induced Liver Injury Risk Early in the Pharmaceutical Pipeline

2020 ◽  
Vol 177 (1) ◽  
pp. 121-139 ◽  
Author(s):  
Wen Kang ◽  
Alexei A Podtelezhnikov ◽  
Keith Q Tanis ◽  
Stephen Pacchione ◽  
Ming Su ◽  
...  
Keyword(s):  
Liver Injury ◽  
Human Model ◽  
Reactive Metabolites ◽  
In Vitro Test ◽  
Drug Induced ◽  
Vitro Assay ◽  
Drug Induced Liver Injury ◽  
Drug Candidates ◽  
Transcriptomic Signature

Abstract Early risk assessment of drug-induced liver injury (DILI) potential for drug candidates remains a major challenge for pharmaceutical development. We have previously developed a set of rat liver transcriptional biomarkers in short-term toxicity studies to inform the potential of drug candidates to generate a high burden of chemically reactive metabolites that presents higher risk for human DILI. Here, we describe translation of those NRF1-/NRF2-mediated liver tissue biomarkers to an in vitro assay using an advanced micropatterned coculture system (HEPATOPAC) with primary hepatocytes from male Wistar Han rats. A 9-day, resource-sparing and higher throughput approach designed to identify new chemical entities with lower reactive metabolite-forming potential was qualified for internal decision making using 93 DILI-positive and -negative drugs. This assay provides 81% sensitivity and 90% specificity in detecting hepatotoxicants when a positive test outcome is defined as the bioactivation signature score of a test drug exceeding the threshold value at an in vitro test concentration that falls within 3-fold of the estimated maximum drug concentration at the human liver inlet following highest recommended clinical dose administrations. Using paired examples of compounds from distinct chemical series and close structural analogs, we demonstrate that this assay can differentiate drugs with lower DILI risk. The utility of this in vitro transcriptomic approach was also examined using human HEPATOPAC from a single donor, yielding 68% sensitivity and 86% specificity when the aforementioned criteria are applied to the same 93-drug test set. Routine use of the rat model has been adopted with deployment of the human model as warranted on a case-by-case basis. This in vitro transcriptomic signature-based strategy can be used early in drug discovery to derisk DILI potential from chemically reactive metabolites by guiding structure-activity relationship hypotheses and candidate selection.

scholarly journals A Critical Perspective on 3D Liver Models for Drug Metabolism and Toxicology Studies

2021 ◽  
Vol 9 ◽  
Author(s):  
Ana S. Serras ◽  
Joana S. Rodrigues ◽  
Madalena Cipriano ◽  
Armanda V. Rodrigues ◽  
Nuno G. Oliveira ◽  
...  
Keyword(s):  
Drug Development ◽  
Liver Toxicity ◽  
Three Dimensional ◽  
Cell Types ◽  
Cell Phenotype ◽  
Drug Induced ◽  
Characterization Methods ◽  
Clinical Phase ◽  
Post Marketing

The poor predictability of human liver toxicity is still causing high attrition rates of drug candidates in the pharmaceutical industry at the non-clinical, clinical, and post-marketing authorization stages. This is in part caused by animal models that fail to predict various human adverse drug reactions (ADRs), resulting in undetected hepatotoxicity at the non-clinical phase of drug development. In an effort to increase the prediction of human hepatotoxicity, different approaches to enhance the physiological relevance of hepatic in vitro systems are being pursued. Three-dimensional (3D) or microfluidic technologies allow to better recapitulate hepatocyte organization and cell-matrix contacts, to include additional cell types, to incorporate fluid flow and to create gradients of oxygen and nutrients, which have led to improved differentiated cell phenotype and functionality. This comprehensive review addresses the drug-induced hepatotoxicity mechanisms and the currently available 3D liver in vitro models, their characteristics, as well as their advantages and limitations for human hepatotoxicity assessment. In addition, since toxic responses are greatly dependent on the culture model, a comparative analysis of the toxicity studies performed using two-dimensional (2D) and 3D in vitro strategies with recognized hepatotoxic compounds, such as paracetamol, diclofenac, and troglitazone is performed, further highlighting the need for harmonization of the respective characterization methods. Finally, taking a step forward, we propose a roadmap for the assessment of drugs hepatotoxicity based on fully characterized fit-for-purpose in vitro models, taking advantage of the best of each model, which will ultimately contribute to more informed decision-making in the drug development and risk assessment fields.

The Urinary Excretion of Lysozyme in Dogs

1970 ◽  
Vol 38 (4) ◽  
pp. 533-547 ◽  
Author(s):  
J. F. Harrison ◽  
A. D. Barnes
Keyword(s):  
Venous Blood ◽  
Blood Stream ◽  
Lysozyme Activity ◽  
Bence Jones Protein ◽  
Glomerular Permeability ◽  
Renal Threshold ◽  
Reabsorptive Capacity ◽  
Glomerular Filtrate ◽  
Serum And Urine

1. Twelve dogs under light anaesthesia were infused with creatinine, lysozyme and other proteins, and the femoral arterial and urinary concentrations of the infused substances were measured. In some experiments renal venous blood was withdrawn through a catheter inserted by laparotomy. 2. The glomerular permeability to lysozyme was estimated to be 38% of the permeability to creatinine, but there was wide variation and the standard deviation was 11%. 3. The maximum tubular reabsorptive capacity for lysozyme was estimated to be 1·0 mg/100 ml glomerular filtrate, SD 0·44 mg/100 ml. 4. The renal threshold for lysozyme was about 1·0 mg/100 ml. 5. There was evidence supporting the hypothesis that reabsorbed lysozyme is catabolized and no evidence of reabsorption of intact lysozyme into the blood stream. 6. Infusion of myglobin, Bence Jones protein and ovalbumin had no effect on the excretion of endogenous or exogenous (infused) lysozyme. 7. Lysozyme infusions had no conclusive effect on the excretion of (infused) Bence Jones protein or ovalbumin. 8. Corrections, based on the recovery in vitro of lysozyme activity from dog serum and urine, do not significantly alter the results.

scholarly journals Development of Scaffolds with Adjusted Stiffness for Mimicking Disease-Related Alterations of Liver Rigidity

2020 ◽  
Vol 11 (1) ◽  
pp. 17 ◽  
Author(s):  
Marc Ruoß ◽  
Silas Rebholz ◽  
Marina Weimer ◽  
Carl Grom-Baumgarten ◽  
Kiriaki Athanasopulu ◽  
...  
Keyword(s):  
Drug Metabolism ◽  
Liver Toxicity ◽  
Calf Serum ◽  
Liver Stiffness ◽  
In Vivo Studies ◽  
Drug Induced ◽  
Fibrotic Liver ◽  
Vitro Model

Drug-induced liver toxicity is one of the most common reasons for the failure of drugs in clinical trials and frequent withdrawal from the market. Reasons for such failures include the low predictive power of in vivo studies, that is mainly caused by metabolic differences between humans and animals, and intraspecific variances. In addition to factors such as age and genetic background, changes in drug metabolism can also be caused by disease-related changes in the liver. Such metabolic changes have also been observed in clinical settings, for example, in association with a change in liver stiffness, a major characteristic of an altered fibrotic liver. For mimicking these changes in an in vitro model, this study aimed to develop scaffolds that represent the rigidity of healthy and fibrotic liver tissue. We observed that liver cells plated on scaffolds representing the stiffness of healthy livers showed a higher metabolic activity compared to cells plated on stiffer scaffolds. Additionally, we detected a positive effect of a scaffold pre-coated with fetal calf serum (FCS)-containing media. This pre-incubation resulted in increased cell adherence during cell seeding onto the scaffolds. In summary, we developed a scaffold-based 3D model that mimics liver stiffness-dependent changes in drug metabolism that may more easily predict drug interaction in diseased livers.

Ultrastructural studies on the interaction of haemophilus influenzae with human endothelial cells in vitro

1990 ◽  
Vol 48 (3) ◽  
pp. 636-637
Author(s):  
D.J.P. Ferguson ◽  
M. Virji ◽  
H. Kayhty ◽  
E.R. Moxon
Keyword(s):  
Endothelial Cells ◽  
Haemophilus Influenzae ◽  
Intercellular Junctions ◽  
Blood Stream ◽  
Ultrastructural Studies ◽  
Endothelial Barriers ◽  
Serotype B ◽  
Meningitis In Children ◽  
Respiratory Epithelial

Haemophilus influenzae is a human pathogen which causes meningitis in children. Systemic H. influenzae infection is largely confined to encapsulated serotype b organisms and is a major cause of meningitis in the U.K. and elsewhere. However, the pathogenesis of the disease is still poorly understood. Studies in the infant rat model, in which intranasal challenge results in bacteraemia, have shown that H. influenzae enters submucosal tissues and disseminates to the blood stream within minutes. The rapidity of these events suggests that H. influenzae penetrates both respiratory epithelial and endothelial barriers with great efficiency. It is not known whether the bacteria penetrate via the intercellular junctions, are translocated within the cells or carried across the cellular barrier in 'trojan horse' fashion within phagocytes. In the present studies, we have challenged cultured human umbilical cord_vein endothelial cells (HUVECs) with both capsulated (b+) and capsule-deficient (b-) isogenic variants of one strain of H. influenzae in order to investigate the interaction between the bacteria and HUVEC and the effect of the capsule.

A Hexagonal (II) Phase Phospholipid Neutralization Assay for Lupus Anticoagulant Identification

1993 ◽  
Vol 70 (05) ◽  
pp. 787-793 ◽  
Author(s):  
Douglas A Triplett ◽  
Linda K Barna ◽  
Gail A Unger
Keyword(s):  
Hemophilia A ◽  
Clinical Laboratory ◽  
Neutralization Assay ◽  
Confirmatory Test ◽  
Specific Factor ◽  
Clinical Settings ◽  
Drug Induced ◽  
Variable Screening ◽  
Routine Clinical Laboratory

SummaryLupus anticoagulants (LAs) are immunoglobulins (IgG, IgM, or both) which interfere with in vitro phospholipid (PL) dependent tests of coagulation (e.g. APTT, dilute PT, dilute Russell Viper Venom Time). These antibodies may be identified in a wide variety of clinical settings. With the exception of heparinized patient samples, the presence of LAs is often the most common cause of an unexplained APTT in a routine clinical laboratory. The diagnosis of LAs is difficult due to variable screening reagent sensitivity and intrinsic heterogeneity of LAs. Recently, Rauch and colleagues have shown human monoclonal hybridoma LAs were inhibited by hexagonal (II) phase PLs. In contrast, lamellar phase PLs had no effect. We have evaluated a new assay system, Staclot LA®, which utilizes a hexagonal (II) phase PL (egg phosphatidylethanolamine [EPE]) as a confirmatory test for LAs. Plasma samples from the following patient populations were studied: LA positive, heparinized, oral anticoagulated, hemophilia A and B, and specific factor inhibitors (factors V, VIII, IX). Unlike previous studies, the LA positive patients were a mixed population including: autoimmune diseases, drug-induced, and post-infection. Our findings confirm the specificity of hexagonal (II) phase PL neutralization of LAs.

Maternal and Fetal Platelet Responses and Adrenoceptor Binding Characteristics

1985 ◽  
Vol 53 (01) ◽  
pp. 095-098 ◽  
Author(s):  
C R Jones ◽  
R McCabe ◽  
C A Hamilton ◽  
J L Reid
Keyword(s):  
Adenylate Cyclase ◽  
Venous Blood ◽  
Adenosine Diphosphate ◽  
Binding Characteristics ◽  
Receptor Coupling ◽  
Threshold Response ◽  
Alpha Receptors ◽  
Maternal Responses ◽  
Epidural Anaesthetic

SummaryPaired blood samples were obtained from mothers (venous) and babies (cord venous blood) at the time of delivery by caesarean section under epidural anaesthetic. Fetal platelets failed to aggregate in response to adrenaline in vitro although adrenaline could potentiate the threshold response to adenosine diphosphate (1 μM). Fetal platelet responses to collagen and 8 Arg vasopressin did not differ significantly from maternal responses. Maternal and fetal platelets also showed similar inhibition of aggregation after activation of adenylate cyclase (PGE1 and parathormone), in contrast to the inhibition of adenylate cyclase by adrenaline.Alpha2 adrenoceptors were investigated using [3H] yohimbine binding receptor number and were reduced modestly but significantly on fetal compared to maternal platelets. The failure of fetal platelet aggregation in response to adrenaline appears to be related to a failure of receptor coupling and may represent a delayed maturation of fetal platelet alpha receptors or a response- to increased circulating catecholamines during birth.

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