Literature DB >> 32369392

Prediction of Pharmacokinetic Clearance and Potential Drug-Drug Interactions for Omeprazole in the Horse using in vitro Systems.

Khaled A Shibany1, Stephanie L Pratt2, Mohammed Aldurdunji1, Sabine Totemeyer1, Stuart W Paine3.   

Abstract

Horses are exposed to various kinds of medication, however, there are limited determinations of plasma clearance (CLp) for the drugs used due to the high cost of equine in vivo studies. Many of the CLp values generated come from the equine sports industry for determining drug plasma screening limits in the control of medications at the time of competition.The kinetics of omeprazole metabolism were investigated in freshly isolated and cryopreserved equine hepatocytes and hepatic microsomes (n = 3 horses). The Vmax, Km and intrinsic clearance (CLint) of omeprazole were determined via the substrate depletion method as well as Km values for the formation of three metabolites. The CLint values were extrapolated to in vivo hepatic plasma clearance (CLH) using the well stirred and parallel tube models.Clp for omeprazole was successfully predicted using freshly isolated or cryopreserved equine hepatocytes, while microsomes under-predicted. Equine microsomes were used to perform a drug-drug interaction (DDI) study between omeprazole and chloramphenicol. The average inhibitor constant Ki, assuming competitive inhibition, was 15.4 ± 5 µM.To the authors' knowledge, this is the first report showing the successful extrapolation of drug CLp in the horse using equine hepatocytes and the prediction of a DDI using microsomes.

Entities:  

Keywords:  equine; equine hepatocytes; in vitro in vivo extrapolation; liver microsomes; omeprazole

Year:  2020        PMID: 32369392     DOI: 10.1080/00498254.2020.1764131

Source DB:  PubMed          Journal:  Xenobiotica        ISSN: 0049-8254            Impact factor:   1.908


  1 in total

1.  Utilizing virtual experiments to increase understanding of discrepancies involving in vitro-to-in vivo predictions of hepatic clearance.

Authors:  Preethi Krishnan; Andrew K Smith; Glen E P Ropella; Lopamudra Dutta; Ryan C Kennedy; C Anthony Hunt
Journal:  PLoS One       Date:  2022-07-22       Impact factor: 3.752

  1 in total

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