Showing papers on "Physiologically based pharmacokinetic modelling published in 2019"
TL;DR: The unique disposition characteristics of nanoparticles are reviewed, how PBPK modeling takes into account the unique disposition properties of nanoparticle properties is assessed, and the applications and challenges of P BPK modeling in characterizing and predicting the disposition and biological effects of nanop particles are commented on.
102 citations
TL;DR: This article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy by reviewing many relevant scientific publications to identify new findings and highlight gaps that need to be addressed.
Abstract: Physiologically based pharmacokinetic modelling is well established in the pharmaceutical industry and is accepted by regulatory agencies for the prediction of drug–drug interactions. However, physiologically based pharmacokinetic modelling is valuable to address a much wider range of pharmaceutical applications, and new regulatory impact is expected as its full power is leveraged. As one example, physiologically based pharmacokinetic modelling is already routinely used during drug discovery for in-vitro to in-vivo translation and pharmacokinetic modelling in preclinical species, and this leads to the application of verified models for first-in-human pharmacokinetic predictions. A consistent cross-industry strategy in this application area would increase confidence in the approach and facilitate further learning. With this in mind, this article aims to enhance a previously published first-in-human physiologically based pharmacokinetic model-building strategy. Based on the experience of scientists from multiple companies participating in the GastroPlus™ User Group Steering Committee, new Absorption, Distribution, Metabolism and Excretion knowledge is integrated and decision trees proposed for each essential component of a first-in-human prediction. We have reviewed many relevant scientific publications to identify new findings and highlight gaps that need to be addressed. Finally, four industry case studies for more challenging compounds illustrate and highlight key components of the strategy.
84 citations
TL;DR: This work has pooled the experience across 4 pharmaceutical companies to propose a general multistep PBPK workflow leveraging pre-existing clinical data for immediate-release formulations of Biopharmaceutics Classification System I and II compounds to promote pragmatic P BPK approaches for compounds where absorption is well understood.
53 citations
TL;DR: An industry perspective on the current challenges with establishing IVIVCs and the potential PBPK and absorption modeling offer to increase their impact is provided and PB-IVIVC best practices and a strategy for model development and application are proposed.
Abstract: The establishment of an in vitro–in vivo correlation (IVIVC) is considered the gold standard to establish in vivo relevance of a dissolution method and to utilize dissolution data in the context of regulatory bioequivalence questions, including the development of dissolution specifications. However, several recent publications, including industry surveys and reviews from regulatory agencies, have indicated a low success rate for IVIVCs, especially for immediate-release formulations. In recent years, the use of physiologically based pharmacokinetics (PBPK) and absorption modeling, as a tool to facilitate formulation development, has been attracting increased attention. This manuscript provides an industry perspective on the current challenges with establishing IVIVCs and the potential PBPK and absorption modeling offer to increase their impact. Case studies across both immediate-release and extended-release formulations from five pharmaceutical companies are utilized to demonstrate how physiologically based IVIVC (PB-IVIVC) may facilitate drug product understanding and to inform bioequivalence assessment and clinically relevant specifications. Finally, PB-IVIVC best practices and a strategy for model development and application are proposed.
52 citations
TL;DR: The PBPK analysis suggests that OATP1B activity could be decreased up to 60% in severe CKD, whereas changes to CYP2C8 are negligible.
Abstract: Chronic kidney disease (CKD) differentially affects the pharmacokinetics (PK) of nonrenally cleared drugs via certain pathways (e.g., cytochrome P450 (CYP)2D6); however, the effect on CYP2C8-mediated clearance is not well understood because of overlapping substrate specificity with hepatic organic anion-transporting polypeptides (OATPs). This study used physiologically based pharmacokinetic (PBPK) modeling to delineate potential changes in CYP2C8 or OATP1B activity in patients with CKD. Drugs analyzed are predominantly substrates of CYP2C8 (rosiglitazone and pioglitazone), OATP1B (pitavastatin), or both (repaglinide). Following initial model verification, pharmacokinetics (PK) of these drugs were simulated in patients with severe CKD considering changes in glomerular filtration rate (GFR), plasma protein binding, and activity of either CYP2C8 and/or OATP1B in a stepwise manner. The PBPK analysis suggests that OATP1B activity could be decreased up to 60% in severe CKD, whereas changes to CYP2C8 are negligible. This improved understanding of CKD effect on clearance pathways could be important to inform the optimal use of nonrenally eliminated drugs in patients with CKD.
47 citations
TL;DR: Using the type of meal and dosing conditions suggested by regulatory agencies as a basis, this review has two specific objectives: to summarize the understanding on the impact of food intake on luminal environment and drug product performance and to summarized the usefulness and limitations of available in vitro and in silico methodologies for the evaluation of drug productperformance after food intake.
Abstract: Objectives Using the type of meal and dosing conditions suggested by regulatory agencies as a basis, this review has two specific objectives: first, to summarize our understanding on the impact of food intake on luminal environment and drug product performance and second, to summarize the usefulness and limitations of available in vitro and in silico methodologies for the evaluation of drug product performance after food intake. Key findings Characterization of the luminal environment and studies evaluating product performance in the lumen, under conditions suggested by regulatory agencies for simulating the fed state, are limited. Various in vitro methodologies have been proposed for evaluating drug product performance in the fed state, but systematic validation is lacking. Physiologically based pharmacokinetic (PBPK) modelling approaches require the use of in vitro biorelevant data and, to date, have been used primarily for investigating the mechanisms via which an already observed food effect is mediated. Summary Better understanding of the impact of changes induced by the meal administration conditions suggested by regulatory agencies on the luminal fate of the drug product is needed. Relevant information will be useful for optimizing the in vitro test methods and increasing the usefulness of PBPK modelling methodologies.
46 citations
TL;DR: The use of physiologically-based pharmacokinetic (PBPK) models as an approach to characterize the in vivo behavior of mAbs is discussed, in the context of the key PK processes that should be considered in these models.
45 citations
TL;DR: This work focuses on computational modeling tools used in formulation design and its applications and recommends avenues for understanding complex formulation design in less time with lower investment.
45 citations
TL;DR: An open-source physiologically based pharmacokinetic model accounting for species-specific toxicokinetic parameters of PFOS is developed and applied to predict human equivalent doses based on reported points of departure in selected critical toxicity studies in rats and monkeys following U.S. EPA's guidelines.
44 citations
TL;DR: In this paper, a review of the applicability of conventional modelling approaches for NMs is scrutinised for their applicability for nanomaterials, and case studies demonstrate their application to model NM-specific kinetics, integrated with environmental fate models, including relevant physiological processes.
Abstract: Quantification of the uptake and elimination of nanomaterials (NMs) by organisms is key in assessing the environmental risks of NMs. For this, uptake models for conventional solutes may be used, although no consensus exists on their applicability for NMs. In this critical review therefore, conventional modelling approaches are scrutinised for their applicability for NMs. Statically derived accumulation factors, like BCF or BAF based on measured concentrations, are considered to be flawed because NMs are thermodynamically not stable, an important assumption for this approach. Dynamically derived accumulation factors, based on kinetic exposure experiments, may be applicable because no equilibrium between the organism and exposure medium is needed. Currently there is no full understanding of the passive uptake of NMs, which hampers assessment of the applicability of biotic ligand models. Passive uptake, however, is generally considered to be very limited, which would imply a limited applicability of BLMs for NMs. Physiologically based pharmacokinetic (PBPK) models, or biodynamic models, have successfully been applied in uptake studies with NMs. Their underlying assumptions can be met in experiments addressing NMs and case studies presented in this review demonstrate their applicability to model NM-form specific kinetics, integrated with environmental fate models, including relevant physiological processes. Their application requires the a priori definition of the major mechanisms driving the uptake kinetics and the quantification of the associated kinetic rate constants. This limits their application to those mechanisms for which the kinetic rate constants can actually be quantified. Within these limitations, PBPK models have been shown to be applicable and provide a promising general approach to improve modelling of NM-accumulation in organisms.
43 citations
TL;DR: This review focuses on the small and full scale in vitro methods to assess drug precipitation in the fasted small intestine.
Abstract: Objectives Drug precipitation in vivo poses a significant challenge for the pharmaceutical industry. During the drug development process, the impact of drug supersaturation or precipitation on the in vivo behaviour of drug products is evaluated with in vitro techniques. This review focuses on the small and full scale in vitro methods to assess drug precipitation in the fasted small intestine. Key findings Many methods have been developed in an attempt to evaluate drug precipitation in the fasted state, with varying degrees of complexity and scale. In early stages of drug development, when drug quantities are typically limited, small-scale tests facilitate an early evaluation of the potential precipitation risk in vivo and allow rapid screening of prototype formulations. At later stages of formulation development, full-scale methods are necessary to predict the behaviour of formulations at clinically relevant doses. Multicompartment models allow the evaluation of drug precipitation after transfer from stomach to the upper small intestine. Optimisation of available biopharmaceutics tools for evaluating precipitation in the fasted small intestine is crucial for accelerating the development of novel breakthrough medicines and reducing the development costs. Summary Despite the progress from compendial quality control dissolution methods, further work is required to validate the usefulness of proposed setups and to increase their biorelevance, particularly in simulating the absorption of drug along the intestinal lumen. Coupling results from in vitro testing with physiologically based pharmacokinetic modelling holds significant promise and requires further evaluation.
TL;DR: This review evaluates the three dynamic models (biokinetic model: BK, physiologically based pharmacokineticmodel: PBPK, and toxicokinetic-toxicodynamic model: TKTD) in the understanding of the key questions in metal ecotoxicology in aquatic systems, i.e., bioaccumulation, transport and toxicity.
TL;DR: A physiologically based pharmacokinetic model for morphine that accounted for OCT1 ontogeny and PG effect in post‐term neonates adequately described the clinically observed variability in morphine PKs.
Abstract: Morphine is commonly used for analgesia in the neonatal intensive care unit (NICU) despite having highly variable pharmacokinetics (PKs) between individual patients. The pharmacogenetic (PG) effect of variants at the loci of organic cation transporter 1 (OCT1) and UDP-glucuronosyltransferase 2B7 (UGT2B7) on age-dependent morphine clearance were evaluated in a cohort of critically ill neonatal patients using an opportunistic sampling design. Our primary results demonstrate the significant influence of OCT1 genotype (P < 0.05) and gestational age (P ≤ 0.005) on morphine PKs. A physiologically based pharmacokinetic (PBPK) model for morphine that accounted for OCT1 ontogeny and PG effect in post-term neonates adequately described the clinically observed variability in morphine PKs. This study serves as a proof of concept for genotype-dependent drug transporter ontogeny in neonates.
TL;DR: In this paper, the authors developed a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors.
Abstract: Population factors such as age, gender, ethnicity, genotype and disease state can cause inter-individual variability in pharmacokinetic (PK) profile of drugs. Primarily, this variability arises from differences in abundance of drug metabolizing enzymes and transporters (DMET) among individuals and/or groups. Hence, availability of compiled data on abundance of DMET proteins in different populations can be useful for developing physiologically based pharmacokinetic (PBPK) models. The latter are routinely employed for prediction of PK profiles and drug interactions during drug development and in case of special populations, where clinical studies either are not feasible or have ethical concerns. Therefore, the main aim of this work was to develop a repository of literature-reported DMET abundance data in various human tissues, which included compilation of information on sample size, technique(s) involved, and the demographic factors. The collation of literature reported data revealed high inter-laboratory variability in abundance of DMET proteins. We carried out unbiased meta-analysis to obtain weighted mean and percent coefficient of variation (%CV) values. The obtained %CV values were then integrated into a PBPK model to highlight the variability in drug PK in healthy adults, taking lamotrigine as a model drug. The validated PBPK model was extrapolated to predict PK of lamotrigine in paediatric and hepatic impaired populations. This study thus exemplifies importance of the DMET protein abundance database, and use of determined values of weighted mean and %CV after meta-analysis in PBPK modelling for the prediction of PK of drugs in healthy and special populations.
TL;DR: The platform PBPK model presented here provides an unprecedented quantitative tool for prediction of mAb PK at the site-of-action in the brain, and preclinical-to-clinical translation of mAbs being developed against central nervous system (CNS) disorders.
Abstract: In this manuscript, we have presented the development of a novel platform physiologically-based pharmacokinetic (PBPK) model to characterize brain disposition of mAbs in the mouse, rat, monkey and human. The model accounts for known anatomy and physiology of the brain, including the presence of distinct blood–brain barrier and blood–cerebrospinal fluid (CSF) barrier. CSF and interstitial fluid turnover, and FcRn mediated transport of mAbs are accounted for. The model was first used to characterize published and in-house pharmacokinetic (PK) data on the disposition of mAbs in rat brain, including the data on PK of mAb in different regions of brain determined using microdialysis. Majority of model parameters were fixed based on literature reported values, and only 3 parameters were estimated using rat data. The rat PBPK model was translated to mouse, monkey, and human, simply by changing the values of physiological parameters corresponding to each species. The translated PBPK models were validated by a priori predicting brain PK of mAbs in all three species, and comparing predicted exposures with observed data. The platform PBPK model was able to a priori predict all the validation PK profiles reasonably well (within threefold), without estimating any parameters. As such, the platform PBPK model presented here provides an unprecedented quantitative tool for prediction of mAb PK at the site-of-action in the brain, and preclinical-to-clinical translation of mAbs being developed against central nervous system (CNS) disorders. The proposed model can be further expanded to account for target engagement, disease pathophysiology, and novel mechanisms, to support discovery and development of novel CNS targeting mAbs.
TL;DR: Simulation and prediction of drug-drug interactions between these LA antiretroviral agents and rifampicin using physiologically based pharmacokinetic (PBPK) modeling predicted the theoretical effect of rifampsicin on cabotegravir and rilpivirine LA intramuscular formulations.
Abstract: Background Cabotegravir and rilpivirine are 2 long-acting (LA) antiretrovirals that can be administered intramuscularly; their interaction with rifampicin, a first-line antituberculosis agent, has not been investigated. The aim of this study was to simulate and predict drug-drug interactions (DDIs) between these LA antiretroviral agents and rifampicin using physiologically based pharmacokinetic (PBPK) modeling. Methods The designed PBPK models were qualified (according to European Medicines Agency guidelines) against observed data for oral formulations of cabotegravir, rilpivirine, and rifampicin. Induction potential of rifampicin was also qualified by comparing the DDI between oral cabotegravir and oral rilpivirine with rifampicin. Qualified PBPK models were utilized for pharmacokinetic prediction of DDIs. Results PBPK models predicted a reduction in both area under the curve (AUC0-28 days) and trough concentration (Ctrough, 28th day) of LA cabotegravir of 41%-46% for the first maintenance dose coadministered with 600 mg once-daily oral rifampicin. Rilpivirine concentrations were predicted to decrease by 82% for both AUC0-28 days and Ctrough, 28th day following the first maintenance dose when coadministered with rifampicin. Conclusions The developed PBPK models predicted the theoretical effect of rifampicin on cabotegravir and rilpivirine LA intramuscular formulations. According to these simulations, it is likely that coadministration of rifampicin with these LA formulations will result in subtherapeutic concentrations of both drugs.
TL;DR: Current knowledge about expression and ontogeny of transporters in the human placenta in healthy pregnant women is summarized to improve knowledge about the adequacy and safety of pharmacotherapy in pregnant women and their fetuses.
Abstract: Tremendous efforts have been directed to investigate the ontogeny of drug transporters in fetuses, neonates, infants, and children based on their importance for understanding drug pharmacokinetics. During development (ie, in the fetus and newborn infant), there is special interest in transporters expressed in the placenta that modulate placental drug transfer. Many of these transporters can decrease or increase drug concentrations in the fetus and at birth, stressing the relevance of elucidating expression in the placenta and potential gestational age-dependent changes therein. Hence, the main objective of this review was to summarize the current knowledge about expression and ontogeny of transporters in the human placenta in healthy pregnant women. In addition, various in vitro, ex vivo, and in silico models that can be used to investigate placental drug transfer, namely, placental cancer cell lines, ex vivo cotyledon perfusion experiments, and physiologically based pharmacokinetic (PBPK) models, are discussed together with their advantages and shortcomings. A particular focus was placed on PBPK models because these models can integrate different types of information, such as expression data, ontogeny information, and observations obtained from the ex vivo cotyledon perfusion experiment. Such a mechanistic modeling framework may leverage the available information and ultimately help to improve knowledge about the adequacy and safety of pharmacotherapy in pregnant women and their fetuses.
TL;DR: An overview of in silico resources available to assist in the construction and evaluation of physiologically-based kinetic (PBK) models, encompassing all attributes required for PBK modelling, are presented.
TL;DR: Direct input of in-vitro dissolution/precipitation profiles to a PBPK model is insufficient-mechanistic modeling is required, thereby helping to identify critical variables, which may impact the number or design of in vitro experiments.
TL;DR: It is indicated that the predictive power of PBPK and allometric models was essentially similar for the prediction of clearance or AUC in pediatric subjects ranging from neonates to adolescents.
Abstract: The objective of this study was to compare the predictive performance of an allometric model with that of a physiologically based pharmacokinetic (PBPK) model to predict clearance or area under the concentration-time curve (AUC) of drugs in subjects from neonates to adolescents From the literature, 10 studies were identified in which clearance or AUC of drugs from neonates to adolescents was predicted by PBPK models In these published studies, drugs were given to children either by intravenous or oral route The allometric model was an age-dependent exponent (ADE) model for the prediction of clearance across the age groups The predicted clearance or AUC values from the PBPK and ADE models were compared with the experimental values The acceptable prediction error was the percentage of subjects within an 05- to 2-fold or 05- to 15-fold prediction error There were 73 drugs with a total of 372 observations From PBPK and allometric models, 911% and 906% of observations were within 05- to 2-fold prediction error, respectively For children ≤2 years old (n = 130), PBPK and allometric models had 89% and 87% of observations within the 05- to 2-fold prediction error, respectively This study indicates that the predictive power of PBPK and allometric models was essentially similar for the prediction of clearance or AUC in pediatric subjects ranging from neonates to adolescents
TL;DR: The proposed method is the first attempt to solely use PET/CT and modeling methods to predict the PSMA-positive tumor volume after RLT, and internal validation shows that this is feasible with an acceptable accuracy.
Abstract: The aim of this work was to develop a theranostic method that allows prediction of prostate-specific membrane antigen (PSMA)–positive tumor volume after radioligand therapy (RLT) based on a pretherapeutic PET/CT measurement and physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling at the example of RLT using 177Lu-labeled PSMA for imaging and therapy (PSMA I&T). Methods: A recently developed PBPK model for 177Lu-PSMA I&T RLT was extended to account for tumor (exponential) growth and reduction due to irradiation (linear quadratic model). Data from 13 patients with metastatic castration-resistant prostate cancer were retrospectively analyzed. Pharmacokinetic/pharmacodynamic parameters were simultaneously fitted in a Bayesian framework to PET/CT activity concentrations, planar scintigraphy data, and tumor volumes before and after (6 wk) therapy. The method was validated using the leave-one-out Jackknife method. The tumor volume after therapy was predicted on the basis of pretherapy PET/CT imaging and PBPK/PD modeling. Results: The relative deviation of the predicted and measured tumor volume for PSMA-positive tumor cells (6 wk after therapy) was 1% ± 40%, excluding 1 patient (prostate-specific antigen–negative) from the population. The radiosensitivity for the prostate-specific antigen–positive patients was determined to be 0.0172 ± 0.0084 Gy−1. Conclusion: To our knowledge, the proposed method is the first attempt to solely use PET/CT and modeling methods to predict the PSMA-positive tumor volume after RLT. Internal validation shows that this is feasible with an acceptable accuracy. Improvement of the method and external validation of the model is ongoing.
01 Sep 2019
TL;DR: Physiologically‐based pharmacokinetic (PBPK) modeling suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin, and the obtained fold increases can potentially be applicable to DDI prediction with other PGP substrates.
Abstract: Physiologically-based pharmacokinetic (PBPK) modeling is a powerful tool to quantitatively describe drug disposition profiles in vivo, thereby providing an alternative to predict drug-drug interactions (DDIs) that have not been tested clinically. This study aimed to predict effects of rifampin-mediated intestinal P-glycoprotein (Pgp) induction on pharmacokinetics of Pgp substrates via PBPK modeling. First, we selected four Pgp substrates (digoxin, talinolol, quinidine, and dabigatran etexilate) to derive in vitro to in vivo scaling factors for intestinal Pgp kinetics. Assuming unbound Michaelis-Menten constant (Km ) to be intrinsic, we focused on the scaling factors for maximal efflux rate (Jmax ) to adequately recover clinically observed results. Next, we predicted rifampin-mediated fold increases in intestinal Pgp abundances to reasonably recover clinically observed DDI results. The modeling results suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin. Hence, the obtained fold increases can potentially be applicable to DDI prediction with other Pgp substrates.
01 Jul 2019
TL;DR: The model indicated acalabrutinib would not perpetrate a CYP2C8 or CYP3A DDI with the sensitive CYP substrates rosiglitazone or midazolam, respectively, and dosing recommendations for DDIs should consider the magnitude of the parent drug excursion, relative to safe parent drug exposures, along with the excursion of total active components to best enable safe and adequate pharmacodynamic coverage.
Abstract: Acalabrutinib, a selective, covalent Bruton tyrosine kinase inhibitor, is a CYP3A substrate and weak CYP3A/CYP2C8 inhibitor. A physiologically-based pharmacokinetic (PBPK) model was developed for acalabrutinib and its active metabolite ACP-5862 to predict potential drug-drug interactions (DDIs). The model indicated acalabrutinib would not perpetrate a CYP2C8 or CYP3A DDI with the sensitive CYP substrates rosiglitazone or midazolam, respectively. The model reasonably predicted clinically observed acalabrutinib DDI with the CYP3A perpetrators itraconazole (4.80-fold vs. 5.21-fold observed) and rifampicin (0.21-fold vs. 0.23-fold observed). An increase of two to threefold acalabrutinib area under the curve was predicted for coadministration with moderate CYP3A inhibitors. When both the parent drug and active metabolite (total active components) were considered, the magnitude of the CYP3A DDI was much less significant. PBPK dosing recommendations for DDIs should consider the magnitude of the parent drug excursion, relative to safe parent drug exposures, along with the excursion of total active components to best enable safe and adequate pharmacodynamic coverage.
TL;DR: The unique physicochemical properties, absorption characteristics, and inherent differences in dosage form transit behavior are attributed to influence the dasatinib bioequivalence.
TL;DR: The data presented in this article provide a unique resource for age-dependent organ size and composition parameters needed for fetal physiologically based pharmacokinetic modelling during drug development and in the risk assessment of environmental chemicals and following maternally administered drugs or unintended exposure to environmental toxicants in this population.
Abstract: The growth of fetal organs is a dynamic process involving considerable changes in the anatomical and physiological parameters that can alter fetal exposure to xenobiotics in utero Physiologically based pharmacokinetic models can be used to predict the fetal exposure as time-varying parameters can easily be incorporated The objective of this study was to collate, analyse and integrate the available time-varying parameters needed for the physiologically based pharmacokinetic modelling of xenobiotic kinetics in a fetal population We performed a comprehensive literature search on the physiological development of fetal organs Data were carefully assessed, integrated and a meta-analysis was performed to establish growth trends with fetal age and weight Algorithms and models were generated to describe the growth of these parameter values as functions of age and/or weight Fetal physiologically based pharmacokinetic parameters, including the size of the heart, liver, brain, kidneys, lungs, spleen, muscles, pancreas, skin, bones, adrenal and thyroid glands, thymus, gut and gonads were quantified as a function of fetal age and weight Variability around the means of these parameters at different fetal ages was also reported The growth of the investigated parameters was not consistent (with respect to direction and monotonicity) Despite the limitations identified in the availability of some values, the data presented in this article provide a unique resource for age-dependent organ size and composition parameters needed for fetal physiologically based pharmacokinetic modelling This will facilitate the application of physiologically based pharmacokinetic models during drug development and in the risk assessment of environmental chemicals and following maternally administered drugs or unintended exposure to environmental toxicants in this population
01 Dec 2019
TL;DR: This tutorial will first introduce the basics of the mrgsolve simulation workflow, including model specification, the introduction of interventions (dosing events) into the simulation, and simulated results postprocessing.
Abstract: mrgsolve is an open-source R package available on the Comprehensive R Archive Network. It combines R and C++ coding for simulation from hierarchical, ordinary differential equation-based models. Its efficient simulation engine and integration into a parallelizable, R-based workflow makes mrgsolve a convenient tool both for simple and complex models and thus is ideal for physiologically-based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) model. This tutorial will first introduce the basics of the mrgsolve simulation workflow, including model specification, the introduction of interventions (dosing events) into the simulation, and simulated results postprocessing. An applied simulation example is then presented using a PBPK model for voriconazole, including a model validation step against adult and pediatric data sets. A final simulation example is then presented using a previously published QSP model for mitogen-activated protein kinase signaling in colorectal cancer, illustrating population simulation of different combination therapies.
01 Nov 2019
TL;DR: Pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry, while considerable variability was noted among the allometric models.
Abstract: The comparative performances of physiologically-based pharmacokinetic (PBPK) modeling and allometric scaling for predicting the pharmacokinetics (PKs) of large molecules in pediatrics are unknown. Therefore, both methods were evaluated for accuracy in translating knowledge of infliximab PKs from adults to children. PBPK modeling was performed using the base model for large molecules in PK-Sim version 7.4 with modifications in Mobi. Eight population PK models from literature were reconstructed and scaled by allometry to pediatrics. Evaluation data included seven pediatric studies (~4-18 years). Both methods performed comparably with 66.7% and 68.6% of model-predicted concentrations falling within twofold of the observed concentrations for PBPK modeling and allometry, respectively. Considerable variability was noted among the allometric models. Therefore, pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry.
TL;DR: P-PSD values obtained for various batches of acalabrutinib products in simple buffers, or in complex fluids such as fruit juices, were successfully integrated into a physiologically based pharmacokinetic model developed using GastroPlus v9.0TM, allowing the prediction of clinical pharmacokinetics under normal physiological stomach pH conditions as well as following treatment with proton pump inhibitors.
TL;DR: This article examines the use of hypothesis testing to overcome parameter non-identifiability issues, with the objective of enhancing confidence in the mechanistic basis of PBPK models and thereby improving the quality of predictions that are meant for internal decisions and regulatory submissions.
Abstract: When scientifically well-founded, the mechanistic basis of physiologically based pharmacokinetic (PBPK) models can help reduce the uncertainty and increase confidence in extrapolations outside the studied scenarios or studied populations. However, it is not always possible to establish mechanistically credible PBPK models. Requirements to establishing confidence in PBPK models, and challenges to meeting these requirements, are presented in this article. Parameter non-identifiability is the most challenging among the barriers to establishing confidence in PBPK models. Using case examples of small molecule drugs, this article examines the use of hypothesis testing to overcome parameter non-identifiability issues, with the objective of enhancing confidence in the mechanistic basis of PBPK models and thereby improving the quality of predictions that are meant for internal decisions and regulatory submissions. When the mechanistic basis of a PBPK model cannot be established, we propose the use of simpler models or evidence-based approaches.
TL;DR: This work lays the foundation for the pre-clinical extrapolation of the pharmacokinetics of AuNPs from mice to larger species and prepares a physiologically-based pharmacokinetic (PBPK) model to guide interspecies extrapolation.
Abstract: Gold nanoparticles (AuNPs) are a focus of growing medical research applications due to their unique chemical, electrical and optical properties. Because of uncertain toxicity, “green” synthesis methods are emerging, using plant extracts to improve biological and environmental compatibility. Here we explore the biodistribution of green AuNPs in mice and prepare a physiologically-based pharmacokinetic (PBPK) model to guide interspecies extrapolation. Monodisperse AuNPs were synthesized and capped with epigallocatechin gallate (EGCG) and curcumin. 64 CD-1 mice received the AuNPs by intraperitoneal injection. To assess biodistribution, groups of six mice were sacrificed at 1, 7, 14, 28 and 56 days, and their organs were analyzed for gold content using inductively coupled plasma mass spectrometry (ICP-MS). A physiologically-based pharmacokinetic (PBPK) model was developed to describe the biodistribution data in mice. To assess the potential for interspecies extrapolation, organism-specific parameters in the model were adapted to represent rats, and the rat PBPK model was subsequently evaluated with PK data for citrate-capped AuNPs from literature. The liver and spleen displayed strong uptake, and the PBPK model suggested that extravasation and phagocytosis were key drivers. Organ predictions following interspecies extrapolation were successful for rats receiving citrate-capped AuNPs. This work lays the foundation for the pre-clinical extrapolation of the pharmacokinetics of AuNPs from mice to larger species.