Physiologically based pharmacokinetic models, populated with drug‐metabolizing enzyme and transporter (DMET) abundance, can be used to predict the impact of hepatic impairment (HI) on the ...pharmacokinetics (PK) of drugs. To increase confidence in the predictive power of such models, they must be validated by comparing the predicted and observed PK of drugs in HI obtained by phenotyping (or probe drug) studies. Therefore, we first predicted the effect of all stages of HI (mild to severe) on the PK of drugs primarily metabolized by cytochrome P450 (CYP) 3A enzymes using the default HI module of Simcyp Version 21, populated with hepatic and intestinal CYP3A abundance data. Then, we validated the predictions using CYP3A probe drug phenotyping studies conducted in HI. Seven CYP3A substrates, metabolized primarily via CYP3A (fraction metabolized, 0.7–0.95), with low to high hepatic availability, were studied. For all stages of HI, the predicted PK parameters of drugs were within twofold of the observed data. This successful validation increases confidence in using the DMET abundance data in HI to predict the changes in the PK of drugs cleared by DMET for which phenotyping studies in HI are not available or cannot be conducted. In addition, using CYP3A drugs as an example, through simulations, we identified the salient PK factors that drive the major changes in exposure (area under the plasma concentration–time profile curve) to drugs in HI. This theoretical framework can be applied to any drug and DMET to quickly determine the likely magnitude of change in drug PK due to HI.
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32.
Pharmacometrics in pregnancy: An unmet need Ke, Alice Ban; Rostami-Hodjegan, Amin; Zhao, Ping ...
Annual review of pharmacology and toxicology,
01/2014, Volume:
54
Journal Article
Peer reviewed
Open access
Pregnant women and their fetuses are orphan populations with respect to the safety and efficacy of drugs. Physiological and absorption, distribution, metabolism, and excretion (ADME) changes during ...pregnancy can significantly affect drug pharmacokinetics (PK) and may necessitate dose adjustment. Here, the specific aspects related to the design, execution, and analysis of clinical studies in pregnant women are discussed, underlining the unmet need for top-down pharmacometrics analyses and bottom-up modeling approaches. The modeling tools that support data analysis for the pregnancy population are reviewed, with a focus on physiologically based pharmacokinetics (PBPK) and population pharmacokinetics (POP-PK). By integrating physiological data, preclinical data, and clinical data (e.g., via POP-PK) to quantify anticipated changes in the PK of drugs during pregnancy, the PBPK approach allows extrapolation beyond the previously studied model drugs to other drugs with well-characterized ADME characteristics. Such a systems pharmacology approach can identify drugs whose PK may be altered during pregnancy, guide rational PK study design, and support dose adjustment for pregnant women.
Pregnancy can significantly change the pharmacokinetics of drugs, including those renally secreted by organic anion transporters (OATs). Quantifying these changes in pregnant women is logistically ...and ethically challenging. Hence, predicting the in vivo plasma renal secretory clearance (CL
) and renal CL (CL
) of OAT drugs in pregnancy is important to design correct dosing regimens of OAT drugs. Here, we first quantified the fold-change in renal OAT activity in pregnant versus nonpregnant individual using available selective OAT probe drug CL
data (training dataset; OAT1: tenofovir, OAT2: acyclovir, OAT3: oseltamivir carboxylate). The fold-change in OAT1 activity during the 2
and 3
trimester was 2.9 and 1.0 compared with nonpregnant individual, respectively. OAT2 activity increased 3.1-fold during the 3
trimester. OAT3 activity increased 2.2, 1.7 and 1.3-fold during the 1
, 2
, and 3
trimester, respectively. Based on these data, we predicted the CL
, CL
and total clearance ((CL
) of drugs in pregnancy, which are secreted by multiple OATs (verification dataset; amoxicillin, pravastatin, cefazolin and ketorolac,
-ketorolac,
-ketorolac). Then, the predicted clearances (CLs) were compared with the observed values. The predicted/observed CL
, CL
, and CL
of drugs in pregnancy of all verification drugs were within 0.80-1.25 fold except for CL
of amoxicillin in the 3
trimester (0.76-fold) and cefazolin in the 2
trimester (1.27-fold). Overall, we successfully predicted the CL
, CL
, and CL
of drugs in pregnancy that are renally secreted by multiple OATs. This approach could be used in the future to adjust dosing regimens of renally secreted OAT drugs which are administered to pregnant women. SIGNIFICANCE STATEMENT: To the authors' knowledge, this is the first report to successfully predict renal secretory clearance and renal clearance of multiple OAT substrate drugs during pregnancy. The data presented here could be used in the future to adjust dosing regimens of renally secreted OAT drugs in pregnancy. In addition, the mechanistic approach used here could be extended to drugs transported by other renal transporters.
Pregnant women are frequently prescribed drugs to treat chronic diseases such as human immunodeficiency virus infection, but little is known about the benefits and risks of these drugs to the fetus ...that are driven by fetal drug exposure. The latter can be estimated by fetal-to-maternal unbound plasma concentration at steady state (K
). For drugs that are substrates of placental efflux transporters i.e., P-glycoprotein (P-gp) or breast cancer resistance protein (BCRP), K
is expected to be <1. Here, we estimated the
K
of selective P-gp and BCRP substrate drugs by maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling of umbilical vein (UV) plasma and maternal plasma (MP) concentrations obtained simultaneously at term from multiple maternal-fetal dyads. To do so, three drugs were selected: nelfinavir (P-gp substrate), efavirenz (BCRP substrate), and imatinib (P-gp/BCRP substrate). An m-f-PBPK model for each drug was developed and validated for the nonpregnant population and pregnant women using the Simcyp simulator (v20). Then, after incorporating placental passive diffusion clearance, the
K
of the drug was estimated by adjusting the placental efflux clearance until the predicted UV/MP values best matched the observed data (K
) of nelfinavir = 0.41, efavirenz = 0.39, and imatinib = 0.35. Furthermore, K
of nelfinavir and efavirenz at gestational weeks (GWs) 25 and 15 were predicted to be 0.34 and 0.23 (GW25) and 0.33 and 0.27 (GW15). These K
values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated
K
values can be predicted from in vitro studies. SIGNIFICANCE STATEMENT: The
fetal-to-maternal unbound steady-state plasma concentration ratio (K
) of nelfinavir P-glycoprotein (P-gp) substrate, efavirenz breast cancer resistance protein (BCRP) substrate, and imatinib (P-gp and BCRP substrate) was successfully estimated using maternal-fetal physiologically based pharmacokinetic (m-f-PBPK) modeling. These K
values can be used to adjust dosing regimens of these drugs to optimize maternal-fetal drug therapy throughout pregnancy, to assess fetal benefits and risks of these dosing regimens, and to determine if these estimated
K
values can be predicted from in vitro studies.
Concentrative nucleoside transporters (CNTs) are active nucleoside influx systems, but their in vivo roles are poorly defined. By generating CNT1 knockout (KO) mice, here we identify a role of CNT1 ...in the renal reabsorption of nucleosides. Deletion of CNT1 in mice increases the urinary excretion of endogenous pyrimidine nucleosides with compensatory alterations in purine nucleoside metabolism. In addition, CNT1 KO mice exhibits high urinary excretion of the nucleoside analog gemcitabine (dFdC), which results in poor tumor growth control in CNT1 KO mice harboring syngeneic pancreatic tumors. Interestingly, increasing the dFdC dose to attain an area under the concentration-time curve level equivalent to that achieved by wild-type (WT) mice rescues antitumor efficacy. The findings provide new insights into how CNT1 regulates reabsorption of endogenous and synthetic nucleosides in murine kidneys and suggest that the functional status of CNTs may account for the optimal action of pyrimidine nucleoside analog therapeutics in humans.
Cannabidiol (CBD) is available as a prescription oral drug that is indicated for the treatment of some types of epilepsy in children and adults. CBD is also available over-the-counter and is used to ...self-treat a variety of other ailments, including pain, anxiety, and insomnia. Accordingly, CBD may be consumed with other medications, resulting in possible CBD-drug interactions. Such interactions can be predicted in healthy and hepatically-impaired (HI) adults and in children through physiologically based pharmacokinetic (PBPK) modeling and simulation. These PBPK models must be populated with CBD-specific parameters, including the enzymes that metabolize CBD in adults. In vitro reaction phenotyping experiments showed that UDP-glucuronosyltransferases (UGTs, 80%), particularly UGT2B7 (64%), were the major contributors to CBD metabolism in adult human liver microsomes. Among the cytochrome P450s (CYPs) tested, CYP2C19 (5.7%) and CYP3A (6.5%) were the major CYPs responsible for CBD metabolism. Using these and other physicochemical parameters, a CBD PBPK model was developed and validated for healthy adults. This model was then extended to predict CBD systemic exposure in HI adults and children. Our PBPK model successfully predicted CBD systemic exposure in both populations within 0.5- to 2-fold of the observed values. In conclusion, we developed and validated a PBPK model to predict CBD systemic exposure in healthy and HI adults and children. This model can be used to predict CBD-drug or CBD-drug-disease interactions in these populations. SIGNIFICANCE STATEMENT: Our PBPK model successfully predicted CBD systemic exposure in healthy and hepatically-impaired adults, as well as children with epilepsy. This model could be used in the future to predict CBD-drug or CBD-drug-disease interactions in these special populations.
Tissue drug concentrations determine the efficacy and toxicity of drugs. When a drug is the substrate of transporters that are present at the blood:tissue barrier, the steady‐state unbound tissue ...drug concentrations cannot be predicted from their corresponding plasma concentrations. To accurately predict transporter‐modulated tissue drug concentrations, all clearances (CLs) mediating the drug's entry and exit (including metabolism) from the tissue must be accurately predicted. Because primary cells of most tissues are not available, we have proposed an alternative approach to predict such CLs, that is the use of transporter‐expressing cells/vesicles (TECs/TEVs) and relative expression factor (REF). The REF represents the abundance of the relevant transporters in the tissue vs. in the TECs/TEVs. Here, we determined the transporter‐based intrinsic CL of glyburide (GLB) and pitavastatin (PTV) in OATP1B1, OATP1B3, OATP2B1, and NTCP‐expressing cells and MRP3‐, BCRP‐, P‐gp‐, and MRP2‐expressing vesicles and scaled these CLs to in vivo using REF. These predictions fell within a priori set twofold range of the hepatobiliary CLs of GLB and PTV, estimated from their hepatic positron emission tomography imaging data: 272.3 and 607.8 mL/min for in vivo hepatic sinusoidal uptake CL, 47.8 and 17.4 mL/min for sinusoidal efflux CL, and 0 and 4.20 mL/min for biliary efflux CL, respectively. Moreover, their predicted hepatic concentrations (area under the hepatic concentration‐time curve (AUC) and maximum plasma concentration (Cmax)), fell within twofold of their mean observed data. These data, together with our previous findings, confirm that the REF approach can successfully predict transporter‐based drug CLs and tissue concentrations to enhance success in drug development.
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Oral inhalation (OI) of drugs is the route of choice to treat respiratory diseases or for recreational drug use (e.g., cannabis). After OI, the drug is deposited in and systemically absorbed from ...various regions of the respiratory tract. Measuring regional respiratory tissue drug concentrations at the site of action is important for evaluating the efficacy and safety of orally inhaled drugs (OIDs). Because such a measurement is routinely not possible in humans, the only alternative is to predict these concentrations, for example by physiologically based pharmacokinetic (PBPK) modeling. Therefore, we developed an OI-PBPK model to integrate the interplay between regional respiratory drug deposition and systemic absorption to predict regional respiratory tissue and systemic drug concentrations. We validated our OI-PBPK model by comparing the simulated and observed plasma concentration-time profiles of two OIDs, morphine and nicotine. Furthermore, we performed sensitivity analyses to quantitatively demonstrate the impact of key parameters on the extent and pattern of regional respiratory drug deposition, absorption, and the resulting regional respiratory tissue and systemic plasma concentrations. Our OI-PBPK model can be applied to predict regional respiratory tissue and systemic drug concentrations to optimize OID formulations, delivery systems, and dosing regimens. Furthermore, our model could be used to establish the bioequivalence of generic OIDs for which systemic plasma concentrations are not measurable or are not a good surrogate of the respiratory tissue drug concentrations. SIGNIFICANCE STATEMENT: Our OI-PBPK model is the first comprehensive model to predict regional respiratory deposition, as well as systemic and regional tissue concentrations of OIDs, especially at the drug's site of action, which is difficult to measure in humans. This model will help optimize OID formulations, delivery systems, dosing regimens, and bioequivalence assessment of generic OID. Furthermore, this model can be linked with organs-on-chips, pharmacodynamic and quantitative systems pharmacology models to predict and evaluate the safety and efficacy of OID.
To predict the impact of liver cirrhosis on hepatic drug clearance using physiologically based pharmacokinetic (PBPK) modeling, we compared the protein abundance of various phase 1 and phase 2 ...drug-metabolizing enzymes (DMEs) in S9 fractions of alcoholic (
= 27) or hepatitis C (HCV,
= 30) cirrhotic versus noncirrhotic (control) livers (
= 25). The S9 total protein content was significantly lower in alcoholic or HCV cirrhotic versus control livers (i.e., 38.3 ± 8.3, 32.3 ± 12.8, vs. 51.1 ± 20.7 mg/g liver, respectively). In general, alcoholic cirrhosis was associated with a larger decrease in the DME abundance than HCV cirrhosis; however, only the abundance of UGT1A4, alcohol dehydrogenase (ADH)1A, and ADH1B was significantly lower in alcoholic versus HCV cirrhotic livers. When normalized to per gram of tissue, the abundance of nine DMEs (UGT1A6, UGT1A4, CYP3A4, UGT2B7, CYP1A2, ADH1A, ADH1B, aldehyde oxidase (AOX)1, and carboxylesterase (CES)1) in alcoholic cirrhosis and five DMEs (UGT1A6, UGT1A4, CYP3A4, UGT2B7, and CYP1A2) in HCV cirrhosis was <25% of that in control livers. The abundance of most DMEs in cirrhotic livers was 25% to 50% of control livers. CES2 abundance was not affected by cirrhosis. Integration of UGT2B7 abundance in cirrhotic livers into the liver cirrhosis (Child Pugh C) model of Simcyp improved the prediction of zidovudine and morphine PK in subjects with Child Pugh C liver cirrhosis. These data demonstrate that protein abundance data, combined with PBPK modeling and simulation, can be a powerful tool to predict drug disposition in special populations.
Using positron emission tomography imaging, we determined the hepatic concentrations and hepatobiliary transport of 11Crosuvastatin (RSV; i.v. injection) in the absence (n = 6) and presence (n = 4 of ...6) of cyclosporin A (CsA; i.v. infusion) following a therapeutic dose of unlabeled RSV (5 mg, p.o.) in healthy human volunteers. The sinusoidal uptake, sinusoidal efflux, and biliary efflux clearance (CL; mL/minute) of 11CRSV, estimated through compartment modeling were 1,205.6 ± 384.8, 16.2 ± 11.2, and 5.1 ± 1.8, respectively (n = 6). CsA (blood concentration: 2.77 ± 0.24 μM), an organic‐anion‐transporting polypeptide, Na+‐taurocholate cotransporting polypeptide, and breast cancer resistance protein inhibitor increased 11CRSV systemic blood exposure (45%; P < 0.05), reduced its biliary efflux CL (52%; P < 0.05) and hepatic uptake (25%; P > 0.05) but did not affect its distribution into the kidneys. CsA increased plasma concentrations of coproporphyrin I and III and total bilirubin by 297 ± 69%, 384 ± 102%, and 81 ± 39%, respectively (P < 0.05). These data can be used in the future to verify predictions of hepatic concentrations and hepatobiliary transport of RSV.
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