The Interplay of Permeability, Metabolism, Transporters, and Dosing in Determining the Dynamics of the Tissue/Plasma Partition Coefficient and Volume of Distribution-A Theoretical Investigation Using Permeability-Limited, Physiologically Based Pharmacokinetic Modeling.

A permeability-limited physiologically based pharmacokinetic (PBPK) model featuring four subcompartments (corresponding to the intracellular and extracellular water of the tissue, the residual plasma, and blood cells) for each tissue has been developed in MATLAB/SimBiology and applied to various what-if scenario simulations. This model allowed us to explore the complex interplay of passive permeability, metabolism in tissue or residual blood, active uptake or efflux transporters, and different dosing routes (intravenous (IV) or oral (PO)) in determining the dynamics of the tissue/plasma partition coefficient (Kp) and volume of distribution (Vd) within a realistic pseudo-steady state. Based on the modeling exercise, the permeability, metabolism, and transporters demonstrated significant effects on the dynamics of the Kp and Vd for IV bolus administration and PO fast absorption, but these effects were not as pronounced for IV infusion or PO slow absorption. Especially for low-permeability compounds, uptake transporters were found to increase both the Kp and Vd at the pseudo-steady state (Vdss), while efflux transporters had the opposite effect of decreasing the Kp and Vdss. For IV bolus administration and PO fast absorption, increasing tissue metabolism was predicted to elevate the Kp and Vdss, which contrasted with the traditional derivation from the steady-state perfusion-limited PBPK model. Moreover, metabolism in the residual blood had more impact on the Kp and Vdss compared to metabolism in tissue. Due to its ability to offer a more realistic description of tissue dynamics, the permeability-limited PBPK model is expected to gain broader acceptance in describing clinical PK and observed Kp and Vdss, even for certain small molecules like cyclosporine, which are currently treated as perfusion-limited in commercial PBPK platforms.

Physiologically Based Pharmacokinetic Modeling and Simulation of Mavacamten Exposure with Drug-Drug Interactions from CYP Inducers and Inhibitors by CYP2C19 Phenotype.

Mavacamten is a first-in-class, oral, selective, allosteric, reversible cardiac myosin inhibitor approved by the US Food and Drug Administration for the treatment of adults with symptomatic New York Heart Association functional class II-III obstructive hypertrophic cardiomyopathy. Mavacamten is metabolized in the liver, predominantly via cytochrome P450 (CYP) enzymes CYP2C19 (74%), CYP3A4 (18%), and CYP2C9 (8%). A physiologically-based pharmacokinetic (PBPK) model was developed using Simcyp version 19 (Certara, Princeton, NJ). Following model verification, the PBPK model was used to explore the effects of strong CYP3A4 and CYP2C19 inducers, and strong, moderate, and weak CYP2C19 and CYP3A4 inhibitors on mavacamten pharmacokinetics (PK) in a healthy population, with the effect of CYP2C19 phenotype predicted for poor, intermediate, normal, and ultrarapid metabolizers. The PBPK model met the acceptance criteria for all verification simulations (> 80% of model-predicted PK parameters within 2-fold of those observed clinically). A weak induction effect was predicted when mavacamten was administered with a strong CYP3A4 inducer in poor metabolizers. Moderate reductions in mavacamten exposure were predicted with a strong CYP2C19/CYP3A4 inducer in all CYP2C19 phenotypes. Except for the effect of strong CYP2C19 inhibitors on ultrarapid metabolizers, steady-state area under plasma concentration-time curve and maximum plasma concentration values were weakly affected (< 2-fold) or not affected (< 1.25-fold), regardless of CYP2C19 phenotype. In conclusion, a fit-for-purpose PBPK model was developed and verified, which accurately predicted the available clinical data and was used to simulate the potential impact of CYP induction and inhibition on mavacamten PKs, stratified by CYP2C19 phenotype.

Drug-Drug Interaction Potential of Mavacamten with Oral Contraceptives: Results from a Clinical Pharmacokinetic Study and a Physiologically Based Pharmacokinetic Model.

Mavacamten is a potential inducer of cytochrome P450 (CYP) 3A4 and, as such, could reduce the exposure of the active components of oral contraceptives, ethinyl estradiol (EE) and norethindrone (NOR), where CYP3A4 is involved in metabolism. This study assessed if repeat doses of mavacamten led to a drug-drug interaction with EE and/or NOR. This was an open-label study in healthy women. In Period 1, participants received 35 mcg of EE and 1 mg of NOR. In Period 2, participants received oral loading doses of mavacamten 25 mg on Days 1-2, 15 mg/day on Days 3-17, and 35 mcg of EE and 1 mg of NOR on Day 15. Plasma concentrations of mavacamten, EE, and NOR were obtained before dosing and up to 72 hours after dosing. For EE only, a physiologically based pharmacokinetic model was used to simulate mavacamten-mediated CYP3A4 induction with EE for various CYP2C19 phenotypes. In total, 13 women were enrolled (mean age, 38.9 [standard deviation, 9.65] years). After mavacamten administration, modest increases in area under the concentration-time curves were observed for both EE and NOR. The maximum concentrations and half-lives for EE and NOR were not affected by coadministration with mavacamten. Criteria for bioequivalence were met or nearly met for EE and NOR exposure with geometric mean ratios between 0.8 and 1.25. All adverse events were mild. The physiologically based pharmacokinetic model predicted a less than 15% decrease in EE exposure across CYP2C19 phenotypes. Coadministration of mavacamten at a therapeutically relevant dose with EE and NOR did not decrease the exposure to either EE or NOR to a level that may lead to reduced effectiveness.

A perspective on the current use of the phase distribution model for predicting milk-to-plasma drug concentration ratio.

The phase distribution model, proposed by Atkinson and Begg in 1990, has been widely used for predicting breastmilk-to-plasma drug concentration ratio. However, misrepresentations of the equations have been noted in recent publications. In this perspective, we revisit the derivation of the equations and provide an R/Shiny interface for the model with a view to helping scientists in this field acquire in-depth understanding of the theoretical background and implementation of the model.

Performance Verification of CYP2C19 Enzyme Abundance Polymorphism Settings within the Simcyp Simulator v21.

Physiologically based pharmacokinetic (PBPK) modeling has a number of applications, including assessing drug−drug interactions (DDIs) in polymorphic populations, and should be iteratively refined as science progresses. The Simcyp Simulator is annually updated and version 21 included updates to hepatic and intestinal CYP2C19 enzyme abundance, including addition of intermediate and rapid metabolizer phenotypes and changes to the ultra-rapid metabolizer enzyme abundance, with implications for population clearance and DDI predictions. This work details verification of the updates with sensitive CYP2C19 substrates, omeprazole and lansoprazole, using available clinical data from literature. Multiple assessments were performed, including recovery of areas under the concentration-time curve (AUC) and Cmax from compiled datasets for each drug, recovery of victim DDI ratios with CYP2C19 and/or CYP3A4 inhibition and recovery of relative exposure between phenotypes. Simulated data were within respective acceptance criteria for >80% of omeprazole AUC values, >70% of lansoprazole AUC and Cmax, >60% of AUC and Cmax DDI ratios and >80% of exposure ratios between different phenotypes. Recovery of omeprazole Cmax was lower (>50−70% within 2-fold) and possibly attributed to the variety of formulations used in the clinical dataset. Overall, the results demonstrated that the updated data used to parameterize CYP2C19 phenotypes reasonably described the pharmacokinetics of omeprazole and lansoprazole in genotyped or phenotyped individuals.

Crosstalk of physiological pH and chemical pKa under the umbrella of physiologically based pharmacokinetic modeling of drug absorption, distribution, metabolism, excretion, and toxicity.

Introduction: Physiological pH and chemical pKa are two sides of the same coin in defining the ionization of a drug in the human body. The Henderson-Hasselbalch equation and pH-partition hypothesis form the theoretical base to define the impact of pH-pKa crosstalk on drug ionization and thence its absorption, distribution, metabolism, excretion, and toxicity (ADMET).Areas covered: Human physiological pH is not constant, but a diverse, dynamic state regulated by various biological mechanisms, while the chemical pKa is generally a constant defining the acidic dissociation of the drug at various environmental pH. Works on pH-pKa crosstalk are scattered in the literature, despite its significant contributions to drug pharmacokinetics, pharmacodynamics, safety, and toxicity. In particular, its impacts on drug ADMET have not been effectively linked to the physiologically based pharmacokinetic (PBPK) modeling and simulation, a powerful tool increasingly used in model-informed drug development (MIDD).Expert opinion: Lacking a full consideration of the interactions of physiological pH and chemical pKa in a PBPK model limits scientists' capability in mechanistically describing the drug ADMET. This mini-review compiled literature knowledge on pH-pKa crosstalk and its impacts on drug ADMET, from the viewpoint of PBPK modeling, to pave the way to a systematic incorporation of pH-pKa crosstalk into PBPK modeling and simulation.

Targeted protein degradation in vivo with Proteolysis Targeting Chimeras: Current status and future considerations.

Proteolysis Targeting Chimeras (PROTACs) are a rapidly expanding new therapeutic modality inducing selective protein degradation and offering the potential of a differentiated pharmacological profile across multiple therapeutic areas. As the repertoire of protein targets and E3 ligases available for incorporation into PROTACs continues to grow, understanding the drug- and system-dependent parameters for PROTACs will be critical for achieving tissue/cell specific pharmacology. The review discusses the current knowledge and future direction of in vivo PROTAC study evaluation. The importance of establishing the quantitative relationship between loss of protein target and biological function in vivo, coupled with building mechanistic PK/PD and ultimately PBPK/PD models, is emphasised with the aim to aid translation from preclinical to clinical space.

Development of a Novel Maternal-Fetal Physiologically Based Pharmacokinetic Model I: Insights into Factors that Determine Fetal Drug Exposure through Simulations and Sensitivity Analyses.

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.

Development of a permeability-limited model of the human brain and cerebrospinal fluid (CSF) to integrate known physiological and biological knowledge: Estimating time varying CSF drug concentrations and their variability using in vitro data.

A 4-compartment permeability-limited brain (4Brain) model consisting of brain blood, brain mass, cranial and spinal cerebrospinal fluid (CSF) compartments has been developed and incorporated into a whole body physiologically-based pharmacokinetic (PBPK) model within the Simcyp Simulator. The model assumptions, structure, governing equations and system parameters are described. The model in particular considers the anatomy and physiology of the brain and CSF, including CSF secretion, circulation and absorption, as well as the function of various efflux and uptake transporters existing on the blood-brain barrier (BBB) and blood-CSF barrier (BCSFB), together with the known parameter variability. The model performance was verified using in vitro data and clinical observations for paracetamol and phenytoin. The simulated paracetamol spinal CSF concentration is comparable with clinical lumbar CSF data for both intravenous and oral doses. Phenytoin CSF concentration-time profiles in epileptic patients were simulated after accounting for disease-induced over-expression of efflux transporters within the BBB. Various 'what-if' scenarios, involving variation of specific drug and system parameters of the model, demonstrated that the 4Brain model is able to simulate the possible impact of transporter-mediated drug-drug interactions, the lumbar puncture process and the age-dependent change in the CSF turnover rate on the local PK within the brain.

Predicting nonlinear pharmacokinetics of omeprazole enantiomers and racemic drug using physiologically based pharmacokinetic modeling and simulation: application to predict drug/genetic interactions.

PURPOSE: The objective of this study is to develop a physiologically-based pharmacokinetic (PBPK) model for each omeprazole enantiomer that accounts for nonlinear PK of the two enantiomers as well as omeprazole racemic drug. METHODS: By integrating in vitro, in silico and human PK data, we first developed PBPK models for each enantiomer. Simulation of racemic omeprazole PK was accomplished by combining enantiomer models that allow mutual drug interactions to occur. RESULTS: The established PBPK models for the first time satisfactorily predicted the nonlinear PK of esomeprazole, R-omeprazole and the racemic drug. The modeling exercises revealed that the strong time-dependent inhibition of CYP2C19 by esomeprazole greatly altered the R-omeprazole PK following administration of racemic omeprazole as in contrast to R-omeprazole given alone. When PBPK models incorporated both autoinhibition of each enantiomer and mutual interactions, the ratios between predicted and observed AUC following single and multiple dosing of omeprazole were 0.97 and 0.94, respectively. CONCLUSIONS: PBPK models of omeprazole enantiomers and racemic drug were developed. These models can be utilized to assess CYP2C19-mediated drug and genetic interaction potential for omeprazole and esomeprazole.

A pregnancy physiologically based pharmacokinetic (p-PBPK) model for disposition of drugs metabolized by CYP1A2, CYP2D6 and CYP3A4.

AIMS: Pregnant women are usually not part of the traditional drug development programme. Pregnancy is associated with major biological and physiological changes that alter the pharmacokinetics (PK) of drugs. Prediction of the changes to drug exposure in this group of patients may help to prevent under- or overtreatment. We have used a pregnancy physiologically based pharmacokinetic (p-PBPK) model to assess the likely impact of pregnancy on three model compounds, namely caffeine, metoprolol and midazolam, based on the knowledge of their disposition in nonpregnant women and information from in vitro studies. METHODS: A perfusion-limited form of a 13-compartment full-PBPK model (Simcyp® Simulator) was used for the nonpregnant women, and this was extended to the pregnant state by applying known changes to all model components (including the gestational related activity of specific cytochrome P450 enzymes) and through the addition of an extra compartment to represent the fetoplacental unit. The uterus and the mammary glands were grouped into the muscle compartment. The model was implemented in Matlab Simulink and validated using clinical observations. RESULTS: The p-PBPK model predicted the PK changes of three model compounds (namely caffeine, metoprolol and midazolam) for CYP1A2, CYP2D6 and CYP3A4 during pregnancy within twofold of observed values. The changes during the third trimester were predicted to be a 100% increase, a 30% decrease and a 35% decrease in the exposure of caffeine, metoprolol and midazolam, respectively, compared with the nonpregnant women. CONCLUSIONS: In the absence of clinical data, the in silico prediction of PK behaviour during pregnancy can provide a valuable aid to dose adjustment in pregnant women. The performance of the model for drugs metabolized by a single enzyme to different degrees (high and low extraction) and for drugs that are eliminated by several different routes warrants further study.

A mathematical model of brain glucose homeostasis.

BACKGROUND: The physiological fact that a stable level of brain glucose is more important than that of blood glucose suggests that the ultimate goal of the glucose-insulin-glucagon (GIG) regulatory system may be homeostasis of glucose concentration in the brain rather than in the circulation. METHODS: In order to demonstrate the relationship between brain glucose homeostasis and blood hyperglycemia in diabetes, a brain-oriented mathematical model was developed by considering the brain as the controlled object while the remaining body as the actuator. After approximating the body compartmentally, the concentration dynamics of glucose, as well as those of insulin and glucagon, are described in each compartment. The brain-endocrine crosstalk, which regulates blood glucose level for brain glucose homeostasis together with the peripheral interactions among glucose, insulin and glucagon, is modeled as a proportional feedback control of brain glucose. Correlated to the brain, long-term effects of psychological stress and effects of blood-brain-barrier (BBB) adaptation to dysglycemia on the generation of hyperglycemia are also taken into account in the model. RESULTS: It is shown that simulation profiles obtained from the model are qualitatively or partially quantitatively consistent with clinical data, concerning the GIG regulatory system responses to bolus glucose, stepwise and continuous glucose infusion. Simulations also revealed that both stress and BBB adaptation contribute to the generation of hyperglycemia. CONCLUSION: Simulations of the model of a healthy person under long-term severe stress demonstrated that feedback control of brain glucose concentration results in elevation of blood glucose level. In this paper, we try to suggest that hyperglycemia in diabetes may be a normal outcome of brain glucose homeostasis.

A mathematical model of respiratory and biothermal dynamics in brain hypothermia treatment.

Brain hypothermia treatment (BHT) requires proper mechanical ventilation and therapeutic cooling. The cooling strategy for BHT has been mainly discussed in the literature while little information is available on the respiratory management. We first developed a mathematical model that integrates the respiratory and biothermal dynamics to discuss the simultaneous managements of mechanical ventilation and therapeutic cooling. The effect of temperature on the linear approximations of hemoglobin-oxygen dissociation, together with temperature dependency of metabolism, is introduced during modeling to combine the respiratory system with the biothermal system. By comparing its transient behavior with published data, the model is verified qualitatively and then quantitatively. Second, model-based simulation of the current respiratory management in BHT suggests reduction of minute ventilation in reference to cooled brain temperature to stabilize the states of blood and brain oxygenation. Lastly, the relationship between cooling temperature and minute ventilation is approximated by a linear first-order transfer function of static gain 0.61min(-1) degrees C(-1) and time constant 8.9 h, which is used to develop a feedforward control to tune the mechanical ventilator in concert with temperature regulation of the cooling blanket. Discussion of the model encourages further studies that provide direct evidence from clinical experiments.

Simulation of propofol anaesthesia for intracranial decompression using brain hypothermia treatment.

BACKGROUND: Although propofol is commonly used for general anaesthesia of normothermic patients in clinical practice, little information is available in the literature regarding the use of propofol anaesthesia for intracranial decompression using brain hypothermia treatment. A novel propofol anaesthesia scheme is proposed that should promote such clinical application and improve understanding of the principles of using propofol anaesthesia for hypothermic intracranial decompression. METHODS: Theoretical analysis was carried out using a previously-developed integrative model of the thermoregulatory, hemodynamic and pharmacokinetic subsystems. Propofol kinetics is described using a framework similar to that of this model and combined with the thermoregulation subsystem through the pharmacodynamic relationship between the blood propofol concentration and the thermoregulatory threshold. A propofol anaesthesia scheme for hypothermic intracranial decompression was simulated using the integrative model. RESULTS: Compared to the empirical anaesthesia scheme, the proposed anaesthesia scheme can reduce the required propofol dosage by more than 18%. CONCLUSION: The integrative model of the thermoregulatory, hemodynamic and pharmacokinetic subsystems is effective in analyzing the use of propofol anaesthesia for hypothermic intracranial decompression. This propofol infusion scheme appears to be more appropriate for clinical application than the empirical one.

An integrated model of thermodynamic-hemodynamic-pharmacokinetic system and its application on decoupling control of intracranial temperature and pressure in brain hypothermia treatment.

Brain hypothermia treatment (BHT) is an intensive care characterized by simultaneous managements of various vital signs, such as intracranial temperature (ICT) and pressure (ICP), of the severe neuropatient. Medical treatments including therapeutic ambient cooling and diuresis are separately carried out based on the experience of the medical staff involved in the clinical management of various pathophysiological processes, such as thermodynamics, hemodynamics and pharmacokinetics. However, no special attention has been paid to the interactions among these subsystems in therapeutic hypothermia because of the lack of theoretical knowledge. Therefore, quantitative analyses using an integrated model of various physiological processes and their interactions are of pressing need. In the present paper, we propose a general compartmental model to describe the pathophysiological processes of the three aforementioned dynamics, on account of the dynamical analogy of temperature, pressure and concentration. The model is verified by the agreement of model-based simulation results with clinical evidence. Based on responses of the integrated model to various stimuli, a transfer function matrix is identified to linearly approximate the characteristic interrelationships between medical treatments (ambient cooling and diuresis) and the vital signs (ICT and ICP). Then a controller that decouples ambient cooling and diuresis is proposed for efficient management of ICT and ICP, enhancement of hypothermic decompression and reduction of diuretic dosage. Decoupling control simulation indicates that ICT and ICP of the integrated model, representing a patient under BHT, can be simultaneously regulated by a single PID controller for ambient cooling and another for diuresis. The proposed decoupler effectively establishes hypothermic decompression, reduces the dosage of diuretic and improves ICP management. Theoretical analyses of the integrated model and decoupling control of ICT and ICP provide insights into the intensive care of various pathophysiological processes in patients undergoing BHT.

A mathematical model of intracranial pressure dynamics for brain hypothermia treatment.

Brain hypothermia treatment is used as a neuroprotectant to decompress the elevated intracranial pressure (ICP) in acute neuropatients. However, a quantitative relationship between decompression and brain hypothermia is still unclear, this makes medical treatment difficult and ineffective. The objective of this paper is to develop a general mathematical model integrating hemodynamics and biothermal dynamics to enable a quantitative prediction of transient responses of elevated ICP to ambient cooling temperature. The model consists of a lumped-parameter compartmental representation of the body, and is based on two mechanisms of temperature dependence encountered in hypothermia, i.e. the van't Hoff's effect of metabolism and the Arrhenius' effect of capillary filtration. Model parameters are taken from the literature. The model is verified by comparing the simulation results to population-averaged data and clinical evidence of brain hypothermia treatment. It is possible to assign special model inputs to mimic clinical maneuvers, and to adjust model parameters to simulate pathophysiological states of intracranial hypertension. Characteristics of elevated ICP are quantitatively estimated by using linear approximation of step response with respect to ambient cooling temperature. Gain of about 4.9 mmHg degrees C(-1), dead time of about 1.0 h and a time constant of about 9.8h are estimated for the hypothermic decompression. Based on the estimated characteristics, a feedback control of elevated ICP is introduced in a simulated intracranial hypertension of vasogenic brain edema. Simulation results suggest the possibility of an automatic control of the elevated ICP in brain hypothermia treatment.