Physiologically-based pharmacokinetics of ziprasidone in pregnant women

Prediction of tissue exposures of polymyxin-B, amikacin and sulbactam using physiologically-based pharmacokinetic modeling

Background

The combination antimicrobial therapy consisting of amikacin, polymyxin-B, and sulbactam demonstrated in vitro synergy against multi-drug resistant Acinetobacter baumannii.

Objectives

The objectives were to predict drug disposition and extrapolate their efficacy in the blood, lung, heart, muscle and skin tissues using a physiologically-based pharmacokinetic (PBPK) modeling approach and to evaluate achievement of target pharmacodynamic (PD) indices against A. baumannii.

Methods

A PBPK model was initially developed for amikacin, polymyxin-B, and sulbactam in adult subjects, and then scaled to pediatrics, accounting for both renal and non-renal clearances. The simulated plasma and tissue drug exposures were compared to the observed data from humans and rats. Efficacy was inferred using joint probability of target attainment of target PD indices.

Results

The simulated plasma drug exposures in adults and pediatrics were within the 0.5 to 2 boundary of the mean fold error for the ratio between simulated and observed means. Simulated drug exposures in blood, skin, lung, and heart were consistent with reported penetration ratio between tissue and plasma drug exposure. In a virtual pediatric population from 2 to <18 years of age using pediatric dosing regimens, the interpretive breakpoints were achieved in 85-90% of the population.

Conclusion

The utility of PBPK to predict and simulate the amount of antibacterial drug exposure in tissue is a practical approach to overcome the difficulty of obtaining tissue drug concentrations in pediatric population. As combination therapy, amikacin/polymyxin-B/sulbactam drug concentrations in the tissues exhibited sufficient penetration to combat extremely drug resistant A. baumannii clinical isolates.

Predict the Drug-Drug Interaction of a Novel PI3Kα/δ Inhibitor, TQ-B3525, and Its Two Metabolites Using Physiologically Based Pharmacokinetic Modeling

A novel dual PI3K α/δ inhibitor, TQ-B3525, has been developed for the targeted treatment of lymphoma and solid tumors. TQ-B3525 is primarily metabolized by CYP3A4 and FOM3, while also serving as a substrate for the P-glycoprotein transporter. The aim of this study was to anticipate the drug-drug interaction (DDI) of TQ-B3525 and its two metabolites with CYP3A4 enzyme potent inducer (rifampicin) and CYP3A4/P-gp inhibitor (itraconazole) utilizing a physiologically based pharmacokinetic (PBPK) modeling approach. Clinical data from healthy and cancer patient adults were employed to construct and evaluate the PBPK model for TQ-B3525, M3, and M8-3. Models involving rifampicin combined with midazolam, itraconazole combined with midazolam or digoxin were utilized to showcase the robustness of evaluating DDI effects. The simulated drug exposure of TQ-B3525, M3, and M8-3 in healthy and patient adults were consistent with clinical data, and the mean fold error values were within the acceptable ranges. The simulated results of positive substrates correspond to those reported in the literature. Co-administration with rifampicin reduces Cmax and AUC of TQ-B3525 to 76.1% and 46.0%, while increasing the levels of M3 and M8-3. With itraconazole, Cmax and AUC of TQ-B3525 rise to 131% and 204%, but decrease substantially for M3 and M8-3. PBPK model simulation results showed that the systemic exposure of TQ-B3525 was significantly affected when co-administered with CYP3A4/P-gp inducers and inhibitors. This indicates that the combination with strong inducers and inhibitors should be carefully avoided or adjust the dosage of TQ-B3525 in clinic.

Recent Progress on Physiologically Based Pharmacokinetic (PBPK) Model: A Review Based on Bibliometrics

Physiologically based pharmacokinetic/toxicokinetic (PBPK/PBTK) models are designed to elucidate the mechanism of chemical compound action in organisms based on the physiological, biochemical, anatomical, and thermodynamic properties of organisms. After nearly a century of research and practice, good results have been achieved in the fields of medicine, environmental science, and ecology. However, there is currently a lack of a more systematic review of progress in the main research directions of PBPK models, especially a more comprehensive understanding of the application in aquatic environmental research. In this review, a total of 3974 articles related to PBPK models from 1996 to 24 March 2024 were collected. Then, the main research areas of the PBPK model were categorized based on the keyword co-occurrence maps and cluster maps obtained by CiteSpace. The results showed that research related to medicine is the main application area of PBPK. Four major research directions included in the medical field were "drug assessment", "cross-species prediction", "drug-drug interactions", and "pediatrics and pregnancy drug development", in which "drug assessment" accounted for 55% of the total publication volume. In addition, bibliometric analyses indicated a rapid growth trend in the application in the field of environmental research, especially in predicting the residual levels in organisms and revealing the relationship between internal and external exposure. Despite facing the limitation of insufficient species-specific parameters, the PBPK model is still an effective tool for improving the understanding of chemical-biological effectiveness and will provide a theoretical basis for accurately assessing potential risks to ecosystems and human health. The combination with the quantitative structure-activity relationship model, Bayesian method, and machine learning technology are potential solutions to the previous research gaps.

Physiologically based pharmacokinetic modelling to inform combination dosing regimens of ceftaroline and daptomycin in special populations

AIMS

The combination of daptomycin and ceftaroline used as salvage therapy is associated with higher survival and decreased clinical failure in complicated methicillin-resistant Staphylococcus aureus (MRSA) infections that are resistant to standard MRSA treatment. This study aimed to evaluate dosing regimens for coadministration of daptomycin and ceftaroline in special populations including paediatrics, renally impaired (RI), obese and geriatrics that generate sufficient coverage against daptomycin-resistant MRSA.

METHODS

Physiologically based pharmacokinetic models were developed from pharmacokinetic studies of healthy adults, geriatric, paediatric, obese and RI patients. The predicted profiles were used to evaluate joint probability of target attainment (PTA), as well as tissue-to-plasma ratios.

RESULTS

The adult dosing regimens of 6 mg/kg every (q)24h or q48h daptomycin and 300-600 mg q12h ceftaroline fosamil by RI categories achieved ≥90% joint PTA when the minimum inhibitory concentrations in the combination are at or below 1 and 4 μg/mL against MRSA. In paediatrics, wherein there is no recommended daptomycin dosing regimen for S. aureus bacteraemia, ≥90% joint PTA is achieved when the minimum inhibitory concentrations in the combination are up to 0.5 and 2 μg/mL for standard paediatric dosing regimens of 7 mg/kg q24h daptomycin and 12 mg/kg q8h ceftaroline fosamil. Model predicted tissue-to-plasma ratios of 0.3 and 0.7 in the skin and lung, respectively, for ceftaroline and 0.8 in the skin for daptomycin.

CONCLUSION

Our work illustrates how physiologically based pharmacokinetic modelling can inform appropriate dosing of adult and paediatric patients and thereby enable prediction of target attainment in the patients during multitherapies.

Physiologically-based pharmacokinetic modeling to inform dosing regimens and routes of administration of rifampicin and colistin combination against Acinetobacter baumannii

BACKGROUND

Carbapenem-resistant Acinetobacter baumannii (CRAB) is resistant to major antibiotics such as penicillin, cephalosporin, fluoroquinolone and aminoglycoside, and has become a significant nosocomial pathogen. The efficacy of rifampicin and colistin combination against CRAB could be dependent on the administration routes and drug concentrations at the site of infection.

OBJECTIVE

The objective is to predict drug disposition in biological tissues. Treatment efficacy is extrapolated by assessing respective pharmacodynamic (PD) indices, as well as parameters associated with the emergence of resistance.

METHODS

Physiologically-based pharmacokinetic models of rifampicin and colistin were utilized to predict tissue exposures. Dosing regimens and administration routes for combination therapy were evaluated in terms of in vitro antimicrobial susceptibility of A. baumannii associated with targeted PD indices and resistance parameters.

RESULTS

Simulated exposures in blood, heart, lung, skin and brain were consistent with reported penetration rates. The results demonstrated that a combination of colistin and rifampicin using conventional intravenous (i.v.) doses could achieve effective exposures in the blood and skin. However, for lung infections, colistin by inhalation would be required due to low lung penetration from intravenous route. Inhaled colistin alone provided good PD coverage but this practice could encourage the emergence of additional resistance which may be overcome by a combination regimen that includes inhaled colistin.

CONCLUSION

This in silico extrapolation provides valuable information on dosing regimens and routes of administration against CRAB infections in specific tissues. The PBPK modeling approach could be a non-invasive way to inform therapeutic benefits of combination antimicrobial therapy.

Antidepressants and Antipsychotics in Human Pregnancy: Transfer Across the Placenta and Opportunities for Modeling Studies

There is limited information about the transfer of antidepressants and antipsychotics across the human placenta. The objective of the current review was to systematically screen the scientific literature using relevant keywords to collect quantitative data on placental transfer of these drugs in humans and to give an overview of current modeling approaches used in this context. The collected data encompassed clinically measured fetal:maternal (F:M) concentration ratios (ie, the ratio between drug concentrations measured in the umbilical cord and drug concentrations measured in the mother) and transfer data obtained from ex vivo cotyledon perfusion experiments. These data were found for 18 antidepressants and some of their pharmacologically active metabolites, and for 10 antipsychotics and the metabolites thereof. Based on the collected data, similar maternal and fetal exposure could be observed for only a few compounds (eg, norfluoxetine and desvenlafaxine), whereas for most drugs (eg, paroxetine, sertraline, and quetiapine), fetal exposure appeared to be on average lower than maternal exposure. Venlafaxine appeared to be an exception in that the data indicated equivalent or higher concentrations in the umbilical cord than in the mother. Physiologically based pharmacokinetic (PBPK) models were sporadically used to investigate maternal pharmacokinetics of antidepressants or antipsychotics (eg, for sertraline, aripiprazole, and olanzapine), although without explicitly addressing fetal drug exposure. It is recommended that PBPK modeling is applied more frequently to these drugs. Although no substitute for clinical studies, these tools can help to better understand pregnancy-induced pharmacokinetic changes and ultimately contribute to a more evidence-based pharmacotherapy of depression and psychosis in pregnant subjects.

Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting Haloperidol Exposure in Healthy and Disease Populations

The physiologically based pharmacokinetic (PBPK) approach can be used to develop mathematical models for predicting the absorption, distribution, metabolism, and elimination (ADME) of administered drugs in virtual human populations. Haloperidol is a typical antipsychotic drug with a narrow therapeutic index and is commonly used in the management of several medical conditions, including psychotic disorders. Due to the large interindividual variability among patients taking haloperidol, it is very likely for them to experience either toxic or subtherapeutic effects. We intend to develop a haloperidol PBPK model for identifying the potential sources of pharmacokinetic (PK) variability after intravenous and oral administration by using the population-based simulator, PK-Sim. The model was initially developed and evaluated to predict the PK of haloperidol and its reduced metabolite in adult healthy population after intravenous and oral administration. After evaluating the developed PBPK model in healthy adults, it was used to predict haloperidol–rifampicin drug–drug interaction and was extended to tuberculosis patients. The model evaluation was performed using visual assessments, prediction error, and mean fold error of the ratio of the observed-to-predicted values of the PK parameters. The predicted PK values were in good agreement with the corresponding reported values. The effects of the pathophysiological changes and enzyme induction associated with tuberculosis and its treatment, respectively, on haloperidol PK, have been predicted precisely. For all clinical scenarios that were evaluated, the predicted values were within the acceptable two-fold error range.

Prediction of Tissue Exposures of Meropenem, Colistin, and Sulbactam in Pediatrics Using Physiologically Based Pharmacokinetic Modeling

BACKGROUND

The combination of polymyxins, meropenem, and sulbactam demonstrated efficacy against multi-drug-resistant bacillus Acinetobacter baumannii. These three antibiotics are commonly used against major blood, skin, lung, and heart muscle infections.

OBJECTIVE

The objective of this study was to predict drug disposition and extrapolate the efficacy in these tissues using a physiologically based pharmacokinetic modeling approach that linked drug exposures to their target pharmacodynamic indices associated with antimicrobial activities against A. baumannii.

METHODS

An adult physiologically based pharmacokinetic model was developed for meropenem, colistin, and sulbactam and scaled to pediatrics accounting for both renal and non-renal clearances. The model reliability was evaluated by comparing simulated plasma and tissue drug exposures to observed data. Target pharmacodynamic indices were used to evaluate whether pediatric and adult dosing regimens provided sufficient coverage.

RESULTS

The modeled plasma drug exposures in adults and pediatric patients were consistent with reported literature data. The mean fold errors for meropenem, colistin, and sulbactam were in the range of 0.710-1.37, 0.981-1.47, and 0.647-1.39, respectively. Simulated exposures in the blood, skin, lung, and heart were consistent with reported penetration rates. In a virtual pediatric population aged from 2 to < 18 years, the interpretive breakpoints were achieved in 85-90% of subjects for their targeted pharmacodynamic indices after administration of pediatric dosing regimens consisting of 30 mg/kg of meropenem, and 40 mg/kg of sulbactam three times daily as a 3-h or continuous infusion and 5 mg/kg/day of colistin base activity.

CONCLUSIONS

The physiologically based pharmacokinetic modeling supports pediatric dosing regimens of meropenem/colistin/sulbactam in a co-administration setting against infections in the blood, lung, skin, and heart tissues due to A. baumannii.

Model-Informed Dose Optimization in Pregnancy

Pregnancy is associated with several physiological changes that can alter the pharmacokinetics (PK) and pharmacodynamics of drugs. These may require dosing changes in pregnant women to achieve drug exposures comparable to the nonpregnant population. There is, however, limited information available on the PK and pharmacodynamics of drugs used during pregnancy. Practical difficulties in performing PK studies and potential liability issues are often the reasons for the availability of limited information. Over the past several years, there has been a rapid development in the application of various modeling strategies such as population PK and physiologically based PK modeling to provide guidance on drug dosing in this special patient population. Population PK models rely on measured PK data, whereas physiologically based PK models integrate physiological, preclinical, and clinical data to quantify changes in PK of drugs in various patient populations. These modeling strategies offer a promising approach to identify the drugs with PK changes during pregnancy and guide dose adjustment in pregnant women. This review focuses on PBPK modeling to guide drug therpay in pregnancy.

Maternal-Fetal Pharmacology of Drugs: A Review of Current Status of the Application of Physiologically Based Pharmacokinetic Models

Pregnancy and the postpartum period are associated with several physiological changes that can alter the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. For certain drugs, dosing changes may be required during pregnancy and postpartum to achieve drug exposures comparable to what is observed in non-pregnant subjects. There is very limited data on fetal exposure of drugs during pregnancy, and neonatal exposure through transfer of drugs via human milk during breastfeeding. Very few systematic clinical pharmacology studies have been conducted in pregnant and postpartum women due to ethical issues, concern for the fetus safety as well as potential legal ramifications. Over the past several years, there has been an increase in the application of modeling and simulation approaches such as population PK (PopPK) and physiologically based PK (PBPK) modeling to provide guidance on drug dosing in those special patient populations. Population PK models rely on measured PK data, whereas physiologically based PK models incorporate physiological, preclinical, and clinical data into the model to predict drug exposure during pregnancy. These modeling strategies offer a promising approach to identify the drugs with PK changes during pregnancy to guide dose optimization in pregnancy, when there is lack of clinical data. PBPK modeling is also utilized to predict the fetal exposure of drugs and drug transfer via human milk following maternal exposure. This review focuses on the current status of the application of PBPK modeling to predict maternal and fetal exposure of drugs and thereby guide drug therapy during pregnancy.

Physiologically based pharmacokinetic-pharmacodynamic evaluation of meropenem plus fosfomycin in paediatrics

AIMS

The objective of the current study was to evaluate paediatric dosing regimens for meropenem plus fosfomycin that generate sufficient coverage against multidrug-resistant bacteria.

METHODS

The physiologically based pharmacokinetic (PBPK) models of meropenem and fosfomycin were developed from previously published pharmacokinetic studies in five populations: healthy subjects of Japanese origin, and healthy adults, geriatric, paediatric and renally impaired of primarily Caucasian origins. Pharmacodynamic (PD) analyses were carried out by evaluating dosing regimens that achieved a ≥90% joint probability of target attainment (PTA), which was defined as the minimum of the marginal probabilities to achieve the target PD index of each antibiotic. For meropenem, the percentage of time over a 24-hour period wherein the free drug concentration was above the minimum inhibitory concentration (fT > MIC) of at least 40% was its PD target. The fosfomycin PD index was described by fAUC/MIC of at least 40.8.

RESULTS

For coadministration consisting of 20 mg/kg meropenem q8h as a 3-hour infusion and 35 mg/kg fosfomycin q8h also as a 3-hour infusion in a virtual paediatric population between 1 month and 12 years of age with normal renal function and a corresponding body weight between 3 and 50 kg, a joint PTA ≥ 90% is achieved at MICs of 16 and 64 mg/L for meropenem and fosfomycin coadministration, respectively, against Klebsiella pneumoniae and Pseudomonas aeruginosa.

CONCLUSION

The current study identified potentially effective paediatric dosing regimens for meropenem plus fosfomycin coadministration against multidrug-resistant bacteria.

Physiologically-based pharmacokinetics of ziprasidone in pregnant women

AIMS

Pregnancy is associated with physiological changes that alter the pharmacokinetics (PK) of drugs. The aim of this study was to predict the PK of ziprasidone in pregnant women.

METHODS

A full physiologically-based pharmacokinetic (PBPK) model of ziprasidone was developed and validated for the non-pregnant population (healthy adults, paediatrics, geriatrics), and this was extended to the pregnant state to assess the change in PK profile of ziprasidone throughout pregnancy.

RESULTS

The PBPK model successfully predicted the ziprasidone disposition in healthy adult volunteers, wherein the predicted and observed AUC, C_max and t_max were within the fold-difference of 0.94-1.09, 0.89-1.40 and 0.80-1.08, respectively. The paediatric and geriatric population, also showed predicted AUC, C_max and t_max within a two-fold range of the observed values. The simulated exposure in pregnant women using a p-PBPK model showed no significant difference when compared to non-pregnant women.

CONCLUSIONS

The PBPK model predicted the impact of physiological changes during pregnancy on PK and exposure of ziprasidone, suggesting that dose adjustment is not necessary in this special population.