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The volume and distribution of fluids available in the gastrointestinal (GI) tract may substantially affect oral drug absorption. Magnetic resonance imaging (MRI) has been used in the past to quantify these fluid volumes in adults and its use is now being extended to the pediatric population. The present research pursued a retrospective, explorative analysis of existing clinical MRI data generated for pediatric patients. Images of 140 children from all pediatric subpopulations were analyzed for their resting GI fluid volumes in fasting conditions. In general, an increase in fluid volume as a function of age was observed for the stomach, duodenum, jejunum, and small intestine (SI) as a whole. No specific pattern was observed for the ileum and colon. Body mass index (BMI), body weight, body height, and SI length were evaluated as easy-to-measure clinical estimators of the gastric and SI fluid volumes. Although weight and height were identified as the best estimators, none performed ideally based on the coefficient of determination (R2). Data generated in this study can be used as physiologically relevant input for biorelevant in vitro tests and in silico models tailored to the pediatric population, thereby contributing to the efficient development of successful oral drug products for children. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ticagrelor is an orally administered antiplatelet agent that has been approved for the reduction of cardiovascular risk in patients with history of cardiovascular disease. However, Ticagrelor can also cause adverse effects, including dyspnea. Ticagrelor plasma and saliva concentrations of 63 Jordanian patients were measured using a sensitive LCMS/MS method. Ticagrelor was not excreted in saliva as it corresponds to the Class IV salivary excretion classification system. The correlation between plasma ticagrelor concentrations and the occurrence of dyspnea was examined to establish a therapeutic window for plasma ticagrelor. A physiologically-based pharmacokinetic (PBPK) model of ticagrelor was built and validated using previously- published plasma data. The validated model was then used to predict the factors affecting ticagrelor plasma concentrations. A loading dose of 135 mg (1.5 tablet) instead of 2 tablets has been suggested to maintain its therapeutic effect and avoid dyspnea. [ABSTRACT FROM AUTHOR]

The goal of this study was to assess a cadmium (Cd) physiologically based pharmacokinetic (PBPK) model to evaluate Cd toxicological reference values (e.g. reference dose , tolerable intake, minimum risk level) adapted to the U.S. population. We reviewed and evaluated previously published Cd PBPK models and developed further adaptations to the 1978 Kjellström and Nordberg (KN) model. Specifically, we propose adaptations with updated U.S.-specific bodyweight, kidney weight and creatinine excretion models by using NHANES data as well as a stochastic PBPK model that provides credible intervals of uncertainty around mean populational estimates. We provide our model review and adaptations as well as present estimates from the newly adapted models using observed U.S. urinary Cd values as a function of gender and age and given dietary exposure as evaluated from NHANES/WWEIA and U.S. Total Diet Study data. Results show all newly adapted models provide acceptable mean estimates of urinary Cd in the U.S. The stochastic model provides credible intervals to further inform regulatory decision making. Validation of the estimated K-Cd concentration values was not possible as data for a representative population was not available. We developed a web-based tool implementing these models and other potential adaptations to facilitate PBPK model estimate comparisons. • We reviewed, and evaluated previously published Cd PBPK models for use in setting toxicological reference values. • We developed U.S specific bodyweight, kidney weight and creatinine excretion models. • We developed a stochastic PBPK model that properly estimates exposure by reverse dosimetry. • We developed a tool to facilitate model estimate comparisons using forward and reverse dosimetry. [ABSTRACT FROM AUTHOR]

The use of physiologically based pharmacokinetic (PBPK) modeling to support the drug product quality attributes, also known as physiologically based biopharmaceutics modeling (PBBM) is an evolving field and the interest in using PBBM is increasing. The US-FDA has emphasized on the use of patient centric quality standards and clinically relevant drug product specifications over the years. Establishing an in vitroin vivo link is an important step towards achieving the goal of patient centric quality standard. Such a link can aid in constructing a bioequivalence safe space and establishing clinically relevant drug product specifications. PBBM is an important tool to construct a safe space which can be used during the drug product development and lifecycle management. There are several advantages of using the PBBM approach, though there are also a few challenges, both with in vitro methods and in vivo understanding of drug absorption and disposition, that preclude using this approach and therefore further improvements are needed. In this review we have provided an overview of experience gained so far and the current perspective from regulatory and industry point of view. Collaboration between scientists from regulatory, industry and academic fields can further help to advance this field and deliver on promises that PBBM can offer towards establishing patient centric quality standards. [ABSTRACT FROM AUTHOR]

Purpose: Venetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure. Method: Two physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (Ki) of VCZ for CYP3A4 was calibrated using drug-drug interaction (DDI) data of midazolam and VCZ. The clinical verified VCZ and VEN model were used to predict the DDI of VCZ and VEN at clinical dosing scenario. Result: VCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5–9.6 fold. The increase in VEN exposure by VCZ was influenced by subject's CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ. Conclusion: The PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability. [ABSTRACT FROM AUTHOR]

RO7119929 is being developed as an orally administered prodrug of the TLR7-specific agonist and active drug, RO7117418, for the treatment of patients with solid tumours. In this publication, we present a case study wherein the human pharmacokinetics and pharmacological active dose were prospectively predicted following oral administration of the prodrug. A simple translational pharmacokinetic-pharmacodynamic strategy was applied to predict the pharmacological active dose of the prodrug in human. In vivo studies in monkey showed that an unbound plasma exposure of active drug of 1.5 ng/mL elicited secretion of key serum pharmacodynamic cytokine and chemokine biomarkers in monkey. This threshold of 1.5 ng/mL was close to the minimum effective concentration of active drug required to induce cytokine secretion in human peripheral blood mononuclear cells (3 ng/mL). Measured in vitro physicochemical and biochemical properties of the prodrug and active drug were applied as input parameters in physiologically based pharmacokinetic models to predict the pharmacokinetics of active drug after oral dosing of the prodrug in humans. Then, using the PBPK model, a dose which delivered an unbound plasma Cmax in line with the target pharmacodynamic threshold of 1.5 ng/mL was found. This defined the lowest pharmacologically active dose as 3 mg. The prodrug entered the clinic in 2020 in patients with primary or secondary liver cancers. Clear pharmacodynamic, transient, and dose-dependent cytokine induction was observed at prodrug doses > 1 mg. [ABSTRACT FROM AUTHOR]

The study is based on using SeDeM expert system in developing controlled-release tramadol HCl osmotic tablets and its in-silico physiologically based pharmacokinetic (PBPK) modeling for in-vivo pharmacokinetic evaluation. A Quality by Design (QbD) based approach in developing SeDEM-driven full factorial osmotic drug delivery was applied. A 24 Full-factorial design was used to make the trial formulations of tramadol HCl osmotic tablets using NaCl as osmogen, Methocel K4M as rate controlling polymer, and avicel pH 101 as diluent. The preformulation characteristics of formulations (F1-F16) were determined by applying SeDeM Expert Tool. The formulation was optimized followed by in-vivo predictive pharmacokinetic assessment using PBPK “ACAT” model of GastroPlus™. The FTIR results showed no interaction among the ingredients. The index of good compressibility (ICG) values of all trial formulation blends were ≥5, suggesting direct compression is the best-suited method. Formulation F3 and F4 were optimized based on drug release at 2, 10, and 16 h with a zero-order kinetic release (r2 = 0.992 and 0.994). The SEM images confirmed micropores formation on the surface of the osmotic tablet after complete drug release. F3 and F4 were also stable (shelf life 29.41 and 23.46 months). The in vivo simulation of the pharmacokinetics of the PBPK in-silico model revealed excellent relative bioavailability of F3 and F4 with reference to tramadol HCl 50 mg IR formulations. The SeDeM expert tool was best utilized to evaluate the compression characteristics of selected formulation excipients and their blends for direct compression method in designing once-daily osmotically controlled-release tramadol HCl tablets. The in-silico GastroPlus™ PBPK modeling provided a thorough pharmacokinetic assessment of the optimized formulation as an alternative to tramadol HCl in vivo studies.

Each year, infections caused around the 25% of neonatal deaths. Early empirical treatments help to reduce this mortality, although optimized dosing regimens are still lacking. The aims were to develop and validate a gentamicin physiologically-based pharmacokinetic (PBPK) model and then potentially explore dosing regimens in neonates using pharmacokinetic and pharmacodynamic criteria. The PBPK model developed consisted of 2 flow-limited tissues: kidney and other tissues. It has been implemented on a new tool called PhysPK, which allows structure reusability and evolution as predictive engine in Model-Informed Precision Dosing (MIPD). Retrospective pharmacokinetic information based on serum levels data from 47 neonates with gestational age between 32 and 39 weeks and younger than one-week postnatal age were used for model validation. The minimal PBPK model developed adequately described the gentamicin serum concentration-time profile with an average fold error nearly 1. Extended interval gentamicin dosing regimens (6 mg/kg q36h and 6 mg/kg q48h for term and preterm neonates, respectively) showed efficacy higher than 99% with toxicity lower than 10% through Monte Carlo simulation evaluations. The gentamicin minimal PBPK model developed in PhysPK from literature information, and validated in preterm and term neonates, presents adequate predictive performance and could be useful for MIPD strategies in neonates.

Disrupted tau proteostasis and transneuronal spread is a pathological hallmark of Alzheimer’s disease. Neurodegenerative diseases remain an unmet medical need and novel disease modifying therapeutics are paramount. Our objective was to develop a mechanistic mathematical model to enhance our understanding of tau antibody pharmacokinetics and pharmacodynamics in animals and humans. A physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) modeling approach was employed to support the preclinical development and clinical translation of therapeutic antibodies targeting tau for the treatment of Alzheimer’s disease. The pharmacokinetics of a tau antibody was evaluated in rat and non-human primate microdialysis studies. Model validation for humans was performed using publicly available clinical data for gosuranemab. In-silico analyses were performed to predict tau engagement in human brain for a range of tau antibody affinities and various dosing regimens. PBPK-PD modeling enabled a quantitative understanding for the relationship between dose, affinity, and target engagement, which supported lead candidate optimization and predictions of clinically efficacious dosing regimens.

Physiologically based pharmacokinetic (PBPK) models which can leverage preclinical data to predict the pharmacokinetic properties of drugs rapidly became an essential tool to improve the efficiency and quality of novel drug development. In this review, by searching the Application Review Files in Drugs@FDA, we analyzed the current application of PBPK models in novel drugs approved by the U.S. Food and Drug Administration (FDA) in the past five years. According to the results, 243 novel drugs were approved by the FDA from 2019 to 2023. During this period, 74 Application Review Files of novel drugs approved by the FDA that used PBPK models. PBPK models were used in various areas, including drug-drug interactions (DDI), organ impairment (OI) patients, pediatrics, drug-gene interaction (DGI), disease impact, and food effects. DDI was the most widely used area of PBPK models for novel drugs, accounting for 74.2 % of the total. Software platforms with graphical user interfaces (GUI) have reduced the difficulty of PBPK modeling, and Simcyp was the most popular software platform among applicants, with a usage rate of 80.5 %. Despite its challenges, PBPK has demonstrated its potential in novel drug development, and a growing number of successful cases provide experience learned for researchers in the industry. [Display omitted] [ABSTRACT FROM AUTHOR]

Prediction of rat, dog, monkey, and human volume of distribution (VDss) by Rodgers-Lukacova model was evaluated using a data set of more than 100 compounds. The prediction accuracy was best for humans followed by monkeys and dogs with 59, 52, and 41% of compounds within 2-fold, respectively. The accuracy of predictions in preclinical species was indicative of the human situation. This was particularly true for monkeys, where 87% of the compounds that were predicted within 2-fold in monkeys were also predicted within 2-fold in humans. The model's tendency to underestimate VDss was higher in rats and dogs compared to humans and monkeys for all ion classes but zwitterions. Hence, correction of human predictions using prediction errors in rats and dogs resulted in overestimation of VDss. The model had a similar degree of underestimation in humans and monkeys. Correction using monkeys improved the accuracy of the human estimate, especially for basic and zwitterion compounds. A strategy is proposed based on the accuracy of prediction in monkey and monkey scalars for prediction and prospective assessment of the accuracy of human VDss. [ABSTRACT FROM AUTHOR]

New drugs may in some cases need to be tested in paediatric and pregnant patients. However, it is difficult to recruit such patients and there are many ethical issues around their inclusion in clinical trials. Modelling and simulation can help to plan well-designed clinical trials with a reduced number of participants and to bridge gaps where recruitment is difficult. Physiologically based pharmacokinetic (PBPK) models for small molecule drugs have been used to aid study design and dose adjustments in paediatrics and pregnancy, with several publications in the literature. However, published PBPK models for monoclonal antibodies (mAb) in these populations are scarce. Here, the current status of mAb PBPK models in paediatrics and pregnancy is discussed. Seven mAb PBPK models published for paediatrics were found, which report good prediction accuracy across a wide age range. No mAb PBPK models for pregnant women have been published to date. Current challenges to the development of such PBPK models are discussed, including gaps in our knowledge of relevant physiological processes and availability of clinical data to verify models. As the availability of such data increases, it will help to improve our confidence in the PBPK model predictive ability. Advantages for using PBPK models to predict mAb PK in paediatrics and pregnancy are discussed. For example, the ability to incorporate ontogeny and gestational changes in physiology, prediction of maternal, placental and foetal exposure and the ability to make predictions from in vitro and preclinical data prior to clinical data being available. [ABSTRACT FROM AUTHOR]

Immune checkpoint blockades prescribed in the neoadjuvant setting are now under active investigation for many types of tumors, and many have shown early success. The primary tumor (PT) and tumor-draining lymph node (TDLN) immune factors, along with adequate therapeutic antibody distributions to the PT and TDLN, are critical for optimal immune activation and anti-tumor efficacy in neoadjuvant immunotherapy. However, it remains largely unknown how much of the antibody can be distributed into the PT-TDLN axis at different clinical scenarios. The goal of the current work is to build a physiologically based pharmacokinetic (PBPK) model framework capable of characterizing antibody distribution gradients in the PT-TDLN axis across various clinical and pathophysiological scenarios. The model was calibrated using clinical data from immuno-PET antibody-imaging studies quantifying antibody pharmacokinetics (PK) in the blood, PTs, and TDLNs. The effects of metastatic lesion location, tumor-induced compression, and inflammation, as well as surgery, on antibody concentration gradients in the PT-TDLN axis were characterized. The PBPK model serves as a valuable tool to predict antibody exposures in various types of tumors, metastases, and the associated lymph node, supporting effective immunotherapy. [ABSTRACT FROM AUTHOR]

Objectives: There are a multitude of different modelling techniques that have been used for inhaled drugs. The main objective of this review was to conduct an exhaustive survey of published mathematical models in the area of asthma and chronic obstructive pulmonary disease (COPD) for inhalation drugs. Additionally, this review will attempt to assess the applicability of these models to assess bioequivalence (BE) of orally inhaled products (OIPs). Evidence acquisition: PubMed, Science Direct, Web of Science, and Scopus databases were searched from 1996 to 2020, to find studies that described mathematical models used for inhaled drugs in asthma/COPD. Results: 50 articles were finally included in this systematic review. This research identified 22 articles on in silico aerosol deposition models, 20 articles related to population pharmacokinetics and 8 articles on physiologically based pharmacokinetic modelling (PBPK) modelling for inhaled drugs in asthma/COPD. Among all the aerosol deposition models, computational fluid dynamics (CFD) simulations are more likely to predict regional aerosol deposition pattern in human respiratory tracts. Across the population PK articles, body weight, gender, age and smoking status were the most common covariates that were found to be significant. Further, limited published PBPK models reported approximately 29 parameters relevant for absorption and distribution of inhaled drugs. The strengths and weaknesses of each modelling technique has also been reviewed. Conclusion: Overall, while there are different modelling techniques that have been used for inhaled drugs in asthma and COPD, there is very limited application of these models for assessment of bioequivalence of OIPs. This review also provides a ready reference of various parameters that have been considered in various models which will aid in evaluation if one model or hybrid in silico models need to be considered when assessing bioequivalence of OIPs. [ABSTRACT FROM AUTHOR]

A physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model for tegoprazan and its major metabolite M1 was developed to predict PK and PD profiles under various scenarios. The PBPK model for tegoprazan and M1 was developed and predicted using the SimCYP® simulator and verified using clinical study data obtained after a single administration of tegoprazan. The established PBPK/PD model was used to predict PK profiles after repeated administrations of tegoprazan, postprandial PK profiles, and intragastric pH changes. The predicted tegoprazan and M1 concentration–time profiles fit the observed profiles well. The arithmetic mean ratios (95% confidence intervals) of the predicted to observed values for the area under the curve (AUC0–24 h), maximum plasma drug concentration (Cmax), and clearance (CL) for tegoprazan and M1 were within a 30% interval. Delayed time of maximum concentration (Tmax) and decreased Cmax were predicted in the postprandial PK profiles compared with the fasted state. This PBPK/PD model may be used to predict PK profiles after repeated tegoprazan administrations and to predict differences in physiological factors in the gastrointestinal tract or changes in gastric acid pH after tegoprazan administration. [ABSTRACT FROM AUTHOR]

New approaches in drug development are needed to address the growing epidemic of obesity as the prevalence of obesity increases worldwide. 2,4-Dinitrophenol (DNP) is an oxidative phosphorylation uncoupling agent that was widely used in the early 1930s for weight loss but was quickly banned by the FDA due to the severe toxicities associated with the compound. One of the limitations leading to the demise of DNP as a pharmaceutical was a lack of understanding about the pharmacokinetic–pharmacodynamic relationship. The purpose of this study was to investigate whole body disposition of DNP in order to understand the relationship between the pharmacokinetics, efficacy and toxicity in the C57BL/6J diet induced obese mouse model. Following intravenous administration of 1 mg/kg, and intraperitoneal administration of 5 mg/kg and 15 mg/kg of DNP, we found limited DNP distribution to tissues. Experimentally measured partition coefficients were found to be less than 1 for all analyzed tissues. In addition, DNP exhibits significant nonlinear pharmacokinetics, which we have attributed to nonlinear plasma protein binding and nonlinear partitioning into liver and kidney. By enhancing our understanding of the PK–PD relationship, we can develop new approaches to leverage oxidative phosphorylation uncoupling as a weight loss strategy. [ABSTRACT FROM AUTHOR]

A physiologically based pharmacokinetic (PBPK) model for the important chemical phenoxyethanol (PhE) and its metabolite phenoxyacetic acid (PhAA) was built via GastroPlusTM software (version 9.0) using currently available analytically measured plasma and urinary time-courses of both PhE and its metabolite PhAA. This model was validated and used to predict tissue and urine concentrations of PhE and its metabolite PhAA in rats and humans after oral and dermal exposures. The prediction results showed that most predicted tissue concentrations of PhE or PhAA were lower than the experimental tissue concentrations based on total radioactivity. The predicted cumulative excretion of PhAA in both rats and humans fits very well with most experimental data. With this GastroPlusTM-based model, the margins of exposure (MOE) of PhE and PhAA were also calculated as 194 and 73.7, respectively. The predicted MOE of PhE is two-fold higher than the previous PBPK model built using total radioactivity-based tissue time courses, and the predicted MOE of PhAA was comparable to the previous PBPK model. These data indicate that for chemicals like PhE, GastroPlusTM can integrate multiple data sets into PBPK models to predict PK parameters for parent and metabolites in both rats and humans following intravenous, dermal, or oral exposures. [ABSTRACT FROM AUTHOR]

Therapeutic monoclonal antibodies (mAbs) have been a promising therapeutic approach for several diseases and a wide variety of mAbs are being evaluated in clinical trials. To accelerate clinical development and improve the probability of success, pharmacokinetics and pharmacodynamics (PKPD) in humans must be predicted before clinical trials can begin. Traditionally, empirical-approach-based PKPD prediction has been applied for a long time. Recently, modeling and simulation (M&S) methods have also become valuable for quantitatively predicting PKPD in humans. Although several models (e.g., the compartment model, Michaelis–Menten model, target-mediated drug disposition model, and physiologically based pharmacokinetic model) have been established and used to predict the PKPD of mAbs in humans, more complex mechanistic models, such as the quantitative systemics pharmacology model, have been recently developed. This review summarizes the recent advances and future direction of M&S-based approaches to the quantitative prediction of human PKPD for mAbs. [ABSTRACT FROM AUTHOR]

Purpose: Ipatasertib, a potent and highly selective small-molecule inhibitor of AKT, is currently under investigation for treatment of cancer. Ipatasertib is a substrate and a time-dependent inhibitor of CYP3A4. It exhibits non-linear pharmacokinetics at subclinical doses in the clinical dose escalation study. To assess the DDI risk of ipatasertib at the intended clinical dose of 400 mg with CYP3A4 inhibitors, inducers, and substrates, a fit-for-purpose physiologically based pharmacokinetic (PBPK) model of ipatasertib was developed. Methods: The PBPK model was constructed in Simcyp using in silico, in vitro, and clinical data and was optimized and verified using clinical data. Results: The PBPK model described non-linear pharmacokinetics of ipatasertib and captured the magnitude of the observed clinical DDIs. Following repeated doses of 400 mg ipatasertib once daily (QD), the PBPK model predicted a 3.3-fold increase of ipatasertib exposure with itraconazole; a 2–2.5-fold increase with moderate CYP3A4 inhibitors, erythromycin and diltiazem; and no change with a weak CYP3A4 inhibitor, fluvoxamine. Additionally, in the presence of strong or moderate CYP3A4 inducers, rifampicin and efavirenz, ipatasertib exposures were predicted to decrease by 86% and 74%, respectively. As a perpetrator, the model predicted that ipatasertib (400 mg) caused a 1.7-fold increase in midazolam exposure. Conclusion: This study demonstrates the value of using a fit-for-purpose PBPK model to assess the clinical DDIs for ipatasertib and to provide dosing strategies for the concurrent use of other CYP3A4 perpetrators or victims. [ABSTRACT FROM AUTHOR]

Muhammad Nasir Kalam,1 Muhammad Fawad Rasool,2 Faleh Alqahtani,3 Imran Imran,4 Asim Ur Rehman,1 Naveed Ahmed1 1Department of Pharmacy, Quaid-i-Azam University, Islamabad, 45320, Pakistan; 2Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800, Pakistan; 3Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia; 4Department of Pharmacology, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800, PakistanCorrespondence: Naveed AhmedDepartment of Pharmacy, Quaid-i-Azam University, Islamabad, 45320, PakistanTel +92 (51) 90644180Email natanoli@qau.edu.pkMuhammad Fawad RasoolDepartment of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, PakistanTel +923008639046Email fawadrasool@bzu.edu.pkAim: The study was aimed to understand the underlying causes for the differences in propranolol pharmacokinetics (PK) between healthy and cirrhosis populations by using a systematic whole-body physiologically based pharmacokinetic (PBPK) model-building approach for suggesting model informed propranolol dosing in liver cirrhosis patients with different stages of disease severity.Methods: A whole-body PBPK model was developed by using population simulator PK-Sim® by using reported physicochemical and clinical data for propranolol in healthy and liver cirrhosis populations. The model evaluation was done by visual verification and comparison of PK parameters using their observed/predicted ratios (Robs/pred).Results: The developed model has effectively described the disposition of propranolol after intravenous and oral application in healthy and liver cirrhosis populations. All the model predictions were comparable to the observed clinical data and the Robs/pred for all the PK parameters were within a 2-fold range. A significant increase in plasma concentration of propranolol and decrease in drug clearance was observed in progressive stages of liver cirrhosis. The developed model after evaluation with the reported clinical PK data was used for suggesting model informed propranolol dosing in different stages of liver cirrhosis based on systemic unbound drug concentration.Conclusion: The developed PBPK model has successfully described propranolol PK in healthy and cirrhosis populations after IV and oral administration. The evaluated PBPK propranolol-cirrhosis model can have many implications in predicting propranolol dosing in liver cirrhosis patients with different stages of disease severity.Keywords: PBPK, propranolol, cirrhosis, dose adjustments, drug therapy

On July 10, 1976, an explosion at a chemical plant in Seveso, Italy, released up to 30kg of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-the most potent dioxin congener. Twenty years later, the Seveso Women's Health Study (SWHS) initiated a follow-up assessment of a cohort of female Seveso residents. Researchers collected serial blood, measured for TCDD levels, and recorded information about the women's medical history after the explosion. The study's aims were to: 1) modify the human PBPK model for TCDD (Emond et al. 2004; Emond et al. 2005; NCEA-USEPA, 2010) to include repetitive gestation and lactation; 2) simulate TCDD blood concentrations during different life stages including pregnancy and lactation, under different exposure scenarios; and 3) use this PBPK model to compare the influence of gestation and lactation on elimination of TCDD. After optimization of the model, it was assessed using data from the SWHS cohort. The 23 women in Subcohort A, were 4-39years old and in Subcohort B, the 18 women were 3-17years old when the explosion occurred. The model accurately predicted the blood concentrations during the 20years post-exposure, including periods of pregnancy and lactation. The model was also used to analyze the contribution of gestation and lactation to the mother's elimination of TCDD. The results suggest that gestation and lactation do not significantly impact TCDD blood elimination. Future efforts will focus on using additional data to evaluate the PBPK model and improving the mathematical descriptions of lactation and multiple gestations.

• An integrative overall PBPK-hepatic lipids quantitative model for in vivo hepatic lipid content via nuclear receptors. • Computational Model simulations highlight the role of hepatic uptake of serum lipids contribution to hepatic lipids content. • Serum FFAs levels play an important role in regulating hepatic lipids content via nuclear receptor activation. • Quantitative model is useful for in vitro to in vivo extrapolations of PXR and LXR mediated increased hepatic FFAs content. Hepatic steatosis is characterized by the intracellular increase of free fatty acids (FFAs) in the form of triglycerides in hepatocytes. This hepatic adverse outcome can be caused by many factors, including exposure to drugs or environmental toxicants. Mechanistically, accumulation of lipids in the liver can take place via several mechanisms such as de novo synthesis and/or uptake of FFAs from serum via high fat content diets. De novo synthesis of FFAs within the liver is mediated by the liver X receptor (LXR), and their uptake into the liver is mediated through the pregnane X receptor (PXR). We investigated the impact of chemical exposure on FFAs hepatic content via activation of LXR and PXR by integrating chemical-specific physiologically based pharmacokinetic (PBPK) models with a quantitative toxicology systems (QTS) model of hepatic lipid homeostasis. Three known agonists of LXR and/or PXR were modeled: T0901317 (antagonist for both receptors), GW3965 (LXR only), and Rifampicin (PXR only). Model predictions showed that T0901317 caused the most FFAs build-up in the liver, followed by Rifampicin and then GW3965. These modeling results highlight the importance of PXR activation for serum FFAs uptake into the liver while suggesting that increased hepatic FAAs de novo synthesis alone may not be enough to cause appreciable accumulation of lipids in the liver under normal environmental exposure levels. Moreover, the overall PBPK-hepatic lipids quantitative model can be used to screen chemicals for their potential to cause in vivo hepatic lipid content buildup in view of their in vitro potential to activate the nuclear receptors and their exposure levels. [ABSTRACT FROM AUTHOR]

Minute ventilation rates (VE), alveolar ventilation rates (VA), cardiac outputs (Q), liver blood flow (LBF) and kidneys blood flows (KBF) for physiologically based toxicokinetic modeling and occupational health risk assessment in active workers have apparently not been determined. Minute energy expenditure rates (E) and oxygen consumption rates (VO2) in workers during exertions and their aggregate daytime activities are obtained by using open-circuit wearable devices for indirect calorimetry measurements and the doubly labeled water method respectively. Hundreds of E (in kcal/min) and VO2 (in L of O2/min) were previously reported for workers. The oxygen uptake factors of 0.2059 ± 0.0019 and 0.2057 ± 0.0018 L of O2/kcal during postprandial and fasting phases respectively enabled conversion of E into VO2. Equations determined in this study based upon more than 25 000 published measurements enable the calculation of 15 parameters in the same worker only by using the VO2 reflecting workload. These parameters, notably VE, VA, VE/VO2 VA/Q, Q, LBF and KBF were found to be interrelated. Altering one of these changes the order of magnitude of the others. Q, LBF and KBF decrease when supine adults at rest switch to an upright position. This effect of gravity diminished when VO2 increased. The fall in LBF and KBF during exertion might enhance muscle blood flow as reported previously. Taken together these equations and data may improve the accuracy of physiologically based toxicokinetic modeling as well as occupational health assessment studies in active workers exposed to xenobiotics. List of main abbreviations: AVOD: arterioveinous oxygen content difference.BMI: body mass index (in kg/m2).BSA: body surface area (in m2).BTPS: body temperature and saturated with water vapor.Bw: body weight (in kg).E: minute energy expenditure rate (in kcal/min).FGE: organ blood flow factor for the gravitational effect on blood circulation.H: oxygen uptake factor, volume of oxygen (at STPD) consumed to produce 1 kcal of energy expended.KBF: kidneys blood flow (in ml/min).LBF: liver blood flow (in ml/min).PBF: liver or kidneys blood flows expressed in terms of percentages (in %) of Qsup C values: namely PBF = (LBF or KBF/Qsup C) x 100.Q: cardiac output (in L/min or ml/min).Qsup C: cardiac output for the cohort of males or females in supination (in ml/min).STPD: standard temperature and pressure, dry air.sup: values measured when adults are in the supine position.up: values measured when adults are in the upright position.VDphys: physiological dead space at BTPS (in L).VT: tidal volume at BTPS (in L).VA: alveolar ventilation rate at BTPS (in L/min).VA/Q: ventilation-perfusion ratio (unitless).VE: minute ventilation rate at BTPS (in L/min).VO2: oxygen consumption rate (i.e. the oxygen uptake) at STPD (in L/min).VQ: ventilatory equivalent for VO2 (VE at BTPS /VO2 at STPD). [ABSTRACT FROM AUTHOR]

Aims: This study aims to quantify drug‐metabolising enzymes, transporters, receptor tyrosine kinases (RTKs) and protein markers (involved in pathways affected in cancer) in pooled healthy, histologically normal and matched cancerous liver microsomes from colorectal cancer liver metastasis (CRLM) patients. Methods: Microsomal fractionation was performed and pooled microsomes were prepared. Global and accurate mass and retention time liquid chromatography–mass spectrometry proteomics were used to quantify proteins. A QconCAT (KinCAT) for the quantification of RTKs was designed and applied for the first time. Physiologically based pharmacokinetic (PBPK) simulations were performed to assess the contribution of altered abundance of drug‐metabolising enzymes and transporters to changes in pharmacokinetics. Results: Most CYPs and UGTs were downregulated in histologically normal relative to healthy samples, and were further reduced in cancer samples (up to 54‐fold). The transporters, MRP2/3, OAT2/7 and OATP2B1/1B3/1B1 were downregulated in CRLM. Application of abundance data in PBPK models for substrates with different attributes indicated substantially lower (up to 13‐fold) drug clearance when using cancer‐specific instead of default parameters in cancer population. Liver function markers were downregulated, while inflammation proteins were upregulated (by up to 76‐fold) in cancer samples. Various pharmacodynamics markers (e.g. RTKs) were altered in CRLM. Using global proteomics, we examined proteins in pathways relevant to cancer (such as metastasis and desmoplasia), including caveolins and collagen chains, and confirmed general over‐expression of such pathways. Conclusion: This study highlights impaired drug metabolism, perturbed drug transport and altered abundance of cancer markers in CRLM, demonstrating the importance of population‐specific abundance data in PBPK models for cancer. [ABSTRACT FROM AUTHOR]

Purpose: Ethambutol (EMB) is a first-line anti-tubercular drug that is known to cause optic neuropathy. The exact mechanism of its eye toxicity is unknown; however, proposition is metal chelating effect of both EMB and its metabolite 2,2'-(ethylenediamino)-dibutyric acid (EDBA). The latter is formed by sequential metabolism of EMB by alcohol dehydrogenases (ADHs) and aldehyde dehydrogenases (ALDHs). The purpose of this study was to predict the levels of drug and EDBA in the eye using physiologically based pharmacokinetic (PBPK) modeling. Methods: The PBPK model of EMB was developed using GastroPlus. The intrinsic hepatic clearance of ALDH, calculated by the model, was scaled down using proteomics data to estimate the rate of formation of EDBA in the eye. Additionally, the comparative permeability of EMB and EDBA was assessed by employing in silico and in vitro approaches. The rate of formation of EDBA in the eye and permeability data were then incorporated in a compartmental model to predict the ocular levels of EMB and EDBA. Results: The simulation results of compartmental model highlighted that there was an on-site formation of EDBA upon metabolism of EMB. Furthermore, in silico and in vitro studies revealed that EDBA possessed much lower permeability than EMB. These observations meant that once EDBA was formed in the eye, it was not permeated out and hence achieved higher ocular concentration. Conclusion: The on-site formation of EDBA in the eye, its higher local concentration due to lower ocular clearance and its pre-known characteristic to chelate metal species better explains the ocular toxicity shown by EMB. [ABSTRACT FROM AUTHOR]

Chlordecone (CD; Kepone™) is a carcinogenic organochlorine insecticide with neurological, reproductive, and developmental toxicity that was widely used in the French West Indies (FWI) from 1973 to 1993 to fight banana weevils. Although CD has not been used there for more than 25 years, it still persists in the environment and has polluted the waterways and soil of current and older banana fields. Today, human exposure to CD in the FWI mainly arises from consuming contaminated foodstuffs. The aims of this study were to develop a physiologically based pharmacokinetic (PBPK) model in the rat and extrapolate it to humans based on available pharmacokinetic data in the literature. A comparison of simulations using the rat model with published experimental datasets showed reasonable predictability for single and repetitive doses, and, thus, it was extrapolated to humans. The human PBPK model, which has seven compartments, is able to simulate the blood concentrations of CD in human populations and estimate the corresponding external dose using the reverse dosimetry approach. The human PBPK model will make it possible to improve quantitative health risk assessments for CD contamination and reassess the current chronic toxicological reference values to protect the FWI population. [ABSTRACT FROM AUTHOR]

The goal of the present study was to assess the predictive performance of a minimal generic rat physiologically based kinetic (PBK) model based on in vitro and in silico input data to predict peak plasma concentrations (C max) upon single oral dosing. To this purpose, a dataset was generated of 3960 C max predictions for 44 compounds, applying different combinations of in vitro and in silico approaches for chemical parameterization, and comparison of the predictions to reported in vivo data. Best performance was obtained when (1) the hepatic clearance was parameterized based on in vitro measured intrinsic clearance values, (2) the method of Rodgers and Rowland for calculating partition coefficients, and (3) in silico calculated fraction unbound plasma and P app values (the latter especially for very lipophilic compounds). Based on these input data, the median C max of 32 compounds could be predicted within 10-fold of the observed C max, with 22 out of these 32 compounds being predicted within 5-fold, and 8 compounds within 2-fold. Overestimations of more than 10-fold were observed for 12 compounds, whereas no underestimations of more than 10-fold occurred. Median C max predictions were frequently found to be within 10-fold of the observed C max when the scaled unbound hepatic intrinsic clearance (Clint,u) was either higher than 20 l/h or lower than 1 l/h. Similar findings were obtained with a test set of 5 in-house BASF compounds. Overall, this study provides relevant insights in the predictive performance of a minimal PBK model based on in vitro and in silico input data. [ABSTRACT FROM AUTHOR]

We previously developed a mechanism-based pharmacokinetic (MBPK) model to characterize the PK of a lymphocyte-targeted, long-acting 3 HIV drug-combination nanoparticle (DcNP) formulation of lopinavir, ritonavir, and tenofovir. MBPK describes time-courses of plasma drug concentration and has provided an initial hypothesis for the lymphatic PK of DcNP. Because anatomical and physiological interpretation of MBPK is limited, in this Part 2, we report the development of a Physiologically Based Pharmacokinetic (PBPK) model for a detailed evaluation of the systemic and lymphatic PK of drugs associated with DcNP. The DcNP model is linked to the PBPK model presented earlier in Part 1 to account for the disposition of released free drugs. A key feature of the DcNP model is the uptake of the injected dose from the subcutaneous site to the adjacent lymphoid depot, routing through the nodes within and throughout the lymphatic network, and its subsequent passage into the blood circulation. Furthermore, the model accounts for DcNP transport to the lymph by lymphatic recirculation and mononuclear cell migration. The present PBPK model can be extended to other nano-drug combinations that target or transit through the lymphatic system. The PBPK model may allow scaling and prediction of DcNP PK in humans. [ABSTRACT FROM AUTHOR]

Aims: To develop physiologically based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) models to predict effective doses of gepotidacin in paediatrics for the treatment of pneumonic plague (Yersinia pestis). Methods: A gepotidacin PBPK model was constructed using a population‐based absorption, distribution, metabolism and excretion simulator, Simcyp®, with physicochemical and in vitro data, optimized with clinical data from a dose‐escalation intravenous (IV) study and a human mass balance study. A PopPK model was developed with pooled PK data from phase 1 studies with IV gepotidacin in healthy adults. Results: For both the PopPK and PBPK models, body weight was found to be a key covariate affecting gepotidacin clearance. With PBPK, ~90% of the predicted PK for paediatrics fell between the 5th and 95th percentiles of adult values except for subjects weighing ≤5 kg. PopPK‐simulated paediatric means for Cmax and AUC(0‐τ) were similar to adult exposures across various weight brackets. The proposed dosing regimens were weight‐based for subjects ≤40 kg and fixed‐dose for subjects >40 kg. Comparison of observed and predicted exposures in adults indicated that both PBPK and PopPK models achieved similar AUC and Cmax for a given dose, but the Cmax predictions with PopPK were slightly higher than with PBPK. The two models differed on dose predictions in children <3 months old. The PopPK model may be suboptimal for low age groups due to the absence of maturation characterization of drug‐metabolizing enzymes involved with clearance in adults. Conclusions: Both PBPK and PopPK approaches can reasonably predict gepotidacin exposures in children. [ABSTRACT FROM AUTHOR]

Drug-combination nanoparticles (DcNP) allow the formulation of multiple HIV drugs in one injectable. In nonhuman primates (NHP), all drugs in DcNP have demonstrated long-acting pharmacokinetics (PK) in the blood and lymph nodes, rendering it suitable for a Targeted Long-acting Antiretroviral Therapy (TLC-ART). To support the translation of TLC-ART into the clinic, the objective is to present a physiologically based PK (PBPK) model tool to control mechanisms affecting the rather complex DcNP-drug PK. Two species contribute simultaneously to the drug PK: drugs that dissociate from DcNP (Part 1) and drugs retained in DcNP (Part 2, presented separately). Here, we describe the PBPK modeling of the nanoparticle-free drugs. The free-drug model was built on subcutaneous injections of suspended lopinavir, ritonavir, and tenofovir in NHP, and validated by external experiments. A novelty was the design of a lymphatic network as part of a whole-body PBPK system which included major lymphatic regions: the cervical, axillary, hilar, mesenteric, and inguinal nodes. This detailed/regionalized description of the lymphatic system and mononuclear cells represents an unprecedented level of prediction that renders the free-drug model extendible to other small-drug molecules targeting the lymphatic system at both the regional and cellular levels. [ABSTRACT FROM AUTHOR]

Purpose: We have hypothesized that a high concentration of circulating monocytes and macrophages may contribute to the fast weight-based clearance of monoclonal antibodies (mAbs) in young children. Exploring this hypothesis, this work uses modeling to clarify the role of monocytes and macrophages in the elimination of mAbs. Methods: Leveraging pre-clinical data from mice, a minimal physiologically-based pharmacokinetic model was developed to characterize mAb uptake and FcRn-mediated recycling in circulating monocytes, macrophages, and endothelial cells. The model characterized IgG disposition in complex scenarios of site-specific FcRn deletion and variable endogenous IgG levels. Evaluation was performed for predicting IgG disposition with co-administration of high dose IVIG. A one-at-a-time sensitivity analysis quantified the role of relevant cellular parameters on IgG elimination in various scenarios. Results: The plasma AUC of mAbs was highly sensitive to endothelial cell parameters, but had near-nil sensitivity to monocyte and macrophage parameters, even in scenarios with 90% loss of FcRn expression/activity. In mice with normal FcRn expression, simulations suggest that less than 2% of an IV dose is eliminated in macrophages, while endothelial cells are predicted to dominate mAb elimination. Conclusions: The model suggests that the role of monocytes and macrophages in IgG homeostasis includes extensive uptake and highly efficient FcRn-mediated protection, but not appreciable degradation when FcRn is present. Therefore, it is very unlikely that a high concentration of circulating monocytes can contribute to explaining the fast weight-based clearance of mAbs in very young children, even if FcRn expression/activity was 90% lower in children than in adults. [ABSTRACT FROM AUTHOR]

In vitro screening for pharmacological activity of existing drugs showed chloroquine and hydroxychloroquine to be effective against severe acute respiratory syndrome coronavirus 2. Oral administration of these compounds to obtain desired pulmonary exposures resulted in dose-limiting systemic toxicity in humans. However, pulmonary drug delivery enables direct and rapid administration to obtain higher local tissue concentrations in target tissue. In this work, inhalable formulations for thermal aerosolization of chloroquine and hydroxychloroquine were developed, and their physicochemical properties were characterized. Thermal aerosolization of 40 mg/mL chloroquine and 100 mg/mL hydroxychloroquine formulations delivered respirable aerosol particle sizes with 0.15 and 0.33 mg per 55 mL puff, respectively. In vitro toxicity was evaluated by exposing primary human bronchial epithelial cells to aerosol generated from Vitrocell. An in vitro exposure to 7.24 μg of chloroquine or 7.99 μg hydroxychloroquine showed no significant changes in cilia beating, transepithelial electrical resistance, and cell viability. The pharmacokinetics of inhaled aerosols was predicted by developing a physiologically based pharmacokinetic model that included a detailed species-specific respiratory tract physiology and lysosomal trapping. Based on the model predictions, inhaling emitted doses comprising 1.5 mg of chloroquine or 3.3 mg hydroxychloroquine three times a day may yield therapeutically effective concentrations in the lung. Inhalation of higher doses further increased effective concentrations in the lung while maintaining lower systemic concentrations. Given the theoretically favorable risk/benefit ratio, the clinical significance for pulmonary delivery of aerosolized chloroquine and hydroxychloroquine to treat COVID-19 needs to be established in rigorous safety and efficacy studies. [ABSTRACT FROM AUTHOR]

Chloroquine (CQ) phosphate has been suggested to be clinically effective in the treatment of coronavirus disease 2019 (COVID-19). To develop a physiologically-based pharmacokinetic (PBPK) model for predicting tissue distribution of CQ and apply it to optimize dosage regimens, a PBPK model, with parameterization of drug distribution extrapolated from animal data, was developed to predict human tissue distribution of CQ. The physiological characteristics of time-dependent accumulation was mimicked through an active transport mechanism. Several dosing regimens were proposed based on PBPK simulation combined with known clinical exposure–response relationships. The model was also validated by clinical data from Chinese patients with COVID-19. The novel PBPK model allows in-depth description of the pharmacokinetics of CQ in several key organs (lung, heart, liver, and kidney), and was applied to design dosing strategies in patients with acute COVID-19 (Day 1: 750 mg BID, Days 2–5: 500 mg BID, CQ phosphate), patients with moderate COVID-19 (Day 1: 750 mg and 500 mg, Days 2–3: 500 mg BID, Days 4–5: 250 mg BID, CQ phosphate), and other vulnerable populations (e.g., renal and hepatic impairment and elderly patients, Days 1–5: 250 mg BID, CQ phosphate). A PBPK model of CQ was successfully developed to optimize dosage regimens for patients with COVID-19.

Abstract Background This study aimed to assess the pediatric lisinopril doses using an adult physiological based pharmacokinetic (PBPK) model. As the empirical rules of dose calculation cannot calculate gender-specific pediatric doses and ignores the age-related physiological differences. Methods A PBPK model of lisinopril for the healthy adult population was developed for oral (fed and fasting) and IV administration using PK-Sim MoBI® and was scaled down to a virtual pediatric population for prediction of lisinopril doses in neonates to infants, infants to toddler, children at pre-school age, children at school age and the adolescents. The pharmacokinetic parameters were predicted for the above groups at decremental doses of 20 mg, 10 mg, 5 mg, 2.5 mg, and 1.5 mg in order to accomplish doses producing the pharmacokinetic parameters, similar (or comparable) to that of the adult population. The above simulated pediatric doses were compared to the doses computed using the conventional four methods, such as Young’s rule, Clark’s rule, and weight-based and body surface area-based equations and the dose reported in different studies. Results Though the doses predicted for all subpopulations of children were comparable to those calculated by Young’s rule, yet the conventional methods overestimated the pediatric doses when compared to the respective PBPK-predicted doses. The findings of previous real time pharmacokinetic studies in pediatric patients supported the present simulated dose. Conclusion Thus, PBPK seems to have predictability potential for pediatric dose since it takes into consideration the physiological changes related to age and gender.

Adequate prediction of fetal exposure of drugs excreted by the kidney requires the incorporation of time-varying renal function parameters into a pharmacokinetic model. Published data on measurements of fetal urinary production rate (FUPR) and creatinine at various gestational ages were collected and integrated for prediction of the fetal glomerular filtration rate (GFR). The predicted GFR values were then compared to neonatal values recorded at birth. Collected data for FUPR across different gestational ages using both 3D (N = 517) and 2D (N = 845) ultrasound methods showed that 2D techniques yield significantly lower estimates of FUPR than 3D (p < 0.0001). A power law function was shown to best capture the change in FUPR with fetal age (FA) for both 2D (FUPR2D(mLmin)=0.000169 FA2.19); and 3D (FUPR3D (mLmin)= 3.21×10-7 FA4.21) data. The predicted FUPR based on the observed 3D data was shown to be strongly linearly related (R2 = 0.95) to measured values of amniotic creatinine concentration (N = 664). The FUPR3D data together with creatinine levels in the fetal urine and serum resulted in median predicted fetal GFR values of 0.47, 1.2, 2.5, and 4.9 ml/min at 23, 28, 33, and 38 weeks of fetal age (50% CV), respectively. These values are in good agreement with neonatal values observed immediately at birth. The derived FUPR and creatinine functions can be utilized to assess fetal renal maturation and predict fetal renal clearance.

Linezolid is used off-label for treatment of central nervous system infections. However, its pharmacokinetics and target attainment in cranial cerebrospinal fluid (CSF) in tuberculous meningitis patients is unknown. This study aimed to predict linezolid cranial CSF concentrations and assess attainment of pharmacodynamic (PD) thresholds (AUC:MIC of >119) in plasma and cranial CSF of adults and children with tuberculous meningitis. A physiologically based pharmacokinetic (PBPK) model was developed to predict linezolid cranial CSF profiles based on reported plasma concentrations. Simulated steady-state PK curves in plasma and cranial CSF after linezolid doses of 300 mg BID, 600 mg BID, and 1200 mg QD in adults resulted in geometric mean AUC:MIC ratios in plasma of 118, 281, and 262 and mean cranial CSF AUC:MIC ratios of 74, 181, and 166, respectively. In children using ~10 mg/kg BID linezolid, AUC:MIC values at steady-state in plasma and cranial CSF were 202 and 135, respectively. Our model predicts that 1200 mg per day in adults, either 600 mg BID or 1200 mg QD, results in reasonable (87%) target attainment in cranial CSF. Target attainment in our simulated paediatric population was moderate (56% in cranial CSF). Our PBPK model can support linezolid dose optimization efforts by simulating target attainment close to the site of TBM disease.

Background: Epirubicin is an anthracycline antineoplastic drug that is primarily used in combination therapies for the treatment of breast, gastric, lung and ovarian cancers and lymphomas. Epirubicin is administered intravenously (IV) over 3 to 5 min once every 21 days with dosing based on body surface area (BSA; mg/m2). Despite accounting for BSA, marked inter-subject variability in circulating epirubicin plasma concentration has been reported. Methods: In vitro experiments were conducted to determine the kinetics of epirubicin glucuronidation by human liver microsomes in the presence and absence of validated UGT2B7 inhibitors. A full physiologically based pharmacokinetic model was built and validated using Simcyp® (version 19.1, Certara, Princeton, NJ, USA). The model was used to simulate epirubicin exposure in 2000 Sim-Cancer subjects over 158 h following a single intravenous dose of epirubicin. A multivariable linear regression model was built using simulated demographic and enzyme abundance data to determine the key drivers of variability in systemic epirubicin exposure. Results: Multivariable linear regression modelling demonstrated that variability in simulated systemic epirubicin exposure following intravenous injection was primarily driven by differences in hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex. By accounting for these factors, it was possible to explain 87% of the variability in epirubicin in a simulated cohort of 2000 oncology patients. Conclusions: The present study describes the development and evaluation of a full-body PBPK model to assess systemic and individual organ exposure to epirubicin. Variability in epirubicin exposure was primarily driven by hepatic and renal UGT2B7 expression, plasma albumin concentration, age, BSA, GFR, haematocrit and sex.

A physiologically based biopharmaceutic model (PBBM) of a modified-release formulation of theophylline (Uniphyllin Continus® 200 mg tablet) was developed and implemented to predict the pharmacokinetic (PK) data of healthy male volunteers by integrating dissolution profiles measured in a biorelevant in vitro model: the Dynamic Colon Model (DCM). The superiority of the DCM over the United States Pharmacopeia (USP) Apparatus II (USP II) was demonstrated by the superior predictions for the 200 mg tablet (average absolute fold error (AAFE): 1.1–1.3 (DCM) vs. 1.3–1.5 (USP II). The best predictions were obtained using the three motility patterns (antegrade and retrograde propagating waves, baseline) in the DCM, which produced similar PK profiles. However, extensive erosion of the tablet occurred at all agitation speeds used in USP II (25, 50 and 100 rpm), resulting in an increased drug release rate in vitro and overpredicted PK data. The PK data of the Uniphyllin Continus® 400 mg tablet could not be predicted with the same accuracy using dissolution profiles from the DCM, which might be explained by differences in upper gastrointestinal (GI) tract residence times between the 200 and 400 mg tablets. Thus, it is recommended that the DCM be used for dosage forms in which the main release phenomena take place in the distal GI tract. However, the DCM again showed a better performance based on the overall AAFE compared to the USP II. Regional dissolution profiles within the DCM cannot currently be integrated into Simcyp®, which might limit the predictivity of the DCM. Thus, further compartmentalization of the colon within PBBM platforms is required to account for observed intra-regional differences in drug distribution.

Mycotoxins such as aflatoxin B1 (AFB1) are secondary fungal metabolites present in food commodities and part of one’s daily exposure, especially in certain regions, e.g., sub-Saharan Africa. AFB1 is mostly metabolised by cytochrome P450 (CYP) enzymes, namely, CYP1A2 and CYP3A4. As a consequence of chronic exposure, it is interesting to check for interactions with drugs taken concomitantly. A physiologically based pharmacokinetic (PBPK) model was developed based on the literature and in-house-generated in vitro data to characterise the pharmacokinetics (PK) of AFB1. The substrate file was used in different populations (Chinese, North European Caucasian and Black South African), provided by SimCYP® software (v21), to evaluate the impact of populations on AFB1 PK. The model’s performance was verified against published human in vivo PK parameters, with AUC ratios and Cmax ratios being within the 0.5–2.0-fold range. Effects on AFB1 PK were observed with commonly prescribed drugs in South Africa, leading to clearance ratios of 0.54 to 4.13. The simulations revealed that CYP3A4/CYP1A2 inducer/inhibitor drugs might have an impact on AFB1 metabolism, altering exposure to carcinogenic metabolites. AFB1 did not have effects on the PK of drugs at representative exposure concentrations. Therefore, chronic AFB1 exposure is unlikely to impact the PK of drugs taken concomitantly.

Tegoprazan is a novel potassium-competitive acid blocker. This study investigated the effect of drug–drug interaction on the pharmacokinetics and pharmacodynamics of tegoprazan co-administered with amoxicillin and clarithromycin, the first-line therapy for the eradication of Helicobacter pylori, using physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) modeling. The previously reported tegoprazan PBPK/PD model was modified and applied. The clarithromycin PBPK model was developed based on the model provided by the SimCYP® compound library. The amoxicillin model was constructed using the middle-out approach. All of the observed concentration–time profiles were covered well by the predicted profiles with the 5th and 95th percentiles. The mean ratios of predicted to observed PK parameters, including the area under the curve (AUC), maximum plasma drug concentration (Cmax), and clearance, were within the 30% intervals for the developed models. Two-fold ratios of predicted fold-changes of Cmax and AUC from time 0 to 24 h to observed data were satisfied. The predicted PD endpoints, including median intragastric pH and percentage holding rate at pH above 4 or 6 on day 1 and day 7, were close to the corresponding observed data. This investigation allows evaluation of the effects of CYP3A4 perpetrators on tegoprazan PK and PD changes, thus providing clinicians with the rationale for co-administration dosing adjustment.

The progress that has been made in computer science positioned in silico studies as an important and well-recognized methodology in the drug discovery and development process. It has numerous advantages in terms of costs and also plays a huge impact on the way the research is conducted since it can limit the use of animal models leading to more sustainable research. Currently, human trials are already being partly replaced by in silico trials. EMA and FDA are both endorsing these studies and have been providing webinars and guidance to support them. For instance, PBPK modeling studies are being used to gather data on drug interactions with other drugs and are also being used to support clinical and regulatory requirements for the pediatric population, pregnant women, and personalized medicine. This trend evokes the need to understand the role of in silico studies in vaccines, considering the importance that these products achieved during the pandemic and their promising hope in oncology. Vaccines are safer than other current oncology treatments. There is a huge variety of strategies for developing a cancer vaccine, and some of the points that should be considered when designing the vaccine technology are the following: delivery platforms (peptides, lipid-based carriers, polymers, dendritic cells, viral vectors, etc.), adjuvants (to boost and promote inflammation at the delivery site, facilitating immune cell recruitment and activation), choice of the targeted antigen, the timing of vaccination, the manipulation of the tumor environment, and the combination with other treatments that might cause additive or even synergistic anti-tumor effects. These and many other points should be put together to outline the best vaccine design. The aim of this article is to perform a review and comprehensive analysis of the role of in silico studies to support the development of and design of vaccines in the field of oncology and infectious diseases. The authors intend to perform a literature review of all the studies that have been conducted so far in preparing in silico models and methods to support the development of vaccines. From this point, it was possible to conclude that there are few in silico studies on vaccines. Despite this, an overview of how the existing work could support the design of vaccines is described.

The rapid onset of action of nifedipine causes a precipitous reduction in blood pressure leading to adverse effects associated with reflex sympathetic nervous system (SNS) activation, including tachycardia and worsening myocardial and cerebrovascular ischemia. As a result, short acting nifedipine preparations are not recommended. However, importantly, there are no modified release preparations of nifedipine authorised for paediatric use, and hence a paucity of clinical studies reporting pharmacokinetics data in paediatrics. Pharmacokinetic parameters may differ significantly between children and adults due to anatomical and physiological differences, often resulting in sub therapeutic and/or toxic plasma concentrations of medication. However, in the field of paediatric pharmacokinetics, the use of pharmacokinetic modelling, particularly physiological-based pharmacokinetics (PBPK), has revolutionised the ability to extrapolate drug pharmacokinetics across age groups, allowing for pragmatic determination of paediatric plasma concentrations to support drug licensing and clinical dosing. In order to pragmatically assess the translation of resultant dissolution profiles to the paediatric populations, virtual clinical trials simulations were conducted. In the context of formulation development, the use of PBPK modelling allowed the determination of optimised formulations that achieved plasma concentrations within the target therapeutic window throughout the dosing strategy. A 5 mg sustained release mini-tablet was successfully developed with the duration of release extending over 24 h and an informed optimised dosing strategy of 450 µg/kg twice daily. The resulting formulation provides flexible dosing opportunities, improves patient adherence by reducing frequent administration burden and enhances patient safety profiles by maintaining efficacious levels of consistent drug plasma levels over a sustained period of time.

An array physiologically-based pharmacokinetic (PBPK) model represents a streamlined method to simultaneously quantify dosimetry of multiple compounds. To predict internal dosimetry of jet fuel components simultaneously, an array PBPK model was coded to simulate inhalation exposures to one or more selected compounds: toluene, ethylbenzene, xylenes, n-nonane, n-decane, and naphthalene. The model structure accounts for metabolism of compounds in the lung and liver, as well as kinetics of each compound in multiple tissues, including the cochlea and brain regions associated with auditory signaling (brainstem and temporal lobe). The model can accommodate either diffusion-limited or flow-limited kinetics (or a combination), allowing the same structure to be utilized for compounds with different characteristics. The resulting model satisfactorily simulated blood concentration and tissue dosimetry data from multiple published single chemical rat studies. The model was then utilized to predict tissue kinetics for the jet fuel hearing loss study (JTEH A, 25:1-14). The model was also used to predict rat kinetic comparisons between hypothetical exposures to JP-8 or a Virent Synthesized Aromatic Kerosene (SAK):JP-8 50:50 blend at the occupational exposure limit (200 mg/m3). The array model has proven useful for comparing potential tissue burdens resulting from complex mixture exposures.