Literature DB >> 29785262

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification.

Rosa Chan1, Leslie Z Benet1.   

Abstract

Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have achieved only minimal success. Several studies have shown total administered dose alone or in combination with drug lipophilicity to be correlated with a higher risk of DILI. However, it would be best to have a predictive DILI methodology early in drug development, long before the clinical dose is known. Here we discuss the extent to which Biopharmaceutics Drug Disposition Classification System (BDDCS) defining characteristics, independent of knowing actual drug pharmacokinetics/pharmacodynamics and dose, can be used to evaluate prior published predictive proposals. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity, and that all of the short-lived published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensively metabolized compounds are at higher risk of developing DILI is confirmed, but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs.
CONCLUSION: Our published analyses suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms, although BDDCS classification itself is not sufficiently predictive. Almost all of the predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs, although some early data with microliver platforms enabling long-enduring metabolic competency show promising results.

Entities:  

Keywords:  BDDCS; BSEP; Drug-induced liver injury; FDA hepatic liability; daily dose

Year:  2018        PMID: 29785262      PMCID: PMC5959290          DOI: 10.1039/C8TX00016F

Source DB:  PubMed          Journal:  Toxicol Res (Camb)        ISSN: 2045-452X            Impact factor:   3.524


  53 in total

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Authors:  Hartmut Jaeschke; Gregory J Gores; Arthur I Cederbaum; Jack A Hinson; Dominique Pessayre; John J Lemasters
Journal:  Toxicol Sci       Date:  2002-02       Impact factor: 4.849

4.  Evaluation of DILI Predictive Hypotheses in Early Drug Development.

Authors:  Rosa Chan; Leslie Z Benet
Journal:  Chem Res Toxicol       Date:  2017-03-15       Impact factor: 3.739

5.  Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.

Authors:  Chelsea M Hosey; Leslie Z Benet
Journal:  Mol Pharm       Date:  2015-04-23       Impact factor: 4.939

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Authors:  A Srivastava; J L Maggs; D J Antoine; D P Williams; D A Smith; B K Park
Journal:  Handb Exp Pharmacol       Date:  2010

7.  Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanistic in vitro Assays.

Authors:  Falgun Shah; Louis Leung; Hugh A Barton; Yvonne Will; A David Rodrigues; Nigel Greene; Michael D Aleo
Journal:  Toxicol Sci       Date:  2015-07-23       Impact factor: 4.849

Review 8.  Toward predictive models for drug-induced liver injury in humans: are we there yet?

Authors:  Minjun Chen; Halil Bisgin; Lillian Tong; Huixiao Hong; Hong Fang; Jürgen Borlak; Weida Tong
Journal:  Biomark Med       Date:  2014       Impact factor: 2.851

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Authors:  Leslie Z Benet
Journal:  Basic Clin Pharmacol Toxicol       Date:  2009-12-07       Impact factor: 4.080

10.  LiverTox: a website on drug-induced liver injury.

Authors:  Jay H Hoofnagle; Jose Serrano; James E Knoben; Victor J Navarro
Journal:  Hepatology       Date:  2013-03       Impact factor: 17.425

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  4 in total

1.  Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).

Authors:  Eni Minerali; Daniel H Foil; Kimberley M Zorn; Thomas R Lane; Sean Ekins
Journal:  Mol Pharm       Date:  2020-06-08       Impact factor: 4.939

2.  Decreasing HepG2 Cytotoxicity by Lowering the Lipophilicity of Benzo[d]oxazolephosphinate Ester Utrophin Modulators.

Authors:  Maria Chatzopoulou; Enrico Emer; Cristina Lecci; Jessica A Rowley; Anne-Sophie Casagrande; Lee Moir; Sarah E Squire; Stephen G Davies; Shawn Harriman; Graham M Wynne; Francis X Wilson; Kay E Davies; Angela J Russell
Journal:  ACS Med Chem Lett       Date:  2020-11-04       Impact factor: 4.345

3.  Antimycobacterial, Enzyme Inhibition, and Molecular Interaction Studies of Psoromic Acid in Mycobacterium tuberculosis: Efficacy and Safety Investigations.

Authors:  Sherif T S Hassan; Miroslava Šudomová; Kateřina Berchová-Bímová; Shanmugaraj Gowrishankar; Kannan R R Rengasamy
Journal:  J Clin Med       Date:  2018-08-20       Impact factor: 4.241

Review 4.  State of the Art and Uses for the Biopharmaceutics Drug Disposition Classification System (BDDCS): New Additions, Revisions, and Citation References.

Authors:  Giovanni Bocci; Tudor I Oprea; Leslie Z Benet
Journal:  AAPS J       Date:  2022-02-23       Impact factor: 3.603

  4 in total

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