Summary

The aim of this study was to investigate the pharmacokinetic and pharmacodynamic properties of irbesartan in renal hypertensive dogs under non-steady-state and steady-state conditions using pharmacokinetic-pharrnacodynamic(PK/PD) modeling. Drugs were administered intragastrically to renal hypertensive dogs, plasma drug concentration was determined by HPLC method and Pharmacologic effects, including SBP, DBP, dp/dtmax and LVSP, were measured simultaneously. AT II, Aldosterone (ALD) and Endothelin (ET) were also used as measurement of effect. The PK and PD data were quantitatively analyzed according to the PK/PD model theory. The pharmacokinetic profiles of irbesartan conformed to a two-compartment open model. There was hysteresis loops between effects and plasma concentrations under non-steady-state condition. The relationship between effects and effect compartment concentrations (C_e) could be represented by the Sigmoid-E_max model. The Hysteresis loops disappeared under steady-state condition with more rapidly attainment of maximum concentration and effect. There were certain difference of pharmacokinetic and pharmacodynamic properties between non-steady-state and steady-state condition.

Purpose

For optimizing the local, pulmonary targeting of inhaled medications, it is important to analyze the relationship between the physicochemical properties of small molecules and their absorption, retention and distribution in the various cell types of the airways and alveoli.

Methods

A computational, multiscale, cell-based model was constructed to facilitate analysis of pulmonary drug transport and distribution. The relationship between the physicochemical properties and pharmacokinetic profile of monobasic molecules was explored. Experimental absorption data of compounds with diverse structures were used to validate this model. Simulations were performed to evaluate the effect of active transport and organelle sequestration on the absorption kinetics of compounds.

Results

Relating the physicochemical properties to the pharmacokinetic profiles of small molecules reveals how the absorption half-life and distribution of compounds are expected to vary in different cell types and anatomical regions of the lung. Based on logP, pK_a and molecular radius, the absorption rate constants (K_a) calculated with the model were consistent with experimental measurements of pulmonary drug absorption.

Conclusions

The cell-based mechanistic model developed herein is an important step towards the rational design of local, lung-targeted medications, facilitating the design and interpretation of experiments aimed at optimizing drug transport properties in lung.

During pregnancy, a drug’s pharmacokinetics may be altered and hence anticipation of potential systemic exposure changes is highly desirable. Physiologically based pharmacokinetics (PBPK) models have recently been used to influence clinical trial design or to facilitate regulatory interactions. Ideally, whole-body PBPK models can be used to predict a drug’s systemic exposure in pregnant women based on major physiological changes which can impact drug clearance (i.e., in the kidney and liver) and distribution (i.e., adipose and fetoplacental unit). We described a simple and readily implementable multitissue/organ whole-body PBPK model with key pregnancy-related physiological parameters to characterize the PK of reference drugs (metformin, digoxin, midazolam, and emtricitabine) in pregnant women compared with the PK in nonpregnant or postpartum (PP) women. Physiological data related to changes in maternal body weight, tissue volume, cardiac output, renal function, blood flows, and cytochrome P450 activity were collected from the literature and incorporated into the structural PBPK model that describes HV or PP women PK data. Subsequently, the changes in exposure (area under the curve (AUC) and maximum concentration (C_max)) in pregnant women were simulated. Model-simulated PK profiles were overall in agreement with observed data. The prediction fold error for C_max and AUC ratio (pregnant vs. nonpregnant) was less than 1.3-fold, indicating that the pregnant PBPK model is useful. The utilization of this simplified model in drug development may aid in designing clinical studies to identify potential exposure changes in pregnant women a priori for compounds which are mainly eliminated renally or metabolized by CYP3A4.

ABSTRACT

Diosgenin (DSG), a well-known steroid sapogenin derived from Dioscorea nipponica Makino and Dioscorea zingiberensis Wright, has a variety of bioactivities. However, it shows low oral bioavailability due to poor aqueous solubility and strong hydrophobicity. The present study aimed to develop DSG nanocrystals to increase the dissolution and then improve the oral bioavailability and biopharmaceutical properties of DSG. DSG nanocrystals were prepared by the media milling method using a combination of pluronic F127 and sodium dodecyl sulfate as surface stabilizers. The physicochemical properties of the optimal DSG nanocrystals were characterized using their particle size distribution, morphology, differential scanning calorimetry, powder X-ray diffraction, Fourier transform infrared spectroscopy data, and solubility and dissolution test results. Pharmacokinetic studies of the DSG coarse suspension and its nanocrystals were performed in rats. The particle size and polydispersity index of DSG nanocrystals were 229.0 ± 3.7 nm and 0.163 ± 0.064, respectively. DSG retained its original crystalline state during the manufacturing process, and its chemical structure was not compromised by the nanonizing process. The dissolution rate of the freeze-dried DSG nanocrystals was significantly improved in comparison with the original DSG. The pharmacokinetic studies showed that the AUC_0–72h and C_max of DSG nanocrystals increased markedly (p < 0.01) in comparison with the DSG coarse suspension by about 2.55- and 2.01-fold, respectively. The use of optimized nanocrystals is a good and efficient strategy for oral administration of DSG due to the increased dissolution rate and oral bioavailability of DSG nanocrystals.

A simple, specific, sensitive, and precise high-performance liquid chromatography (HPLC) assay with UV detection has been developed for quantitative determination of fenozan acid in human blood plasma. Using this method, the pharmacokinetics of the new domestic preparation dibufelon (OOO Consortium-PIK, Russia) were investigated after a single peroral administration of an 800-mg dose in 12 healthy volunteers. It is established that the drug is rapidly absorbed from the GI tract into the systemic blood flow [C_max ,178 ± 29 ng/mL; T_max, 3.9 ± 0.5 h; AUC_0–∞, 1434 ± 269 (ng ∙ h)/mL; C_max/AUC_0–∞, 0.135 ± 0.011 L/h], rather well retained in humans (MRT, 8.6 ± 0.8 h; T₁/₂, 5.3 ± 0.8 h), and, despite a rapid total clearance (Cl_t,824 ± 167 L/h), penetrates well into organs and tissues (V_Z, 5590 ± 1204 L).

The ability to predict subcutaneous (SC) absorption rate and tissue distribution of therapeutic proteins (TPs) using a bottom-up approach is highly desirable early in the drug development process prior to clinical data being available. A whole-body physiologically based pharmacokinetic (PBPK) model, requiring only a few drug parameters, to predict plasma and interstitial fluid concentrations of TPs in humans after intravenous and subcutaneous dosing has been developed. Movement of TPs between vascular and interstitial spaces was described by considering both convection and diffusion processes using a 2-pore framework. The model was optimised using a variety of literature sources, such as tissue lymph/plasma concentration ratios in humans and animals, information on the percentage of dose absorbed following SC dosing via lymph in animals and data showing loss of radiolabelled IgG from the SC dosing site in humans. The resultant model was used to predict t_max and plasma concentration profiles for 12 TPs (molecular weight 8–150 kDa) following SC dosing. The predicted plasma concentration profiles were generally comparable to observed data. t_max was predicted within 3-fold of reported values, with one third of the predictions within 0.8–1.25-fold. There was no systematic bias in simulated C_max values, although a general trend for underprediction of t_max was observed. No clear trend between prediction accuracy of t_max and TP isoelectric point or molecular size was apparent. The mechanistic whole-body PBPK model described here can be applied to predict absorption rate of TPs into blood and movement into target tissues following SC dosing.

The problems of curve fitting and modeling in pharmacokinetics are discussed. A new nonlinear regression program FUNFIT, written for interactive time sharing, is presented which should be more reliable than programs based on the Gauss-Newton or other related gradient methods. The new program and the well-established program NONLIN were tested on two linear models using human plasma drug level data. FUNFIT found a substantially better solution than NONLIN in the majority of the cases.

Lumping is a common pragmatic approach aimed at the reduction of whole-body physiologically based pharmacokinetic (PBPK) model dimensionality and complexity. Incorrect lumping is equivalent to model misspecification with all the negative consequences to the subsequent model implementation. Proper lumping should guarantee that no useful information about the kinetics of the underlying processes is lost. To enforce this guarantee, formal standard lumping procedures and techniques need to be defined and implemented. This study examines the lumping process from a system theory point of view, which provides a formal basis for the derivation of principles and standard procedures of lumping. The lumping principle in PBPK modeling is defined as follows: Only tissues with identical model specification, and occupying identical positions in the system structure should be lumped together at each lumping iteration. In order to lump together parallel tissues, they should have similar or close time constants. In order to lump together serial tissues, they should equilibrate very rapidly with one another. The lumping procedure should include the following stages: (i) tissue specification conversion (when tissues with different model specifications are to be lumped together); (ii) classification of the tissues into classes with significantly different kinetics, according to the basic principle of lumping above; (iii) calculation of the parameters of the lumped compartments; (iv) simulation of the lumped system; (v) lumping of the experimental data; and (vi) verification of the lumped model. The use of the lumping principles and procedures to be adopted is illustrated with an example of a commonly implemented whole-body physiologically based pharmacokinetic model structure to characterize the pharmacokinetics of a homologous series of barbiturates in the rat.

The pharmacokinetics of chloramphenicol (CAP) and total chloramphenicol succinate (CAPS) were studied in eight hospitalized adult patients with normal renal and hepatic function receiving intravenous chloramphenicol sodium succinate therapy. The steady-state peak concentrations of CAP (8.4–26.0 μg/ml) occurred at an average of 18.0 min (range 5.4–40.2) after cessation of the chloramphenicol sodium succinate infusion. Unhydrolyzed CAPS prodrug, representing 26.0±7.0% of the dose, was recovered unchanged in the urine indicating that the bioavailability of CAP from a dose of intravenous chloramphenicol succinate is not complete. A pharmacokinetic model was developed for simultaneous fitting of CAP and CAPS plasma concentration data. Pharmacokinetic parameters determined by simultaneous fitting were: V, 0.81±0.18 liters/kg; t_1/2, 3.20 ±1.02 hr; CL_B, 3.21±1.27 ml/min/kg for chloramphenicol; and V, 0.38±0.13 liters/kg; t_1/2, 0.57±0.12hr; CL_B, 7.72±1.87 ml/min/kg for total chloramphenicol succinate.

Summary

The concentration-time profiles of Doxorubicin (DOXO) from day 0 to day 21 after i.v. infusion of 25 or 30 mg/m² doxorubicin HCl stealth liposomes (Caelyx^®) were investigated in 9 patients receiving combination polychemotherapy with cyclophosphamide, vinorelbine and prednisone. Peak serum concentrations occurred from 0.04 to 4.0 days after infusion (mean t_max=1.79±1.55 d) with a mean c_max of 4595±2849 ng/ml. A total amount of 12.84±2.47 mg liposomal DOXO in the plasma volume (Vp=2794+537 ml) could be estimated at t_max (=27% of the mean dose of 47.6 mg). Stealth liposomes were eliminated slowly from the blood with a mean t_1/2el of 1.9+0.5 days (MRT was 4.6+2.5 days).

AUC_last values ranged from 8070 to 33446 ng/ml^*d (mean 10987±9339 ng/ml^*d). The low plasma clearance (Cl_tot=4681±2835 ml/day) and the small volume of distribution (Vz=11.7±6.3 l) suggested that stealth-liposomes were stable in the blood at least for 14 days. Polychemotherapy with Hyper-CCVP schedule did not alter the stability of stealth liposomes, but peak levels of DOXO seemed to be somewhat lower compared to regression analysis of literature data (c_max versus dosage range from 20 to 60 mg/m²). Due to c_last occurring between day 12 to 18, no indices for an accumulation of the drug in the blood could be found, when liposomes were given every four weeks.