Determining fetal drug exposure (except at the time of birth) is not possible for both logistical and ethical reasons. Therefore, we developed a novel maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) model to predict fetal exposure to drugs and populated this model with gestational age-dependent changes in maternal-fetal physiology. Then, we used this m-f-PBPK to: 1) perform a series of sensitivity analyses to quantitatively demonstrate the impact of fetoplacental metabolism and placental transport on fetal drug exposure for various drug-dosing regimens administered to the mother; 2) predict the impact of gestational age on fetal drug exposure; and 3) demonstrate that a single umbilical venous (UV)/maternal plasma (MP) ratio (even after multiple-dose oral administration to steady state) does not necessarily reflect fetal drug exposure. In addition, we verified the implementation of this m-f-PBPK model by comparing the predicted UV/MP and fetal/MP AUC ratios with those predicted at steady state after an intravenous infusion. Our simulations yielded novel insights into the quantitative contribution of fetoplacental metabolism and/or placental transport on gestational age-dependent fetal drug exposure. Through sensitivity analyses, we demonstrated that the UV/MP ratio does not measure the extent of fetal drug exposure unless obtained at steady state after an intravenous infusion or when there is little or no fluctuation in MP drug concentrations after multiple-dose oral administration. The proposed m-f-PBPK model can be used to predict fetal exposure to drugs across gestational ages and therefore provide the necessary information to assess the risk of drug toxicity to the fetus.
Fetal exposure to drugs cannot be readily estimated from single time point cord blood sampling at the time of delivery. Therefore, we developed a physiologically based pharmacokinetic (PBPK) model to estimate fetal drug exposure throughout pregnancy. In this study, we report verification of this novel maternal-fetal PBPK (m-f-PBPK) model for drugs that passively diffuse across the placenta and are not metabolized/transported there. Our recently built m-f-PBPK model was populated with gestational age-dependent changes in maternal drug disposition and maternal-fetal physiology. Using midazolam as an in vivo calibrator, the transplacental passive diffusion clearance of theophylline and zidovudine was first estimated. Then, for verification, the predicted maternal plasma (MP) and umbilical venous (UV) plasma drug concentrations by our m-f-PBPK were compared against those observed at term. Overall, our m-f-PBPK model well predicted the maternal and fetal exposure to the two verification drugs, theophylline and zidovudine, at term, across a range of dosing regimens, with nearly all observed MP and UV plasma drug concentrations falling within the 90% prediction interval [i.e., 5th-95th percentile range of a virtual pregnant population ( = 100)]. Prediction precision and bias of theophylline MP and UV were 14.5% and 12.4%, and 9.4% and 7.5%, respectively. Furthermore, for zidovudine, after the exclusion of one unexpectedly low MP concentration, prediction precision and bias for MP and UV were 50.3% and 30.2, and 28.3% and 15.0%, respectively. This m-f-PBPK should be useful to predict fetal exposure to drugs, throughout pregnancy, for drugs that passively diffuse across the placenta.
Renal impairment (RI) is known to influence the pharmacokinetics of nonrenally eliminated drugs, although the mechanism and clinical impact is poorly understood. We assessed the impact of RI and single dose oral rifampin (RIF) on the pharmacokinetics of CYP3A, OATP1B, P‐gp, and BCRP substrates using a microdose cocktail and OATP1B endogenous biomarkers. RI alone had no impact on midazolam (MDZ), maximum plasma concentration (Cmax), and area under the curve (AUC), but a progressive increase in AUC with RI severity for dabigatran (DABI), and up to ~2‐fold higher AUC for pitavastatin (PTV), rosuvastatin (RSV), and atorvastatin (ATV) for all degrees of RI was observed. RIF did not impact MDZ, had a progressively smaller DABI drug‐drug interaction (DDI) with increasing RI severity, a similar 3.1‐fold to 4.4‐fold increase in PTV and RSV AUC in healthy volunteers and patients with RI, and a diminishing DDI with RI severity from 6.1‐fold to 4.7‐fold for ATV. Endogenous biomarkers of OATP1B (bilirubin, coproporphyrin I/III, and sulfated bile salts) were generally not impacted by RI, and RIF effects on these biomarkers in RI were comparable or larger than those in healthy volunteers. The lack of a trend with RI severity of PTV and several OATP1B biomarkers, suggests that mechanisms beyond RI directly impacting OATP1B activity could also be considered. The DABI, RSV, and ATV data suggest an impact of RI on intestinal P‐gp, and potentially BCRP activity. Therefore, DDI data from healthy volunteers may represent a worst‐case scenario for clinically derisking P‐gp and BCRP substrates in the setting of RI.
This phase I study assessed the intrapulmonary pharmacokinetic profiles of relebactam (MK-7655), a novel β-lactamase inhibitor, and imipenem. Sixteen healthy subjects received 250 mg relebactam with 500 mg imipenem-cilastatin, given intravenously every 6 h for 5 doses, and were randomized to bronchoscopy/bronchoalveolar lavage at 0.5, 1, 1.5, or 3 h after the last dose (4 subjects per time point). Both drugs penetrated the epithelial lining fluid (ELF) to a similar degree, with the profiles being similar in shape to the corresponding plasma profiles and with the apparent terminal half-lives in plasma and ELF being 1.2 and 1.3 h, respectively, for relebactam and 1.0 h in both compartments for imipenem. The exposure (area under the concentration-time curve from time zero to infinity) in ELF relative to that in plasma was 54% for relebactam and 55% for imipenem, after adjusting for protein binding. ELF penetration for relebactam was further analyzed by fitting the data to a two-compartment pharmacokinetic model to capture its behavior in plasma, with a partitioning coefficient capturing its behavior in the lung compartment. In this model, the time-invariant partition coefficient for relebactam was found to be 55%, based on free drug levels. These results support the clinical evaluation of relebactam with imipenem-cilastatin for the treatment of bacterial pneumonia.
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