Publications by authors named "Jennifer Sager"

14 Publications

  • Page 1 of 1

Pregnancy has no Clinically Significant Effect on the Pharmacokinetics of Bupropion or Its Metabolites.

Ther Drug Monit 2021 Mar 9. Epub 2021 Mar 9.

Department of Obstetrics and Gynecology, University of Washington School of Medicine, Seattle, WA. Department of Pharmaceutics, University of Washington School of Pharmacy, Seattle, WA.

Background: Bupropion (BUP) is a chiral antidepressant and smoking cessation aide with benefits and side effects correlated with parent and active metabolite concentrations. BUP is metabolized by CYP2B6, CYP2C19, and CYP3A4 to hydroxy-BUP (OH-BUP), and by 11β-hydroxysteroid dehydrogenase-1 and aldo-keto reductases to threohydrobupropion (Threo) and erythrohydrobupropion (Erythro), respectively. As pregnancy alters the activity of drug-metabolizing enzymes, the authors hypothesized that BUP metabolism and BUP metabolite concentrations, would be altered during pregnancy, potentially affecting the efficacy and safety of BUP in pregnant women.

Methods: Pregnant women (n=8) taking BUP chronically were enrolled, and steady-state plasma samples and dosing interval urine samples were collected during pregnancy and postpartum. Maternal and umbilical cord venous blood samples were collected at delivery from three subjects, and cord blood/maternal plasma concentration ratios were calculated. The concentrations of BUP stereoisomers and their metabolites were measured. Paired t-tests were used to compare pharmacokinetic parameters during pregnancy and postpartum.

Results: No significant changes were observed in the steady-state plasma concentrations, metabolite to parent ratios, formation clearances, or renal clearance of any of the compounds during pregnancy when compared to postpartum. The umbilical cord venous plasma concentrations of BUP and its metabolites were 30-60% lower than maternal plasma concentrations.

Conclusions: This study showed that there are no clinically meaningful differences in the stereoselective disposition of BUP or its metabolites during pregnancy, indicating that dose adjustment during pregnancy may not be necessary. The results also showed that the placenta provides a partial barrier for bupropion and its metabolite distribution to the fetus, with possible placental efflux transport of bupropion and its metabolites.
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http://dx.doi.org/10.1097/FTD.0000000000000885DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426418PMC
March 2021

2020 AAHA Anesthesia and Monitoring Guidelines for Dogs and Cats.

J Am Anim Hosp Assoc 2020 Mar/Apr;56(2):59-82

From Washington State University College of Veterinary Medicine, Pullman, Washington (T.G.); University of Florida Veterinary Hospitals, Gainesville, Florida (J.S.); Peak Performance Veterinary Group, Breckenridge, Colorado (J.S.G.); University of California, Davis, School of Veterinary Medicine, Davis, California (E.M.); Pima Pet Clinic, Tucson, Arizona (J.A.P.); Veterinary Anesthesia Specialists, Clackamas, Oregon (H.S.); and Wheat Ridge Animal Hospital, Wheat Ridge, Colorado (C.T.).

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http://dx.doi.org/10.5326/JAAHA-MS-7055DOI Listing
November 2020

AAFP Feline Anesthesia Guidelines.

J Feline Med Surg 2018 07;20(7):602-634

Colorado State University Veterinary Teaching Hospital, 300 W Drake Rd, Fort Collins, CO 80523, USA.

Aim: The overarching purpose of the AAFP Anesthesia Guidelines (hereafter referred to as the 'Guidelines') is to make anesthesia and sedation safer for the feline patient. Scope and accessibility: It is noteworthy that these are the first exclusively feline anesthesia guidelines authored by an expert panel, making them particularly useful as an extensively referenced, practical resource for veterinary practice teams. Because much of the key content is presented in tabular or visual format, the Guidelines have a high level of accessibility and convenience that invites regular usage. While the recommendations in the Guidelines focus primarily on client-owned cats, the content is also applicable to community-sourced animals with an unknown medical history.
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http://dx.doi.org/10.1177/1098612X18781391DOI Listing
July 2018

Physiologically Based Pharmacokinetic Model of the CYP2D6 Probe Atomoxetine: Extrapolation to Special Populations and Drug-Drug Interactions.

Drug Metab Dispos 2017 11 31;45(11):1156-1165. Epub 2017 Aug 31.

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington

Physiologically based pharmacokinetic (PBPK) modeling of drug disposition and drug-drug interactions (DDIs) has become a key component of drug development. PBPK modeling has also been considered as an approach to predict drug disposition in special populations. However, whether models developed and validated in healthy populations can be extrapolated to special populations is not well established. The goal of this study was to determine whether a drug-specific PBPK model validated using healthy populations could be used to predict drug disposition in specific populations and in organ impairment patients. A full PBPK model of atomoxetine was developed using a training set of pharmacokinetic (PK) data from CYP2D6 genotyped individuals. The model was validated using drug-specific acceptance criteria and a test set of 14 healthy subject PK studies. Population PBPK models were then challenged by simulating the effects of ethnicity, DDIs, pediatrics, and renal and hepatic impairment on atomoxetine PK. Atomoxetine disposition was successfully predicted in 100% of healthy subject studies, 88% of studies in Asians, 79% of DDI studies, and 100% of pediatric studies. However, the atomoxetine area under the plasma concentration versus time curve (AUC) was overpredicted by 3- to 4-fold in end stage renal disease and hepatic impairment. The results show that validated PBPK models can be extrapolated to different ethnicities, DDIs, and pediatrics but not to renal and hepatic impairment patients, likely due to incomplete understanding of the physiologic changes in these conditions. These results show that systematic modeling efforts can be used to further refine population models to improve the predictive value in this area.
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http://dx.doi.org/10.1124/dmd.117.076455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5637815PMC
November 2017

Interaction and Transport of Methamphetamine and its Primary Metabolites by Organic Cation and Multidrug and Toxin Extrusion Transporters.

Drug Metab Dispos 2017 07 20;45(7):770-778. Epub 2017 Apr 20.

Department of Pharmaceutics, University of Washington, Seattle, Washington

Methamphetamine is one of the most abused illicit drugs with roughly 1.2 million users in the United States alone. A large portion of methamphetamine and its metabolites is eliminated by the kidney with renal clearance larger than glomerular filtration clearance. Yet the mechanism of active renal secretion is poorly understood. The goals of this study were to characterize the interaction of methamphetamine and its major metabolites with organic cation transporters (OCTs) and multidrug and toxin extrusion (MATE) transporters and to identify the major transporters involved in the disposition of methamphetamine and its major metabolites, amphetamine and -hydroxymethamphetamine (-OHMA). We used cell lines stably expressing relevant transporters to show that methamphetamine and its metabolites inhibit human OCTs 1-3 (hOCT1-3) and hMATE1/2-K with the greatest potencies against hOCT1 and hOCT2. Methamphetamine and amphetamine are substrates of hOCT2, hMATE1, and hMATE2-K, but not hOCT1 and hOCT3. -OHMA is transported by hOCT1-3 and hMATE1, but not hMATE2-K. In contrast, organic anion transporters 1 and 3 do not interact with or transport these compounds. Methamphetamine and its metabolites exhibited complex interactions with hOCT1 and hOCT2, suggesting the existence of multiple binding sites. Our studies suggest the involvement of the renal OCT2/MATE pathway in tubular secretion of methamphetamine and its major metabolites and the potential of drug-drug interactions with substrates or inhibitors of the OCTs. This information may be considered when prescribing medications to suspected or known abusers of methamphetamine to mitigate the risk of increased toxicity or reduced therapeutic efficacy.
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http://dx.doi.org/10.1124/dmd.116.074708DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5478906PMC
July 2017

Quantitative Prediction of CYP3A4 Induction: Impact of Measured, Free, and Intracellular Perpetrator Concentrations from Human Hepatocyte Induction Studies on Drug-Drug Interaction Predictions.

Drug Metab Dispos 2017 06 23;45(6):692-705. Epub 2017 Mar 23.

Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Inc., Boston, Massachusetts

Typically, concentration-response curves are based upon nominal inducer concentrations for in-vitro-to-in-vivo extrapolation of CYP3A4 induction. The limitation of this practice is that it assumes the hepatocyte culture model is a static system. We assessed whether correcting for: 1) changes in perpetrator concentration in the induction medium during the incubation period, 2) perpetrator binding to proteins in the induction medium, and 3) nonspecific binding of perpetrator can improve the accuracy of CYP3A4 induction predictions. Of the seven compounds used in this evaluation, significant parent loss and nonspecific binding were observed for rifampicin (29.3-38.3%), pioglitazone (64.3-78.6%), and rosiglitazone (57.1-75.5%). As a result, the free measured EC values (EC) of pioglitazone, rosiglitazone, and rifampicin were significantly lower than the nominal EC values. In general, the accuracy of the induction predictions, using multiple static models, improved when corrections were made for measured medium concentrations, medium protein binding, and nonspecific binding of the perpetrator, as evidenced by 18-29% reductions in the root mean square error. The relative induction score model performed better than the basic static and mechanistic static models, resulting in lower prediction error and no false-positive or false-negative predictions. However, even when the EC value was used, the induction prediction for bosentan, which is a substrate of organic anion transporter proteins, was overpredicted by approximately 2-fold. Accounting for the ratio of unbound intracellular concentrations to unbound medium concentrations (K) (0.5-7.5) and the predicted multiple-dose K (0.6) for bosentan resulted in induction predictions within 35% of the observed interaction.
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http://dx.doi.org/10.1124/dmd.117.075481DOI Listing
June 2017

In vitro to in vivo extrapolation of the complex drug-drug interaction of bupropion and its metabolites with CYP2D6; simultaneous reversible inhibition and CYP2D6 downregulation.

Biochem Pharmacol 2017 Jan 9;123:85-96. Epub 2016 Nov 9.

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, WA, USA. Electronic address:

Bupropion is a widely used antidepressant and smoking cessation aid and a strong inhibitor of CYP2D6 in vivo. Bupropion is administered as a racemic mixture of R- and S-bupropion and has stereoselective pharmacokinetics. Four primary metabolites of bupropion, threo- and erythro-hydrobupropion and R,R- and S,S-OH-bupropion, circulate at higher concentrations than the parent drug and are believed to contribute to the efficacy and side effects of bupropion as well as to the CYP2D6 inhibition. However, bupropion and its metabolites are only weak inhibitors of CYP2D6 in vitro, and the magnitude of the in vivo drug-drug interactions (DDI) caused by bupropion cannot be explained by the in vitro data even when CYP2D6 inhibition by the metabolites is accounted for. The aim of this study was to quantitatively explain the in vivo CYP2D6 DDI magnitude by in vitro DDI data. Bupropion and its metabolites were found to inhibit CYP2D6 stereoselectively with up to 10-fold difference in inhibition potency between enantiomers. However, the reversible inhibition or active uptake into hepatocytes did not explain the in vivo DDIs. In HepG2 cells and in plated human hepatocytes bupropion and its metabolites were found to significantly downregulate CYP2D6 mRNA in a concentration dependent manner. The in vivo DDI was quantitatively predicted by significant down-regulation of CYP2D6 mRNA and reversible inhibition of CYP2D6 by bupropion and its metabolites. This study is the first example of a clinical DDI resulting from CYP down-regulation and first demonstration of a CYP2D6 interaction resulting from transcriptional regulation.
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http://dx.doi.org/10.1016/j.bcp.2016.11.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5164944PMC
January 2017

Identification and Structural Characterization of Three New Metabolites of Bupropion in Humans.

ACS Med Chem Lett 2016 Aug 17;7(8):791-6. Epub 2016 Jun 17.

Departments of Pharmaceutics, Obstetrics and Gynecology, and Medicinal Chemistry, University of Washington , Seattle, Washington 98195, United States.

Bupropion is a widely used antidepressant and the recommended CYP2B6 probe drug. However, current understanding of bupropion elimination pathways is limited. Bupropion has three active circulating metabolites, OH-bupropion, threohydrobupropion, and erythrohydrobupropion, but together with bupropion these metabolites and their conjugates in urine represent only 23% of the dose, and the majority of the elimination pathways of bupropion result in uncharacterized metabolites. The aim of this study was to determine the structures of the uncharacterized bupropion metabolites using human clinical samples and in vitro incubations. Three new metabolites, 4'-OH-bupropion, erythro-4'-OH-hydrobupropion, and threo-4'-OH-hydrobupropion, were detected in human liver microsome incubations and were isolated from human urine. The structures of the metabolites were confirmed via comparison of UV absorbance, NMR spectra, and mass spectral data to those of the synthesized standards. In total, these metabolites represented 24% of the drug related material excreted in urine.
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http://dx.doi.org/10.1021/acsmedchemlett.6b00189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5026406PMC
August 2016

Stereoselective Metabolism of Bupropion to OH-bupropion, Threohydrobupropion, Erythrohydrobupropion, and 4'-OH-bupropion in vitro.

Drug Metab Dispos 2016 10 5;44(10):1709-19. Epub 2016 Aug 5.

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington

Bupropion is a widely used antidepressant, smoking cessation aid, and weight-loss therapy. It is administered as a racemic mixture, but the pharmacokinetics and activity of bupropion are stereoselective. The activity and side effects of bupropion are attributed to bupropion and its metabolites S,S- and R,R-OH-bupropion, threohydrobupropion, and erythrohydrobupropion. Yet the stereoselective metabolism in vitro and the enzymes contributing to the stereoselective disposition of bupropion have not been characterized. In humans, the fraction of bupropion metabolized (fm) to the CYP2B6 probe metabolite OH-bupropion is 5-16%, but ticlopidine increases bupropion exposure by 61%, suggesting a 40% CYP2B6 and/or CYP2C19 fm for bupropion. Yet, the CYP2C19 contribution to bupropion clearance has not been defined, and the enzymes contributing to overall bupropion metabolite formation have not been fully characterized. The aim of this study was to characterize the stereoselective metabolism of bupropion in vitro to explain the stereoselective pharmacokinetics and the effect of drug-drug interactions (DDIs) and CYP2C19 pharmacogenetics on bupropion exposure. The data predict that threohydrobupropion accounts for 50 and 82%, OH-bupropion for 34 and 12%, erythrohydrobupropion for 8 and 4%, and 4'-OH-bupropion for 8 and 2% of overall R- and S-bupropion clearance, respectively. The fm,CYP2B6 was predicted to be 21%, and the fm,CYP2C19, 6% for racemic bupropion. Importantly, ticlopidine was found to inhibit all metabolic pathways of bupropion in vitro, including threohydrobupropion, erythrohydrobupropion, and 4'OH-bupropion formation, explaining the in vivo DDI. The stereoselective pharmacokinetics of bupropion were quantitatively explained by the in vitro metabolic clearances and in vivo interconversion between bupropion stereoisomers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034696PMC
http://dx.doi.org/10.1124/dmd.116.072363DOI Listing
October 2016

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification.

Drug Metab Dispos 2015 Nov 21;43(11):1823-37. Epub 2015 Aug 21.

Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms "PBPK" and "physiologically based pharmacokinetic model" to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.
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http://dx.doi.org/10.1124/dmd.115.065920DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4613950PMC
November 2015

Inhibition of CYP2C19 and CYP3A4 by omeprazole metabolites and their contribution to drug-drug interactions.

Drug Metab Dispos 2013 Jul 25;41(7):1414-24. Epub 2013 Apr 25.

Department of Pharmaceutics, School of Pharmacy, University of Washington, University of Washington, Seattle, WA, USA.

The aim of this study was to evaluate the contribution of metabolites to drug-drug interactions (DDI) using the inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites as a model. Of the metabolites identified in vivo, 5-hydroxyomeprazole, 5'-O-desmethylomeprazole, omeprazole sulfone, and carboxyomeprazole had a metabolite to parent area under the plasma concentration-time curve (AUC(m)/AUC(p)) ratio ≥ 0.25 when either total or unbound concentrations were measured after a single 20-mg dose of omeprazole in a cocktail. All of the metabolites inhibited CYP2C19 and CYP3A4 reversibly. In addition omeprazole, omeprazole sulfone, and 5'-O-desmethylomeprazole were time dependent inhibitors (TDI) of CYP2C19, whereas omeprazole and 5'-O-desmethylomeprazole were found to be TDIs of CYP3A4. The in vitro inhibition constants and in vivo plasma concentrations were used to evaluate whether characterization of the metabolites affected DDI risk assessment. Identifying omeprazole as a TDI of both CYP2C19 and CYP3A4 was the most important factor in DDI risk assessment. Consideration of reversible inhibition by omeprazole and its metabolites would not identify DDI risk with CYP3A4, and with CYP2C19, reversible inhibition values would only identify DDI risk if the metabolites were included in the assessment. On the basis of inactivation data, CYP2C19 and CYP3A4 inhibition by omeprazole would be sufficient to identify risk, but metabolites were predicted to contribute 30-63% to the in vivo hepatic interactions. Therefore, consideration of metabolites may be important in quantitative predictions of in vivo DDIs. The results of this study show that, although metabolites contribute to in vivo DDIs, their relative abundance in circulation or logP values do not predict their contribution to in vivo DDI risk.
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http://dx.doi.org/10.1124/dmd.113.051722DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3684819PMC
July 2013

Age- and calorie-independent life span extension from dietary restriction by bacterial deprivation in Caenorhabditis elegans.

BMC Dev Biol 2008 May 5;8:49. Epub 2008 May 5.

Department of Pathology, University of Washington, Seattle, WA 98195, USA.

Background: Dietary restriction (DR) increases life span and delays age-associated disease in many organisms. The mechanism by which DR enhances longevity is not well understood.

Results: Using bacterial food deprivation as a means of DR in C. elegans, we show that transient DR confers long-term benefits including stress resistance and increased longevity. Consistent with studies in the fruit fly and in mice, we demonstrate that DR also enhances survival when initiated late in life. DR by bacterial food deprivation significantly increases life span in worms when initiated as late as 24 days of adulthood, an age at which greater than 50% of the cohort have died. These survival benefits are, at least partially, independent of food consumption, as control fed animals are no longer consuming bacterial food at this advanced age. Animals separated from the bacterial lawn by a barrier of solid agar have a life span intermediate between control fed and food restricted animals. Thus, we find that life span extension from bacterial deprivation can be partially suppressed by a diffusible component of the bacterial food source, suggesting a calorie-independent mechanism for life span extension by dietary restriction.

Conclusion: Based on these findings, we propose that dietary restriction by bacterial deprivation increases longevity in C. elegans by a combination of reduced food consumption and decreased food sensing.
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http://dx.doi.org/10.1186/1471-213X-8-49DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2408926PMC
May 2008

Characterization of transverse channel concentration profiles obtainable with a class of microfluidic networks.

Langmuir 2006 Apr;22(9):4452-5

Department of Computer Science, University of New Mexico, Albuquerque, New Mexico 87131, USA.

We analyze mathematically a previously reported class of passive microfluidic mixing networks. The networks produce nonhomogeneous concentrations in the output channel, resulting in diverse concentration profiles. We formally prove that all profiles obtainable with this class of networks can be described as polynomials of degree no higher than the number of input channels less one. We derive explicit formulas for the calculation of resultant output concentration profiles and conversely for the calculation of input concentrations needed to obtain set output profiles.
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http://dx.doi.org/10.1021/la052166pDOI Listing
April 2006
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