Purdue University Graduate School
Chandrali 07.6.2020_final_thesis.pdf (11.11 MB)


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posted on 2020-07-07, 15:17 authored by Chandrali S BhattacharyaChandrali S Bhattacharya
Background: Bupropion, an atypical antidepressant and smoking cessation aid, is associated with wide inter-subject variability in its efficacy and safety. Variability in response to bupropion therapy is thought to be driven by variability in metabolism. Bupropion undergoes complex phase 1 and 2 stereoselective metabolism. Though bupropion`s pharmacology is not fully understood, much of it is thought to be due to its metabolites, specially, S, S-hydroxybupropion. In vitro studies (functional assays measuring IC50 at dopamine transporter-DAT, norepinephrine transporter-NET, various subtypes of nicotinic receptors-nAChR) and mouse models (forced swim test to assess antidepressant effect, antinociceptive models to assess antagonism of nicotine effects) indicate S, S-hydroxybupropion to contribute more towards efficacy as an antidepressant and smoking cessation aid than racemic bupropion and R, R-hydroxybupropion, respectively. Both pharmacokinetics (PK) and pharmacodynamics (PD) of bupropion and its metabolites are complex and reported to be stereoselective. As bupropion is known to act on multiple central nervous system (CNS) targets (DAT, NET nAChR), understanding CNS disposition (target site) is critical to explain variability in bupropion`s therapeutic and toxic effects.
Objective: The objective of our study was to characterize the exposure of bupropion enantiomers and corresponding phase 1 metabolite diastereomers in plasma and brain in a surrogate non-clinical species, and to subsequently develop animal-to-human-translational population-PK and Physiologically Based PK (PBPK) models to predict human brain concentrations of bupropion and its active metabolite S, S-hydroxybupropion. Application of these PK modeling approaches to map the time course of unbound brain concentration can then be compared to in vitro potency measures at DAT, NET and nAChRs to predict target engagement over time (PD). Establishing relationships between plasma PK, target site PK along with PD would elucidate possible cause(s) of inter-patient variability to bupropion therapy.
Methods: The first step towards development of a CNS model was to identify a nonclinical species with phase 1 metabolism closest to humans. To accomplish this, hepatic microsomal incubations of four species-rat, mouse, non-human primates (NHPs) and humans were conducted separately for the R- and S-bupropion enantiomers, and the formation of enantiomer-specific metabolites was determined using LC-MS/MS. Intrinsic formation clearance (CLint) of metabolites across the four species (rats, mice, NHPs, humans) was determined from the formation rate versus substrate concentration relationship.
Racemic bupropion (10 mg/kg) and preformed S, S-hydroxybupropion (2 mg/kg) were administered subcutaneously to adult male Sprague Dawley rats (n = 24/compound). Brain and plasma were collected from rats (n = 3) at eight time points for 6 hours and analyzed using a chiral LC-MS/MS method. Rat plasma protein and brain homogenate binding studies were conducted for all analytes to correct for unbound fraction using equilibrium dialysis method.
A plasma-brain compartmental pharmacokinetic approach was used to describe the blood–brain-barrier transport of both bupropion and S, S-hydroxybupropion. Also, a 2-compartment permeability-limited brain model consisting of brain blood, brain mass compartments was developed and incorporated into a whole body physiologically-based pharmacokinetic (PBPK) parent-metabolite model for bupropion and S, S-hydroxybupropion. Both population PK and PBPK modeling approaches were subsequently translated to humans to predict human plasma and brain site exposure and its relationship to DAT and NET IC50 potencies.
Results: The total clearance of S-bupropion was higher than that of R-bupropion in monkey and human liver microsomes. The contribution of hydroxybupropion to the total racemic bupropion clearance was 38%, 62%, 17%, and 96% in human, monkey, rat, and mouse, respectively. In the same species order, threohydrobupropion contributed 53%, 23%, 17%, and 3%, and erythrohydrobupropion contributed 9%, 14%, 66%, and 1.3%, respectively, to racemic bupropion clearance. Hepatic microsomal incubation studies indicated non-human primates to be the appropriate species to model CNS disposition. However, the cost and limited pharmacokinetic and pharmacodynamic data in NHPs were insurmountable barriers to conducting in vivo studies in NHPs. After considering multiple factors, such as the formation of reductive metabolites (higher in rats than mice), which are also thought to contribute to bupropion`s therapeutic efficacy, availability of microdialysis data measuring bupropion and dopamine, norepinephrine levels in brain extracellular fluid (ECF) and other in vitro potency evaluations in rats, rat was chosen as the surrogate species to model bupropion`s disposition.
In rats, unbound plasma and brain exposures and plasma clearances of both R and S-bupropion were similar. The exposure to parent was higher (50 to 100-fold) than to metabolites. The exposure of oxidative metabolites (R, R- and S, S-hydroxybupropion) was 2 to 3-fold higher in brain and plasma than reductive metabolites (R, R- and S, S-threohydrobupropion, S, R- and R, S-erythrohydrobupropion). Hepatic clearances of R- and S-bupropion scaled from in vitro rat hepatic microsomal incubation studies were 3-fold and 25-fold lower than their respective in vivo unbound apparent clearances. This could possibly be due to substantial contribution of metabolic pathways not characterized in this in vivo study and/or possible extrahepatic disposition in the rat. The unbound brain to unbound plasma AUC0-6h ratio (Kp,uu) of R- and S-bupropion were 0.43 and 0.38 respectively. Kp,uu of oxidative metabolites (R, R- and S, S-hydroxybupropion) and reductive metabolites (R, R- and S, S-threohydrobupropion) were close to 1. Kp,uu of S, R-erythrohydrobupropion was 0.43 and that of pre-formed S, S-hydroxybupropion was 5.
With respect to population PK modeling of both bupropion and S, S-hydroxybupropion, a plasma-brain compartmental model structure with time dependent change in brain influx clearance was required to adequately characterize the BBB transport of parent and this active metabolite. Using a physiologically-based pharmacokinetic model (PBPK) approach too, incorporation of active efflux and carrier mediated uptake terms in addition to passive permeability was necessary to adequately characterize brain disposition of bupropion and S, S-hydroxybupropion. Both modeling approaches (population-PK and PBPK) when translated to humans indicated that the predicted human brain exposures fall below the reported DAT and NET IC50 measures of bupropion and S, S-hydroxybupropion.
Conclusion: Specific to our work in the rat, the discrepancy between in vitro scaled hepatic clearance and in vivo plasma clearance of R and S-bupropion suggests alternative non-CYP mediated clearance pathways and/or extra hepatic disposition of bupropion. Both translational PK models indicate active process such as efflux transporter or carrier mediated uptake could be involved in bupropion`s disposition in the brain. Variability in expression of these speculated active/carrier mediated transporters could possibly cause variability in response. Also, other CNS targets could contribute to bupropion`s therapeutic efficacy, elucidation of which would require further investigation.


Indiana Clinical and Translational Sciences Institute (CTSI) for the pre doctoral grant (Grant Number UL1TR002529, A. Shekhar, PI), from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award

IU Simon Comprehensive Cancer Center Support Grant (P30CA082709)


Degree Type

  • Doctor of Philosophy


  • Pharmacy Practice

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Brian R. Overholser

Advisor/Supervisor/Committee co-chair

Robert E. Stratford

Additional Committee Member 2

Kevin M. Sowinski

Additional Committee Member 3

David R. Foster

Additional Committee Member 4

Zeruesenay Desta