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Tyrosine kinase inhibitors (TKIs) have demonstrated significant efficacy against various types of cancers through molecular targeting mechanisms. Over the past 22 years, more than 100 TKIs have been approved for the treatment of various types of cancer indicating the significant progress achieved in this research area. Despite having significant efficacy and ability to target multiple pathways, TKIs administration is associated with challenges. There are reported inconsistencies between observed food effect and labeling administration, challenges of concomitant administration with acid-reducing agents (ARA), pill burden and dosing frequency. In this context, the objective of present review is to visit administration challenges of TKIs and effective ways to tackle them. We have gathered data of 94 TKIs approved in between 2000 and 2022 with respect to food effect, ARA impact, administration schemes (food and PPI restrictions), number of pills per day and administration frequency. Further, trend analysis has been performed to identify inconsistencies in the labeling with respect to observed food effect, molecules exhibiting ARA impact, in order to identify solutions to remove these restrictions through novel formulation approaches. Additionally, opportunities to reduce number of pills per day and dosing frequency for better patient compliance were suggested using innovative formulation interventions. Finally, utility of physiologically based pharmacokinetic modeling (PBPK) for rationale formulation development was discussed with literature reported examples. Overall, this review can act as a ready-to-use-guide for the formulation, biopharmaceutics scientists and medical oncologists to identify opportunities for innovation for TKIs. [ABSTRACT FROM AUTHOR]

This study investigated the impact of gastro-intestinal fluid volume and bile salt (BS) concentration on the dissolution of carbamazepine (CBZ) immediate release (IR) 100 mg tablets and to integrate these in vitro biorelevant dissolution profiles into physiologically based pharmacokinetic modelling (PBPK) in pediatric and adult populations to determine the biopredictive dissolution profile. Dissolution profiles of CBZ IR tablets (100 mg) were generated in 50–900 mL biorelevant adult fasted state simulated gastric and intestinal fluid (Ad-FaSSGF and Ad-FaSSIF), also in three alternative compositions of biorelevant pediatric FaSSGF and FaSSIF medias at 200 mL. This study found that CBZ dissolution was poorly sensitive to changes in the composition of the biorelevant media, where dissimilar dissolution (F2 = 46.2) was only observed when the BS concentration was changed from 3000 to 89 μM (Ad-FaSSIF vs Ped-FaSSIF 50% 14 BS). PBPK modeling demonstrated the most predictive dissolution volume and media composition to forecast the PK was 500 mL of Ad-FaSSGF/Ad-FaSSIF media for adults and 200 mL Ped-FaSSGF/FaSSIF media for pediatrics. A virtual bioequivalence simulation was conducted by using Ad-FaSSGF and/or Ad-FaSSIF 500 mL or Ped-FaSSGF and/or Ped-FaSSIF 200 mL dissolution data for CBZ 100 mg (reference and generic test) IR product. The CBZ PBPK models showed bioequivalence of the product. This study demonstrates that the integration of biorelevant dissolution data can predict the PK profile of a poorly soluble drug in both populations. Further work using more pediatric drug products is needed to verify biorelevant dissolution data to predict the in vivo performance in pediatrics. [ABSTRACT FROM AUTHOR]

Current regulatory guidelines on drug-food interactions recommend an early assessment of food effect to inform clinical dosing instructions, as well as a pivotal food effect study on the to-be-marketed formulation if different from that used in earlier trials. Study waivers are currently only granted for BCS class 1 drugs. Thus, repeated food effect studies are prevalent in clinical development, with the initial evaluation conducted as early as the first-in-human studies. Information on repeated food effect studies is not common in the public domain. The goal of the work presented in this manuscript from the Food Effect PBPK IQ Working Group was to compile a dataset on these studies across pharmaceutical companies and provide recommendations on their conduct. Based on 54 studies collected, we report that most of the repeat food effect studies do not result in meaningful differences in the assessment of the food effect. Seldom changes observed were more than twofold. There was no clear relationship between the change in food effect and the formulation change, indicating that in most cases, once a compound is formulated appropriately within a specific formulation technology, the food effect is primarily driven by inherent compound properties. Representative examples of PBPK models demonstrate that following appropriate validation of the model with the initial food effect study, the models can be applied to future formulations. We recommend that repeat food effect studies should be approached on a case-by-case basis taking into account the totality of the evidence including the use of PBPK modeling. [ABSTRACT FROM AUTHOR]

In lieu of large bioequivalence studies and exposing healthy postmenopausal women to additional drug exposure for elagolix coadministered with hormonal add-back therapy, physiologically based pharmacokinetic (PBPK) modeling was used with in vitro dissolution data to test for virtual bioequivalence. For endometriosis, elagolix is approved at doses of 150 mg once daily and 200 mg twice daily as a tablet. As a combination therapy, two individual tablets, consisting of an elagolix tablet and an estradiol/norethindrone acetate 1/0.5 mg (E2/NETA) tablet, were utilized in Phase 3 endometriosis trials. However, the commercial combination drug products consist of a morning capsule (containing an elagolix tablet and E2/NETA tablet as a fixed-dose combination capsule, AM capsule) and an evening capsule (consisting of an elagolix tablet, PM capsule). In vitro dissolution profiles were dissimilar for the tablet and capsule formulations; thus, in vivo bioequivalence studies or a bioequivalence waiver would have been required. To simulate virtual cross-over, bioequivalence trials, in vitro dissolution data was incorporated into a previously verified PBPK model. The updated PBPK model was externally validated using relevant bioequivalence study data. Based on results of the virtual bioequivalence simulations, the commercial drug product capsules met the bioequivalence criteria of 0.80–1.25 when compared to the reference tablets. This was a novel example where PBPK modeling was utilized along with in vitro dissolution data to demonstrate virtual bioequivalence in support of a regulatory bioequivalence waiver. [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]

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]

The purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model predicting the pharmacokinetics (PK) of different compounds in pregnant subjects. This model considers the differences in tissue sizes, blood flow rates, enzyme expression levels, glomerular filtration rates, plasma protein binding, and other factors affected during pregnancy in both the maternal and fetal models. The PBPKPlus™ module in GastroPlus® was used to model the PK of cefuroxime and cefazolin. For both compounds, the model was first validated against PK data in healthy non-pregnant volunteers and then applied to predict pregnant groups PK. The model accurately described the PK in both non-pregnant and pregnant groups and explained well differences in the plasma concentration due to pregnancy. The fetal plasma and amniotic fluid concentrations were also predicted reasonably well at different stages of pregnancy. This work describes the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for compounds excreted renally. The prediction for pregnant groups is also improved when the model is calibrated with postpartum or non-pregnant female group if such data are available. [ABSTRACT FROM AUTHOR]

Food can alter drug absorption and impact safety and efficacy. Besides conducting clinical studies, in vitro approaches such as biorelevant solubility and dissolution testing and in vivo dog studies are typical approaches to estimate a drug's food effect. The use of physiologically based pharmacokinetic models has gained importance and is nowadays a standard tool for food effect predictions at preclinical and clinical stages in the pharmaceutical industry. This manuscript is part of a broader publication from the IQ Consortium's food effect physiologically based pharmacokinetic model (PBPK) modeling working group and complements previous publications by focusing on cases where the food effect was predicted with low confidence. Pazopanib-HCl, trospium-Cl, and ziprasidone-HCl served as model compounds to provide insights into why several food effect predictions failed in the first instance. Furthermore, the manuscript depicts approaches whereby PBPK-based food effect predictions may be improved. These improvements should focus on the PBPK model functionality, especially better reflecting fasted- and fed-state gastric solubility, gastric re-acidification, and complex mechanisms related to gastric emptying of drugs. For improvement of in vitro methodologies, the focus should be on the development of more predictive solubility, supersaturation, and precipitation assays. With regards to the general PBPK modeling methodology, modelers should account for the full solubility profile when modeling ionizable compounds, including common ion effects, and apply a straightforward strategy to account for drug precipitation. [ABSTRACT FROM AUTHOR]

Development of comprehensive and updated quantitative relationships between physiological parameters and age for pediatrics remains to be accomplished. Towards this goal, we have performed a thorough literature search and collected published data on organ weights and organ blood flow rates for 0–20-year-old male and female human subjects. The data were used to develop continuous relationships between physiological parameters and age, using a single form of mathematical equation. Four sets of equations (0–2 years male, 0–2 years female, 2–20 years male, 2–20 years female) for the body weight vs. age, height vs. age, and organ weight vs. age relationships and 2 sets of equations (0–20 years male, 0–20 years female) for organ flow rate vs. age relationship were developed. The variability of each physiological parameter was also estimated, and the equations allow simulation of a virtual population for a specific age, weight, and sex. We further compared the physiological parameters vs. age curves simulated using our equations to the existing databases (Simcyp Simulator and PK-Sim). The predicted physiological parameters were comparable between our study and the existing databases, validating our equation's utility. Additionally, we described body weight-normalized organ weights and organ blood flow rates as a function of age, to provide an insight into how the contribution of each organ towards total body weight and total blood flow changes throughout ontogenesis. The physiological parameter database and equations presented here can serve as an open source to facilitate the development of pediatric physiologically based pharmacokinetic models. [ABSTRACT FROM AUTHOR]

Over the last 10 years, 40% of approved oral drugs exhibited a significant effect of food on their pharmacokinetics (PK) and currently the only method to characterize the effect of food on drug absorption, which is recognized by the authorities, is to conduct a clinical evaluation. Within the pharmaceutical industry, there is a significant effort to predict the mechanism and clinical relevance of a food effect. Physiologically based pharmacokinetic (PBPK) models combining both drug-specific and physiology-specific data have been used to predict the effect of food on absorption and to reveal the underlying mechanisms. This manuscript provides detailed descriptions of how a middle-out modeling approach, combining bottom-up in vitro-based predictions with limited top-down fitting of key model parameters for clinical data, can be successfully used to predict the magnitude and direction of food effect when it is predicted poorly by a bottom-up approach. For nefazodone, a mechanistic clearance for the gut and liver was added, for furosemide, an absorption window was introduced, and for aprepitant, the biorelevant solubility was refined using multiple solubility measurements. In all cases, these adjustments were supported by literature data and showcased a rational approach to assess the factors limiting absorption and exposure. [ABSTRACT FROM AUTHOR]

Vismodegib displays unique pharmacokinetic characteristics including saturable plasma protein binding to alpha-1 acid glycoprotein (AAG) and apparent time-dependent bioavailability leading to non-linear PK with dose and time, significantly faster time to steady-state and lower than predicted accumulation. Given these unique characteristics, a PBPK model was developed to explore mechanistic insights into saturable protein binding and complex oral absorption processes and de-convolute the impact of these independent non-linear processes on vismodegib exposure. Simcyp V18 was used for model development; oral absorption was characterized using the multi-layer gut wall (M-ADAM) model and mechanistic permeability model, incorporating transport across an unstirred boundary layer (UBL) between the luminal fluid and enterocyte in each segment of the gastrointestinal tract. PBPK simulations were compared with observed PK data from clinical trials in oncology patients and healthy subjects. Saturation of vismodegib protein binding to AAG led to substantially lower total drug accumulation, time to steady-state, and Csstotal. For free exposure, Cssfree and accumulation were unchanged, but time to steady-state was substantially reduced. Vismodegib oral absorption declined with both dose and dosing frequency; the concentration gradient driving vismodegib oral absorption declined with multiple doses, leading to a 32% decrease in vismodegib fa from first dose to steady-state. Fed simulations suggested that increased solubility and dissolution are partially offset by reduced permeability across the UBL due to slower diffusion of micelle-bound drug. This work demonstrates the value of PBPK modeling to simultaneously capture and de-convolute multi-faceted absorption and disposition processes and provide mechanistic insights for compounds with complex pharmacokinetics. [ABSTRACT FROM AUTHOR]

Physiologically-based pharmacokinetic (PBPK) modelling provides an integrated framework to predict the disposition of small molecule drugs in children and is increasingly being used for dose recommendation and optimal design of paediatric studies and in regulatory submissions. Existing paediatric PBPK models can be adopted to describe the disposition of therapeutic proteins (TPs) in children by incorporating information on age-related changes of additional physiological and biological parameters (e.g. endogenous IgG, neonatal Fc receptor, lymph flow). In this study, physiological parameters were collated from literature and evaluated for any age-dependent trends. The age-dependent physiological parameters were used to construct a paediatric PBPK model for TPs. The model was then used to predict the pharmacokinetics of recombinant human erythropoietin (EPO), infliximab, etanercept, basiliximab, anakinra and enfuvirtide in paediatric subjects. The developed paediatric PBPK model predicted the drug concentration-time profiles reasonably well in full-term neonates (clinical PK data only available for EPO), infants, children and adolescents with the ratios of predicted over observed clearance values within 1.5-fold and 25 out of 26 clearance predictions were within 0.8- to 1.25-fold of the observed values. The clinically reported data are required to further assess the predictive accuracy of PK for Fc-containing proteins in term-born children younger than 2 months. This study demonstrates the ability of PBPK models accounting for age-dependent changes in relevant parameters to predict the pharmacokinetics of different types of TPs in paediatrics. The information gained from the PBPK models described here can facilitate our understanding of the complexities of TPs' disposition during growth and development. [ABSTRACT FROM AUTHOR]

Using physiologically based pharmacokinetic (PBPK) modeling and simulations, this study estimated the exposure of sunitinib and its active metabolite SU012662 in pediatric patients. A PBPK simulator, SimCYP, was used to develop and validate the pharmacokinetic models. Model development employed a combined "bottom–up" and "top–down" approach to fully utilize the available in vitro or in silico experimental data and in vivo observed clinical data. First, the PBPK model for sunitinib was established, then the cytochrome P450 3A4–mediated metabolism of sunitinib was used as the input for SU012662. PBPK models were validated using pharmacokinetics of sunitinib and SU012662 from one study in adult patients with solid tumors and three clinical trials in pediatric patients with solid or gastrointestinal stromal tumors. The models were further used to predict the exposure of sunitinib and SU012662 by pediatric age groups. The PBPK models for sunitinib and SU012662 developed based on pharmacokinetic characteristics in adults successfully predicted the observed in vivo pharmacokinetics of sunitinib and SU012662 in both adults and pediatric patients. Based on the SimCYP model predictions, a daily dose of 20 mg/m2 will produce sunitinib and SU012662 total exposures in pediatric patients similar to those in adults with gastrointestinal stromal tumor treated with a clinical dose of 50 mg once daily. [ABSTRACT FROM AUTHOR]

In physiologically based pharmacokinetic (PBPK) modelling, the large number of input parameters, limited amount of available data and the structural model complexity generally hinder simultaneous estimation of uncertain and/or unknown parameters. These parameters are generally subject to estimation. However, the approaches taken for parameter estimation vary widely. Global sensitivity analyses are proposed as a method to systematically determine the most influential parameters that can be subject to estimation. Herein, a global sensitivity analysis was conducted to identify the key drug and physiological parameters influencing drug disposition in PBPK models and to potentially reduce the PBPK model dimensionality. The impact of these parameters was evaluated on the tissue-to-unbound plasma partition coefficients (Kpus) predicted by the Rodgers and Rowland model using Latin hypercube sampling combined to partial rank correlation coefficients (PRCC). For most drug classes, PRCC showed that LogP and fraction unbound in plasma (fup) were generally the most influential parameters for Kpu predictions. For strong bases, blood:plasma partitioning was one of the most influential parameter. Uncertainty in tissue composition parameters had a large impact on Kpu and Vss predictions for all classes. Among tissue composition parameters, changes in Kpu outputs were especially attributed to changes in tissue acidic phospholipid concentrations and extracellular protein tissue:plasma ratio values. In conclusion, this work demonstrates that for parameter estimation involving PBPK models and dimensionality reduction purposes, less influential parameters might be assigned fixed values depending on the parameter space, while influential parameters could be subject to parameters estimation. [ABSTRACT FROM AUTHOR]

FDA's Orange Book lists 17 currently marketed active pharmaceutical ingredients (API) formulated within ophthalmic suspensions in which a majority has 90% or more of the API undissolved. We used an ocular physiologically based pharmacokinetic (O-PBPK) model to compare a suspension with a solution for ophthalmic products with dexamethasone (Dex) as the model drug. Simulations with a Dex suspension O-PBPK model previously verified in rabbit were used to characterize the consequences of drug clearance mechanism in the precorneal compartment on pharmacokinetic (PK) exposure and to assess the ocular and systemic PK characteristics of ophthalmic suspensions with different strengths or magnitudes of viscosity. O-PBPK-based simulations show that (1) Dex suspension 0.05% has a 2.5- and 5-fold higher AUC in aqueous humor and plasma, respectively, than the Dex saturated solution; (2) strength increase by 5- and 10-fold induces a respective 2.2- and 3.3-fold increase in aqueous humor and 4.4- and 8.6-fold increase in plasma Cmax and AUC; and (3) increasing formulation viscosity (from 1.6 to 75 cP) causes an overall increase in API available for absorption in the cornea resulting in a higher ocular Cmax and AUC with no significant impact on systemic exposure. This research demonstrates that solid particles present in a suspension can not only help to achieve a higher ocular exposure but also unfavorably raise systemic exposure. A model able to correlate formulation changes to both ocular and plasma exposure is a necessary tool to support ocular product development taking into consideration both local efficacy and systemic safety aspects. [ABSTRACT FROM AUTHOR]

Active uptake mediated by organic anion transporter 2 (OAT2) has been previously hypothesized as a key player in hepatic disposition of its substrates. Previous studies have shown that another hepatic uptake transporter, organic anion transporting polypeptides (OATP) 1B1, significantly elevates liver concentrations of drugs transported by it. As tissue concentration typically governs pharmacodynamics, drug-drug interactions, and toxicity in the liver, it is important to understand if OAT2 functions similarly to OATP1B1 in raising liver exposure. Since this is a research problem that cannot be easily assessed in clinical studies at this time, here we estimated human liver exposure of an OAT2 substrate meloxicam using a deduction method based on physiologically based pharmacokinetic (PBPK) modeling of clinical systemic exposure data. Although in vitro data suggest that OAT2-mediated active uptake is involved in meloxicam disposition, the modeling result concludes that its unbound liver exposure is unlikely significantly different from its unbound systemic exposure. This conclusion is further supported by data and modeling from a terminal monkey study and in vitro hepatocyte studies with bovine serum albumin. Overall, based on currently available data, we do not expect that OAT2 has a strong impact on the liver exposure of meloxicam. [ABSTRACT FROM AUTHOR]

Huge variation of drug transporter abundance was seen in the literature, making PBPK prediction difficult when transporters play a major role. Among multiple factors such as membrane fraction, digestion, and peptide selection that contributed to such variation, peptide selection is the least discussed. Herein, a strategy was established by using a small amount of purified protein standard to select a peptide with near 100% digestion efficiency for quantitation of a transporter protein MDR1. The impact of native membrane protein's tertiary structure on the digestion efficiency of surrogate peptides of MDR1 was investigated. Peptides in more solvent accessible regions are found to be digested much more efficiently than those in large stretches of helical structures. The concentration of peptide EALDESIPPVSFWR(EAL) in the most solvent accessible linker region of MDR1 was found closest to the true protein concentration. When using EAL for MDR1 quantitation, the abundance is over 10 times higher than previously reported, indicating the importance of peptide selection for transporter quantitation. In addition, this study also proposes a screening strategy to select peptides appropriate for relative quantitation for in vitro- in vivo extrapolation in the absence of any protein standard. [ABSTRACT FROM AUTHOR]

Following a meal, a transient increase in splanchnic blood flow occurs that can result in increased exposure to orally administered high-extraction drugs. Typically, physiologically based pharmacokinetic (PBPK) models have incorporated this increase in blood flow as a time-invariant fed/fasted ratio, but this approach is unable to explain the extent of increased drug exposure. A model for the time-varying increase in splanchnic blood flow following a moderate- to high-calorie meal (TV- Q ) was developed to describe the observed data for healthy individuals. This was integrated within a PBPK model and used to predict the contribution of increased splanchnic blood flow to the observed food effect for two orally administered high-extraction drugs, propranolol and ibrutinib. The model predicted geometric mean fed/fasted AUC and C ratios of 1.24 and 1.29 for propranolol, which were within the range of published values (within 1.0-1.8-fold of values from eight clinical studies). For ibrutinib, the predicted geometric mean fed/fasted AUC and C ratios were 2.0 and 1.84, respectively, which was within 1.1-fold of the reported fed/fasted AUC ratio but underestimated the reported C ratio by up to 1.9-fold. For both drugs, the interindividual variability in fed/fasted AUC and C ratios was underpredicted. This suggests that the postprandial change in splanchnic blood flow is a major mechanism of the food effect for propranolol and ibrutinib but is insufficient to fully explain the observations. The proposed model is anticipated to improve the prediction of food effect for high-extraction drugs, but should be considered with other mechanisms. [ABSTRACT FROM AUTHOR]

Clarithromycin is a substrate and mechanism-based inhibitor of cytochrome P450 (CYP) 3A4 as well as a substrate and competitive inhibitor of P-glycoprotein (P-gp) and organic anion-transporting polypeptides (OATP) 1B1 and 1B3. Administered concomitantly, clarithromycin causes drug-drug interactions (DDI) with the victim drugs midazolam (CYP3A4 substrate) and digoxin (P-gp substrate). The objective of the presented study was to build a physiologically based pharmacokinetic (PBPK) DDI model for clarithromycin, midazolam, and digoxin and to exemplify dosing adjustments under clarithromycin co-treatment. The PBPK model development included an extensive literature search for representative PK studies and for compound characteristics of clarithromycin, midazolam, and digoxin. Published concentration-time profiles were used for model development (training dataset), and published and unpublished individual profiles were used for model evaluation (evaluation dataset). The developed single-compound PBPK models were linked for DDI predictions. The full clarithromycin DDI model successfully predicted the metabolic (midazolam) and transporter (digoxin) DDI, the acceptance criterion (0.5 ≤ AUC/AUC ≤ 2) was met by all predictions. During co-treatment with 250 or 500 mg clarithromycin (bid), the midazolam and digoxin doses should be reduced by 74 to 88% and by 21 to 22%, respectively, to ensure constant midazolam and digoxin exposures (AUC). With these models, we provide highly mechanistic tools to help researchers understand and characterize the DDI potential of new molecular entities and inform the design of DDI studies with potential CYP3A4 and P-gp substrates. [ABSTRACT FROM AUTHOR]

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

This paper focuses on the retrospective evaluation of physiologically based pharmacokinetic (PBPK) techniques used to mechanistically predict clearance throughout pediatric life. An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions. Subsequently, the model was evaluated for mechanistic prediction of total, CYP2D6-related, and renal clearance predictions in very early life. In two in vitro pediatric human liver microsomal (HLM) batches (1 and 3 months), O-desmethyltramadol and N-desmethyltramadol formation rates were compared with CYP2D6 and CYP3A4 activity, respectively. O-desmethyltramadol formation was mediated only by CYP2D6, while N-desmethyltramadol was mediated in part by CYP3A4. Additionally, the clearance maturation of the PBPK model predictions was compared to two in vivo maturation models (Hill and exponential) based on plasma concentration data, and to clearance estimations from a WinNonlin® fit of plasma concentration and urinary excretion data. Maturation of renal and CYP2D6 clearance is captured well in the PBPK model predictions, but total tramadol clearance is underpredicted. The most pronounced underprediction of total and CYP2D6-mediated clearance was observed in the age range of 2-13 years. In conclusion, the PBPK technique showed to be a powerful mechanistic tool capable of predicting maturation of CYP2D6 and renal tramadol clearance in early infancy, although some underprediction occurs between 2 and 13 years for total and CYP2D6-mediated tramadol clearance. [ABSTRACT FROM AUTHOR]

Physiologically based absorption models can be an important tool in understanding product performance and hence implementation of Quality by Design (QbD) in drug product development. In this report, we show several case studies to demonstrate the potential application of absorption modeling in rational design of drug product under the QbD paradigm. The examples include application of absorption modeling-(1) prior to first-in-human studies to guide development of a formulation with minimal sensitivity to higher gastric pH and hence reduced interaction when co-administered with PPIs and/or H2RAs, (2) design of a controlled release formulation with optimal release rate to meet trough plasma concentrations and enable QD dosing, (3) understanding the impact of API particle size distribution on tablet bioavailability and guide formulation design in late-stage development, (4) assess impact of API phase change on product performance to guide specification setting, and (5) investigate the effect of dissolution rate changes on formulation bioperformance and enable appropriate specification setting. These case studies are meant to highlight the utility of physiologically based absorption modeling in gaining a thorough understanding of the product performance and the critical factors impacting performance to drive design of a robust drug product that would deliver the optimal benefit to the patients. [ABSTRACT FROM AUTHOR]

Quantitative prediction of the impact of chronic kidney disease (CKD) on drug disposition has become important for the optimal design of clinical studies in patients. In this study, clinical data of 151 compounds under CKD conditions were extensively surveyed, and alterations in pharmacokinetic parameters were evaluated. In CKD patients, the unbound hepatic intrinsic clearance decreased to a similar extent for drugs eliminated via hepatic metabolism by cytochrome P450, UDP-glucuronosyltransferase, and other mechanisms. Renal clearance showed a similar decrease to glomerular filtration rate, irrespective of the contribution of tubular secretion. The scaling factor (SF) obtained from the interquartile range of the relative change in each parameter was applied to the well-stirred model to predict clearance in patients. Hepatic and renal clearance could be successfully predicted for approximately half and two-thirds, respectively, of the applied compounds, showing the high utility of SFs. SFs were also introduced to a physiologically based pharmacokinetic (PBPK) model, and the plasma concentration profiles of 12 model compounds with different elimination pathways were predicted for CKD patients. The PBPK model combined with SFs provided good predictability for plasma concentration. The developed PBPK model with information on SFs would accelerate translational research in drug development by predicting pharmacokinetics in CKD patients. [ABSTRACT FROM AUTHOR]

Compared to small chemical molecules, monoclonal antibodies and Fc-containing derivatives (mAbs) have unique pharmacokinetic behaviour characterised by relatively poor cellular permeability, minimal renal filtration, binding to FcRn, target-mediated drug disposition, and disposition via lymph. A minimal physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics of mAbs in humans was developed. Within the model, the body is divided into three physiological compartments; plasma, a single tissue compartment and lymph. The tissue compartment is further sub-divided into vascular, endothelial and interstitial spaces. The model simultaneously describes the levels of endogenous IgG and exogenous mAbs in each compartment and sub-compartment and, in particular, considers the competition of these two species for FcRn binding in the endothelial space. A Monte-Carlo sampling approach is used to simulate the concentrations of endogenous IgG and mAb in a human population. Existing targeted-mediated drug disposition (TMDD) models are coupled with the minimal PBPK model to provide a general platform for simulating the pharmacokinetics of therapeutic antibodies using primarily pre-clinical data inputs. The feasibility of utilising pre-clinical data to parameterise the model and to simulate the pharmacokinetics of adalimumab and an anti-ALK1 antibody (PF-03446962) in a population of individuals was investigated and results were compared to published clinical data. [ABSTRACT FROM AUTHOR]

Monoclonal antibodies (mAbs) exhibit biexponential profiles in plasma that are commonly described with a standard two-compartment model with elimination from the central compartment. These models adequately describe mAb plasma PK. However, these models ignore elimination from the peripheral compartment. This may lead to underestimation of the volume of distribution of the peripheral compartment and thus over-predicts concentration in the peripheral compartment. We developed a simple and physiologically relevant model that incorporates information on binding and dissociation rates between mAb and FcRn receptor, mAb uptake, reflection, and catabolic degradation. We employed a previously published PBPK model and, with assumptions regarding rates of processes controlling mAb disposition, reduced the complex PBPK model to a simpler circular model with central, peripheral, and lymph compartments specifying elimination from both central and peripheral. We successfully applied the model to describe the PK of an investigational mAb. Our model presents an improvement over standard two-compartmental models in predicting whole-body average tissue concentrations while adequately describing plasma PK with minimal complexity and physiologically more meaningful parameters. [ABSTRACT FROM AUTHOR]

Predicting the penetration of drugs across the human blood-brain barrier (BBB) is a significant challenge during their development. A variety of in vitro systems representing the BBB have been described, but the optimal use of these data in terms of extrapolation to human unbound brain concentration profiles remains to be fully exploited. Physiologically based pharmacokinetic (PBPK) modelling of drug disposition in the central nervous system (CNS) currently consists of fitting preclinical in vivo data to compartmental models in order to estimate the permeability and efflux of drugs across the BBB. The increasingly popular approach of using in vitro-in vivo extrapolation (IVIVE) to generate PBPK model input parameters could provide a more mechanistic basis for the interspecies translation of preclinical models of the CNS. However, a major hurdle exists in verifying these predictions with observed data, since human brain concentrations can't be directly measured. Therefore a combination of IVIVE-based and empirical modelling approaches based on preclinical data are currently required. In this review, we summarise the existing PBPK models of the CNS in the literature, and we evaluate the current opportunities and limitations of potential IVIVE strategies for PBPK modelling of BBB penetration. [ABSTRACT FROM AUTHOR]

The use of physiologically based pharmacokinetic (PBPK) models in the field of pediatric drug development has garnered much interest of late due to a recent Food and Drug Administration recommendation. The purpose of this study is to illustrate the developmental processes involved in creation of a pediatric PBPK model incorporating existing adult drug data. Lorazepam, a benzodiazepine utilized in both adults and children, was used as an example. A population-PBPK model was developed in PK-Sim v4.2® and scaled to account for age-related changes in size and composition of tissue compartments, protein binding, and growth/maturation of elimination processes. Dose (milligrams per kilogram) requirements for children aged 0-18 years were calculated based on simulations that achieved targeted exposures based on adult references. Predictive accuracy of the PBPK model for producing comparable plasma concentrations among 63 pediatric subjects was assessed using average-fold error (AFE). Estimates of clearance (CL) and volume of distribution (Vss) were compared with observed values for a subset of 15 children using fold error (FE). Pediatric dose requirements in young children (1-3 years) exceeded adult levels on a linear weight-adjusted (milligrams per kilogram) basis. AFE values for model-derived concentration estimates were within 1.5- and 2-fold deviation from observed values for 73% and 92% of patients, respectively. For CL, 60% and 80% of predictions were within 1.5 and 2 FE, respectively. Comparatively, predictions of Vss were more accurate with 80% and 100% of estimates within 1.5 and 2 FE, respectively. Using the presented workflow, the developed pediatric model estimated lorazepam pharmacokinetics in children as a function of age. [ABSTRACT FROM AUTHOR]

Efforts have been made to extend the biological half-life of monoclonal antibody drugs (mAbs) by increasing the affinity of mAb-neonatal Fc receptor (FcRn) binding; however, mixed results have been reported. One possible reason for a poor correlation between the equilibrium affinity of mAb-FcRn binding and mAb systemic pharmacokinetics is that the timecourse of endosomal transit is too brief to allow binding to reach equilibrium. In the present work, a new physiologically based pharmacokinetic (PBPK) model has been developed to approximate the pH and time-dependent endosomal trafficking of immunoglobulin G (IgG). In this model, a catenary sub-model was utilized to describe the endosomal transit of IgG and the time dependencies in IgG-FcRn association and dissociation. The model performs as well as a previously published PBPK model, with assumed equilibrium kinetics of mAb-FcRn binding, in capturing the disposition profile of murine mAb from wild-type and FcRn knockout mice (catenary vs. equilibrium model: r², 0.971 vs. 0.978; median prediction error, 3.38% vs. 3.79%). Compared to the PBPK model with equilibrium binding, the present catenary PBPK model predicts much more moderate changes in half-life with altered FcRn binding. For example, for a 10-fold increase in binding affinity, the catenary model predicts <2.5-fold change in half-life compared to an ~8-fold increase as predicted by the equilibrium model; for a 100-fold increase in binding affinity, the catenary model predicts ~7-fold change in half-life compared to >70-fold increase as predicted by the equilibrium model. Predictions of the new catenary PBPK model are more consistent with experimental results in the published literature. [ABSTRACT FROM AUTHOR]

Accurate predictions of human pharmacokinetic and pharmacodynamic (PK/PD) profiles are critical in early drug development, as safe, efficacious, and “developable” dosing regimens of promising compounds have to be identified. While advantages of successful integration of preclinical PK/PD data in the “anticipation” of human doses (AHD) have been recognized, pharmaceutical scientists have faced difficulties with practical implementation, especially for PK/PD profile projections of compounds with challenging absorption, distribution, metabolism, excretion and formulation properties. In this article, practical projection approaches for formulation-dependent human PK/PD parameters and profiles of Biopharmaceutics Classification System classes I-IV drugs based on preclinical data are described. Case examples for “AHD” demonstrate the utility of preclinical and clinical PK/PD modeling for formulation risk identification, lead candidate differentiation, and prediction of clinical outcome. The application of allometric scaling methods and physiologically based pharmacokinetic approaches for clearance or volume of distribution projections is described using GastroPlus™. Methods to enhance prediction confidence such as in vitro– in vivo extrapolations in clearance predictions using in vitro microsomal data are discussed. Examples for integration of clinical PK/PD and formulation data from frontrunner compounds via “reverse pharmacology strategies” that minimize uncertainty with PK/PD predictions are included. The use of integrated softwares such as GastroPlus™ in combination with established PK projection methods allow the projection of formulation-dependent preclinical and human PK/PD profiles required for compound differentiation and development risk assessments. [ABSTRACT FROM AUTHOR]

Physiologically based pharmacokinetic (PBPK) models are composed of a series of differential equations and have been implemented in a number of commercial software packages. These models require species-specific and compound-specific input parameters and allow for the prediction of plasma and tissue concentration time profiles after intravenous and oral administration of compounds to animals and humans. PBPK models allow the early integration of a wide variety of preclinical data into a mechanistic quantitative framework. Use of PBPK models allows the experimenter to gain insights into the properties of a compound, helps to guide experimental efforts at the early stages of drug discovery, and enables the prediction of human plasma concentration time profiles with minimal (and in some cases no) animal data. In this review, the application and limitations of PBPK techniques in drug discovery are discussed. Specific reference is made to its utility (1) at the lead development stage for the prioritization of compounds for animal PK studies and (2) at the clinical candidate selection and “first in human” stages for the prediction of human PK. [ABSTRACT FROM AUTHOR]

The effect of food on pharmacokinetic properties of drugs is a commonly observed occurrence affecting about 40% of orally administered drugs. Within the pharmaceutical industry, significant resources are invested to predict and characterize a clinically relevant food effect. Here, the predictive performance of physiologically based pharmacokinetic (PBPK) food effect models was assessed via de novo mechanistic absorption models for 30 compounds using controlled, pre-defined in vitro, and modeling methodology. Compounds for which absorption was known to be limited by intestinal transporters were excluded in this analysis. A decision tree for model verification and optimization was followed, leading to high, moderate, or low food effect prediction confidence. High (within 0.8- to 1.25-fold) to moderate confidence (within 0.5- to 2-fold) was achieved for most of the compounds (15 and 8, respectively). While for 7 compounds, prediction confidence was found to be low (> 2-fold). There was no clear difference in prediction success for positive or negative food effects and no clear relationship to the BCS category of tested drug molecules. However, an association could be demonstrated when the food effect was mainly related to changes in the gastrointestinal luminal fluids or physiology, including fluid volume, motility, pH, micellar entrapment, and bile salts. Considering these findings, it is recommended that appropriately verified mechanistic PBPK modeling can be leveraged with high to moderate confidence as a key approach to predicting potential food effect, especially related to mechanisms highlighted here. [ABSTRACT FROM AUTHOR]

In recent years, global sensitivity analysis (GSA) has gained interest in physiologically based pharmacokinetics (PBPK) modelling and simulation from pharmaceutical industry, regulatory authorities, and academia. With the case study of an in-house PBPK model for inhaled compounds in rats, the aim of this work is to show how GSA can contribute in PBPK model development and daily use. We identified two types of GSA that differ in the aims and, thus, in the parameter variability: inter-compound and intra-compound GSA. The inter-compound GSA aims to understand which are the parameters that mostly influence the variability of the metrics of interest in the whole space of the drugs' properties, and thus, it is useful during the model development. On the other hand, the intra-compound GSA aims to highlight how much the uncertainty associated with the parameters of a given drug impacts the uncertainty in the model prediction and so, it is useful during routine PBPK use. In this work, inter-compound GSA highlighted that dissolution- and formulation-related parameters were mostly important for the prediction of the fraction absorbed, while the permeability is the most important parameter for lung AUC and MRT. Intra-compound GSA highlighted that, for all the considered compounds, the permeability was one of the most important parameters for lung AUC, MRT and plasma MRT, while the extraction ratio and the dose for the plasma AUC. GSA is a crucial instrument for the quality assessment of model-based inference; for this reason, we suggest its use during both PBPK model development and use. [ABSTRACT FROM AUTHOR]

In pediatric PBPK models, age-related changes in the body are known to occur. Given the sparsity of and the variability associated with relevant physiological parameters, different PBPK software providers may vary in their system's data. In this work, three commercially available PBPK software packages (PK-Sim®, Simcyp®, and Gastroplus®) were investigated regarding their differences in system-related information, possibly affecting clearance prediction. Three retrograde PBPK clearance models were set up to enable prediction of pediatric tramadol clearance. These models were qualified in terms of total, CYP2D6, and renal clearance in adults. Tramadol pediatric clearance predictions from PBPK were compared with a pooled popPK model covering clearance ranging from neonates to adults. Fold prediction errors were used to evaluate the results. Marked differences in liver clearance prediction between PBPK models were observed. In general, the prediction bias of total clearance was greatest at the youngest population and decreased with age. Regarding CYP2D6 and renal clearance, important differences exist between PBPK software tools. Interestingly, the PBPK model with the shortest CYP2D6 maturation half-life (PK-Sim) agreed best with the in vivo CYP2D6 maturation model. Marked differences in physiological data explain the observed differences in hepatic clearance prediction in early life between the various PBPK software providers tested. Consensus on the most suited pediatric data to use should harmonize and optimize pediatric clearance predictions. Moreover, the combination of bottom-up and top-down approaches, using a convenient probe substrate, has the potential to update system-related parameters in order to better represent pediatric physiology.