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  4. Linking organic anion transporting polypeptide 1B1 and 1B3 (OATP1B1 and OATP1B3) interaction profiles to hepatotoxicity - The hyperbilirubinemia use case
 
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2017
Journal Article
Title

Linking organic anion transporting polypeptide 1B1 and 1B3 (OATP1B1 and OATP1B3) interaction profiles to hepatotoxicity - The hyperbilirubinemia use case

Abstract
Hyperbilirubinemia is a pathological condition of excessive accumulation of conjugated or unconjugated bilirubin in blood. It has been associated with neurotoxicity and non-neural organ dysfunctions, while it can also be a warning of liver side effects. Hyperbilirubinemia can either be a result of overproduction of bilirubin due to hemolysis or dyserythropoiesis, or the outcome of impaired bilirubin elimination due to liver transporter malfunction or inhibition. There are several reports in literature that inhibition of organic anion transporting polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) might lead to hyperbilirubinemia. In this study we created a set of classification models for hyperbilirubinemia, which, besides physicochemical descriptors, also include the output of classification models of human OATP1B1 and 1B3 inhibition. Models were based on either human data derived from public toxicity reports or animal data extracted from the eTOX database VITIC. The gener ated models showed satisfactory accuracy (68%) and area under the curve (AUC) for human data and 71% accuracy and 70% AUC for animal data. However, our results did not indicate strong association between OATP inhibition and hyperbilirubinemia, neither for humans nor for animals.
Author(s)
Kotsampasakou, Eleni
Escher, Sylvia E.
Ecker, Gerhard F.
Journal
European journal of pharmaceutical sciences : EUFEPS  
DOI
10.1016/j.ejps.2017.01.002
Language
English
Fraunhofer-Institut für Toxikologie und Experimentelle Medizin ITEM  
Keyword(s)
  • Hyperbilirubinemia

  • liver

  • Organic anion transporting polypeptide 1B1 (OATP1B1)

  • Organic anion transporting polypeptide 1B3 (OATP1B3)

  • classification

  • support vector machines

  • decision trees

  • Amphotericin B

  • Atazanavir

  • Ciprofloxacin

  • Citalopram

  • Clopidogrel

  • Itraconazole

  • Paclitaxel

  • Nelfinavir

  • cyclosporine

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