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In drug development decision-making is often supported through model-based methods, such as physiologically-based pharmacokinetics (PBPK). Global sensitivity analysis (GSA) is gaining use for quality assessment of model-informed inference. However, the inclusion and interpretation of correlated factors in GSA has proven an issue. Here we developed and evaluated a latent variable approach for dealing with correlated factors in GSA. An approach was developed that describes the correlation between two model inputs through the causal relationship of three independent factors: the latent variable and the unique variances of the two correlated parameters. The latent variable approach was applied to a set of algebraic models and a case from PBPK. Then, this method was compared to Sobol's GSA assuming no correlations, Sobol's GSA with groups and the Kucherenko approach. For the latent variable approach, GSA was performed with Sobol's method. By using the latent variable approach, it is possible to devise a unique and easy interpretation of the sensitivity indices while maintaining the correlation between the factors. Compared methods either consider the parameters independent, group the dependent variables into one unique factor or present difficulties in the interpretation of the sensitivity indices. In situations where GSA is called upon to support model-informed decision-making, the latent variable approach offers a practical method, in terms of ease of implementation and interpretability, for applying GSA to models with correlated inputs that does not violate the independence assumption. Prerequisites and limitations of the approach are discussed. [ABSTRACT FROM AUTHOR]

Purpose: To explore the application of the parameters of the physiologically based finite time pharmacokinetic (PBFTPK) models subdivided in first-order (PBFTPK)1 and zero-order (PBFTPK)0 models to bioavailability and bioequivalence. To develop a methodology for the estimation of absolute bioavailability, F, from oral data exclusively. Methods: Simulated concentration time data were generated from the Bateman equation and compared with data generated from the (PBFTPK)1 and (PBFTPK)0 models. The blood concentration Cb(τ) at the end of the absorption process τ, was compared to Cmax; the utility of AUC 0 τ and AUC t ∞ in bioequivalence assessment was also explored. Equations for the calculation of F from oral data were derived for the (PBFTPK)1 and (PBFTPK)0 models. An estimate for F was also derived from an areas proportionality using oral data exclusively. Results: The simulated data of the (PBFTPK)0 models exhibit rich dynamics encountered in complex drug absorption phenomena. Both (PBFTPK)1 and (PBFTPK)0 models result either in Cmax = Cb(τ) or Cmax > Cb(τ) for rapidly- and not rapidly-absorbed drugs, respectively; in the latter case, Cb(τ) and τ are meaningful parameters for drug's rate of exposure. For both (PBFTPK)1 and (PBFTPK)0 models, AUC 0 τ or portions of it cannot be used as early exposure rate indicators. AUC τ ∞ is a useful parameter for the assessment of extent of absorption for very rapidly absorbed drugs. An estimate for F for theophylline formulations was found close to unity. Conclusion: The (PBFTPK)1 and (PBFTPK)0 models are more akin to in vivo conditions. Estimates for F can be derived from oral data exclusively. [ABSTRACT FROM AUTHOR]

Current methods to assess risk in infants exposed to maternal medication through breast milk do not specifically account for infants most vulnerable to high drug exposure. A workflow applied to lamotrigine incorporated variability in infant anatomy and physiology, milk intake volume, and milk concentration to predict infant exposure. An adult physiologically based pharmacokinetic model of lamotrigine was developed and evaluated. The model was scaled to account for growth and maturation of a virtual infant population (n=100). Daily infant doses were simulated using milk intake volume and concentration models described by a nonlinear equation of weight-normalized intake across infant age and a linear function on the relationship of observed milk concentrations and maternal doses, respectively. Average infant plasma concentration at steady state was obtained through simulation. Models were evaluated by comparing observed to simulated infant plasma concentrations from breastfeeding infants based on a 90% prediction interval (PI). Upper AUC ratio (UAR) was defined as a novel risk metric. Twenty-five paired (milk concentrations measured) and 18 unpaired (milk concentrations unknown) infant plasma samples were retrieved from the literature. Forty-four percent and 11% of the paired and unpaired infant plasma concentrations were outside of the 90% PI, respectively. Over all ages (0–7 months), unpaired predictions captured more observed infant plasma concentrations within 90% PI than paired. UAR was 0.18–0.44 when mothers received 200 mg lamotrigine, suggesting that infants can receive 18–44% of the exposure per dose as compared to adults. UARs determined for further medications could reveal trends to better classify at-risk mother-infant pairs. [ABSTRACT FROM AUTHOR]

Physiologically based pharmacokinetic (PBPK) models are an important type of systems model used commonly in drug development before commencement of first-in-human studies. Due to structural complexity, these models are not easily utilised for future data-driven population pharmacokinetic (PK) analyses that require simpler models. In the current study we aimed to explore and automate methods of simplifying PBPK models using a proper lumping technique. A linear 17-state PBPK model for fentanyl was identified from the literature. Four methods were developed to search the optimal lumped model, including full enumeration (the reference method), non-adaptive random search (NARS), scree plot plus NARS, and simulated annealing (SA). For exploratory purposes, it was required that the total area under the fentanyl arterial concentration–time curve (AUC) between the lumped and original models differ by 0.002% at maximum. In full enumeration, a 4-state lumped model satisfying the exploratory criterion was found. In NARS, a lumped model with the same number of lumped states was found, requiring a large number of random samples. The scree plot provided a starting lumped model to NARS and the search completed within a short time. In SA, a 4-state lumped model was consistently delivered. In simplify an existing linear fentanyl PBPK model, SA was found to be robust and the most efficient and may be suitable for general application to other larger-scale linear systems. Ultimately, simplified PBPK systems with fundamental mechanisms may be readily used for data-driven PK analyses. [ABSTRACT FROM AUTHOR]

Abstract: Reluctance to enroll pediatric subjects in clinical trials has left gaps in information about dosing, safety, and efficacy of medications. Pharmacotherapeutic information for pediatric patients may be available for only a small range of ages and may be deficient, as children respond differently as they grow and mature from prematurity to adolescence. Current regulations, however, require early planning for the participation of children in drug development, as pediatric plans must be submitted at the end of phase 1 (European Union) or the end of phase 2 (United States). These plans are extensive, outlining planned studies, subjects to be enrolled, dose and dosage form justification, planned observations, and statistical analysis as well as planned modeling, simulation, and extrapolation analyses. The extent to which efficacy information in adults can be extrapolated to children depends on how similar the disease is in adults and each of the 5 pediatric age groups. Extrapolation may not be possible for conditions that do not occur in adults, requiring a complete development plan in adults, or extrapolation may be complete because of similar pathology and response to treatment. Pharmacokinetic and safety information cannot be extrapolated and must be collected in children of all ages, unless a waiver is granted. Physiologically based pharmacokinetic modeling, optimal design, population pharmacokinetics, and scavenged samples are all examples of new methodologies being used to study pediatric therapeutics. Clinicaltrials.gov and EU Clinical Trials registry are good sources of results of pediatric trials, although sponsors are also working toward prompt publication of study results in peer‐reviewed journals. [ABSTRACT FROM AUTHOR]

The interest for environmental issues and the concern resulting from the potential exposure to contaminants were the starting point to develop methodologies in order to evaluate the consequences that those might have over both the environment and human health. Considering the feature of POPs, including PBDEs, such as bioaccumulation, biomagnification, long-range transport and adverse effects even long time after exposure, risk assessment of POPs requires specific approaches and tools. In this particular context, the MERLIN-Expo tool was used to assess the aquatic environmental exposure of Adige River to PBDEs and the accumulation of PBDEs in humans through the consumption of possible contaminated local aquatic food. The aquatic food web models provided as output of the deterministic simulation the time trend of concentrations for twenty years of BDE-47 and total PBDEs, expressed using the physico-chemical properties of BDE-47, in aquatic organisms of the food web of Adige River. For BDE-47, the highest accumulated concentrations were detected for two benthic species: Thymallus thymallus and Squalius cephalus whereas the lowest concentrations were obtained for the pelagic specie Salmo trutta marmoratus . The trend obtained for the total PBDEs, calculated using the physico-chemical properties of BDE-47, follows the one of BDE-47. For human exposure, different BDE-47 and total PBDEs concentration trends between children, adolescent, adults and elderly were observed, probably correlated with the human intake of fish products in the daily diet and the ability to metabolize these contaminants. In detail, for the adolescents, adults and elderly a continuous accumulation of the target contaminants during the simulation's years was observed, whereas for children a plateau at the end of the simulation period was perceived. [ABSTRACT FROM AUTHOR]

A physiologically based pharmacokinetic (PBPK) model has been developed for ganciclovir and its prodrug valganciclovir. Initial bottom-up modeling based on physicochemical drug properties and measured in vitro inputs was verified in preclinical animal species, and then, a clinical model was verified in a stepwise fashion with pharmacokinetic data in adult, children, and neonatal patients. The final model incorporated conversion of valganciclovir to ganciclovir through esterases and permeability-limited tissue distribution of both drugs with active transport processes added in gut, liver, and kidney. A PBPK model which accounted for known age-related tissue volumes, composition and blood flows, and renal filtration clearance was able to simulate well the measured plasma exposures in adults and pediatric patients. Overall, this work illustrates the stepwise development of PBPK models which could be used to predict pharmacokinetics in infants and neonates, thereby assisting drug development in a vulnerable patient population where clinical data are challenging to obtain. [ABSTRACT FROM AUTHOR]

Transporters play an important role in drug absorption, disposition, and drug action. The evaluation of drug transporters requires a comprehensive understanding of transporter biology and pharmacology. Physiologically based pharmacokinetic (PBPK) models may offer an integrative platform to quantitatively evaluate the role of drug transporters and its interplay with other drug disposition processes such as passive drug diffusion and elimination by metabolizing enzymes. To date, PBPK modeling and simulations integrating drug transporters lag behind that for drug-metabolizing enzymes. In addition, predictive performance of PBPK has not been well established for predicting the role of drug transporters in the pharmacokinetics of a drug. To enhance overall predictive performance of transporter-based PBPK models, it is necessary to have a detailed understanding of transporter biology for proper representation in the models and to have a quantitative understanding of the contribution of transporters in the absorption and metabolism of a drug. This article summarizes PBPK-based submissions evaluating the role of drug transporters to the Office of Clinical Pharmacology of the US Food and Drug Administration. [ABSTRACT FROM AUTHOR]

Whole-body physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development for their ability to predict drug concentrations in clinically relevant tissues and to extrapolate across species, experimental conditions and sub-populations. A whole-body PBPK model can be fitted to clinical data using a Bayesian population approach. However, the analysis might be time consuming and numerically unstable if prior information on the model parameters is too vague given the complexity of the system. We suggest an approach where (i) a whole-body PBPK model is formally reduced using a Bayesian proper lumping method to retain the mechanistic interpretation of the system and account for parameter uncertainty, (ii) the simplified model is fitted to clinical data using Markov Chain Monte Carlo techniques and (iii) the optimised reduced PBPK model is used for extrapolation. A previously developed 16-compartment whole-body PBPK model for mavoglurant was reduced to 7 compartments while preserving plasma concentration-time profiles (median and variance) and giving emphasis to the brain (target site) and the liver (elimination site). The reduced model was numerically more stable than the whole-body model for the Bayesian analysis of mavoglurant pharmacokinetic data in healthy adult volunteers. Finally, the reduced yet mechanistic model could easily be scaled from adults to children and predict mavoglurant pharmacokinetics in children aged from 3 to 11 years with similar performance compared with the whole-body model. This study is a first example of the practicality of formal reduction of complex mechanistic models for Bayesian inference in drug development. [ABSTRACT FROM AUTHOR]

DZNep is a potential epigenetic drug, and exerts potent anti-proliferative and pro-apoptotic effects on broad-spectrum carcinomas via disruption of the EZH2 pathway. Antitumor studies on DZNep have been stuck in the preclinical phase because of the lack of information about its integral pharmacokinetic (PK) properties. To circumvent this problem, we extensively investigated the disposition characteristics of the DZNep in rats. By incorporating the disposition data across species into a whole-body physiologically based pharmacokinetic (PBPK) models using the GastroPlus TM software, we simulated human PK properties of DZNep and determined whether DZNep could be developed for human cancer therapy. Firstly, DZNep was found to cause nephrotoxicity in a dose-dependent manner in rats and its safe dose was determined to be 10 mg/kg. DZNep showed a short plasma elimination half-life (1.1 h) in rats, a low protein binding in plasma (18.5%), a low partitioning to erythrocyte (0.78), and a low intrinsic hepatic clearance in rats and humans. There was extensive tissue distribution and predominant renal excretion (80.3%). The simulated rat PBPK model of DZNep was well-verified with satisfactory coefficients of determination for all the tested tissues ( R 2 > 0.781). The simulated human PBPK model successfully identified that intravenous administration of DZNep at appropriate dosing regimen could be further developed for human non-small cell lung carcinoma treatments. The present findings provide valuable information regarding experimental or in silico PK characteristics of DZNep in rats and humans, which is helpful to guide future studies of DZNep in both preclinical and clinical phases. [ABSTRACT FROM AUTHOR]

During the last decades, the importance of modeling and simulation in clinical drug development, with the goal to qualitatively and quantitatively assess and understand mechanisms of pharmacokinetic processes, has strongly increased. However, this increase could not equally be observed for orally inhaled drugs. The objectives of this review are to understand the reasons for this gap and to demonstrate the opportunities that mathematical modeling of pharmacokinetics of orally inhaled drugs offers. To achieve these objectives, this review (i) discusses pulmonary physiological processes and their impact on the pharmacokinetics after drug inhalation, (ii) provides a comprehensive overview of published pharmacokinetic models, (iii) categorizes these models into physiologically based pharmacokinetic (PBPK) and (clinical data-derived) empirical models, (iv) explores both their (mechanistic) plausibility, and (v) addresses critical aspects of different pharmacometric approaches pertinent for drug inhalation. In summary, pulmonary deposition, dissolution, and absorption are highly complex processes and may represent the major challenge for modeling and simulation of PK after oral drug inhalation. Challenges in relating systemic pharmacokinetics with pulmonary efficacy may be another factor contributing to the limited number of existing pharmacokinetic models for orally inhaled drugs. Investigations comprising in vitro experiments, clinical studies, and more sophisticated mathematical approaches are considered to be necessary for elucidating these highly complex pulmonary processes. With this additional knowledge, the PBPK approach might gain additional attractiveness. Currently, (semi-)mechanistic modeling offers an alternative to generate and investigate hypotheses and to more mechanistically understand the pulmonary and systemic pharmacokinetics after oral drug inhalation including the impact of pulmonary diseases. [ABSTRACT FROM AUTHOR]

Objectives To develop a physiologically based pharmacokinetic ( PBPK) model for furosemide immediate release ( IR) tablets and modified release ( MR) capsules by coupling biorelevant dissolution testing results with pharmacokinetic ( PK) and physiologic parameters, and to investigate the key factors influencing furosemide absorption using simulation approaches and the PBPK model. Methods Using solubility, dissolution kinetics, gastrointestinal ( GI) parameters and disposition parameters, a PBPK model for furosemide was developed with STELLA software. Solubility and dissolution profiles for both formulations were evaluated in biorelevant and compendial media. The simulated plasma profiles were compared with in-vivo profiles using point estimates of area under plasma concentration-time curve, maximal concentration after the dose and time to maximal concentration after the dose. Key findings Simulated plasma profiles of both furosemide IR tablets and MR capsules were similar to the observed in-vivo profile in terms of PK parameters. Sensitivity analysis of the IR tablet model indicated that both the gastric emptying and absorption rate have an influence on the plasma profile. For the MR capsules, the sensitivity analysis suggested that the release rate in the small intestine, gastric emptying and the absorption rate all have an influence on the plasma profile. Conclusions A predictive model to describe both IR and MR dosage forms containing furosemide was attained. Because sensitivity analysis of the model is able to identify key factors influencing the plasma profile, this in-vitro-in-silico-in-vivo approach could be a useful tool for facilitating formulation development of drug products. [ABSTRACT FROM AUTHOR]

Objectives To summarize the basis for and progress with the development of in-vitro-in-silico-in-vivo ( IV-IS- IV) relationships for oral dosage forms using physiologically based pharmacokinetic ( PBPK) modelling, with the focus on predicting the performance of solid oral dosage forms in humans. Key findings Various approaches to forecasting oral absorption have been reported to date. These range from simple dissolution tests, through biorelevant dissolution testing and laboratory simulations of the gastrointestinal ( GI) tract, to the use of PBPK modelling to predict oral drug absorption based on the physicochemical parameters of the drug substance. Although each of these approaches can be useful for qualitative predictions, forecasting oral absorption on a quantitative basis with an individual approach is only possible for selected drug/dosage form combinations. By integrating biorelevant dissolution test results with the PBPK models, it has become possible to achieve quantitatively accurate as well as qualitative predictions of plasma profiles after oral dosing for both immediate and modified release formulations. Summary With further refinement of both the biorelevant dissolution testing methods and the PBPK models, it should be possible to expedite the development and regulatory approval of optimized dosage forms and dosing conditions. [ABSTRACT FROM AUTHOR]

Background The instantaneous rate of change of alcohol exposure (slope) may contribute to changes in measures of brain function following administration of alcohol that are usually attributed to breath alcohol concentration ( BrAC) acting alone. To test this proposition, a 2-session experiment was designed in which carefully prescribed, constant-slope trajectories of BrAC intersected at the same exposure level and time since the exposure began. This paper presents the methods and limitations of the experimental design. Methods Individualized intravenous infusion rate profiles of 6% ethanol (EtOH) that achieved the constant-slope trajectories for an individual were precomputed using a physiologically based pharmacokinetic model. Adjusting the parameters of the model allowed each infusion profile to account for the subject's EtOH distribution and elimination kinetics. Sessions were conducted in randomized order and made no use of feedback of BrAC measurements obtained during the session to modify the precalculated infusion profiles. In one session, an individual's time course of exposure, BrAC( t), was prescribed to rise at a constant rate of 6.0 mg% per minute until it reached 68 mg% and then descend at −1.0 mg% per minute; in the other, to rise at a rate of 3.0 mg% per minute. The 2 exposure trajectories were designed to intersect at a BrAC ( t = 20 minutes) = 60 mg% at an experimental time of 20 minutes. Results Intersection points for 54 of 61 subjects were within prescribed deviations (range of ±3 mg% and ±4 minutes from the nominal intersection point). Conclusions Results confirmed the feasibility of applying the novel methods for achieving the intended time courses of the BrAC, with technical problems limiting success to 90% of the individuals tested. [ABSTRACT FROM AUTHOR]

High-quality, in vitro screening tools are essential in identifying promising compounds during drug development. Tests with currently used cell-based assays provide an indication of a compound's potential therapeutic benefits to the target tissue, but not to the whole body. Data obtained with animal models often cannot be extrapolated to humans. Multicompartment microfluidic-based devices, particularly those that are physical representations of physiologically based pharmacokinetic (PBPK) models, may contribute to improving the drug development process. These scaled-down devices, termed micro cell culture analogs (μμCCAs) or body-on-a-chip devices, can simulate multitissue interactions under near-physiological fluid flow conditions and with realistic tissue-to-tissue size ratios. Because the device can be used with both animal and human cells, it can facilitate cross-species extrapolation. Used in conjunction with PBPK models, the devices permit an estimation of effective concentrations that can be used for studies with animal models or predict the human response. The devices also provide a means for relatively high-throughput screening of drug combinations and, when utilized with a patient's tissue sample, an opportunity for individualized medicine. Here we review efforts made toward the development of microfabricated cell culture systems and give examples that demonstrate their potential use in drug development, such as identifying synergistic drug interactions as well as simulating multiorgan metabolic interactions. In addition to their use in drug development, the devices also can be used to estimate the toxicity of chemicals as occupational hazards and environmental contaminants. [ABSTRACT FROM AUTHOR]

Abstract: The U.S. Environmental Protection Agency''s (EPA) Integrated Risk Information System (IRIS) Program develops assessments of health effects that may result from chronic exposure to chemicals in the environment. The IRIS database contains more than 540 assessments. When supported by available data, IRIS assessments provide quantitative analyses of carcinogenic effects. Since publication of EPA''s 2005 Guidelines for Carcinogen Risk Assessment, IRIS cancer assessments have implemented new approaches recommended in these guidelines and expanded the use of complex scientific methods to perform quantitative dose–response assessments. Two case studies of the application of the mode of action framework from the 2005 Cancer Guidelines are presented in this paper. The first is a case study of 1,2,3-trichloropropane, as an example of a chemical with a mutagenic mode of carcinogenic action thus warranting the application of age-dependent adjustment factors for early-life exposure; the second is a case study of ethylene glycol monobutyl ether, as an example of a chemical with a carcinogenic action consistent with a nonlinear extrapolation approach. The use of physiologically based pharmacokinetic (PBPK) modeling to quantify interindividual variability and account for human parameter uncertainty as part of a quantitative cancer assessment is illustrated using a case study involving probabilistic PBPK modeling for dichloromethane. We also discuss statistical issues in assessing trends and model fit for tumor dose–response data, analysis of the combined risk from multiple types of tumors, and application of life-table methods for using human data to derive cancer risk estimates. These issues reflect the complexity and challenges faced in assessing the carcinogenic risks from exposure to environmental chemicals, and provide a view of the current trends in IRIS carcinogenicity risk assessment. [Copyright &y& Elsevier]

(i) To describe an example of the development work required for building a 'pediatric physiologically based pharmacokinetic' (P-PBPK) model (Simcyp Pediatric ADME Simulator), (ii) to replicate pediatric clinical studies and undertake theoretical studies to show the potential applications of mechanistic PBPK in pediatric drug clinical investigation and practice, with emphasis on pediatric anesthesia. PBPK models draw together the physiological and biochemical information that determine drug absorption, distribution, metabolism, and excretion and then link them in a physiologically realistic 'systems' model. Incorporating the emerging additional information on developmental physiology and biochemistry has resulted in the creation of P-PBPK. There has been a renewed interest in the application of such modeling by the pharmaceutical industry to improve the efficiency of drug development, especially in populations where designing and conducting clinical studies is more challenging, such as pediatric patients. P-PBPK was used to simulate a number of published clinical studies and clinical case scenarios with the aim of highlighting the potential applications. Changing the P-PBPK model parameters in a number of 'what if' simulations were used to explore the likely underlying reasons for observed pharmacokinetic (PK) behavior of drugs in critically ill children. In addition, the use of P-PBPK models to predict complex drug-drug interactions (DDI) highlighted disparities with adult populations. The examples highlight the use of prior knowledge of in vitro drug attributes and biology of the system (human body) to simulate PK and multiple DDI scenarios not infrequently encountered in critically ill pediatric patients. [ABSTRACT FROM AUTHOR]

Pediatric pharmacokinetic and pediatric safety and efficacy studies are, in most cases, a mandatory activity during the drug development process in North America and Europe. Pharmacokinetic modeling in anticipation of the pediatric clinical trial should take a data or knowledge-driven approach by employing either top-down or bottom-up approaches to assessing differential age-related dosing. These two approaches depend on different starting information and are likely to be used in conjunction with each other for the purposes of defining pediatric dosing guidelines. This review primarily focuses on the available bottom-up, mechanistic models for predicting age-dependent drug absorption, distribution and elimination, and their integration through the whole-body physiologically based pharmacokinetic (PBPK) model. The bottom-up approach incorporating adult and pediatric whole-body PBPK models for optimizing age-related dosing is detailed for a drug currently undergoing pediatric development. [ABSTRACT FROM AUTHOR]

This report describes a physiologically based pharmacokinetic model for cyclohexane and its use in comparing internal doses in rats and volunteers following inhalation exposures. Parameters describing saturable metabolism of cyclohexane are measured in rats and used along with experimentally determined partition coefficients. The model is evaluated by comparing predicted blood and brain concentrations to data from studies in rats and then allometrically scaling the results to humans. Levels of cyclohexane in blood and exhaled air are measured in human volunteers and compared with model values. The model predicts that exposure of volunteers to cyclohexane at levels of 4100 mg/m3 (*1200 ppm) will result in brain levels similar to those in rats exposed to 8000 mg/m3 (the no-effect level for acute central nervous system effects). There are no acute central nervous system effects in humans exposed to 860 mg/m3, consistent with model predictions that current occupational exposure levels for cyclohexane protect against acute central nervous system effects. [ABSTRACT FROM PUBLISHER]

Three regression methods, namely ridge regression (RR), partial least squares (PLS), and principal components regression (PCR), were used to develop models for the prediction of rat blood:air partition coefficient for increasingly diverse data sets. Initially, modeling was performed for a set of 13 chlorocarbons. To this set, 10 additional hydrophobic compounds were added, including aromatic and non-aromatic hydrocarbons. A set of 16 hydrophilic compounds was also modeled separately. Finally, all 39 compounds were combined into one data set for which comprehensive models were developed. A large set of diverse, theoretical molecular descriptors was calculated for use in the current study. The topostructural (TS), topochemical (TC), and geometrical or 3-dimensional (3D) indices were used hierarchically in model development. In addition, single-class models were developed using the TS, TC, and 3D descriptors. In most cases, RR outperformed PLS and PCR, and the models developed using TC indices were superior to those developed using other classes of descriptors. [Copyright &y& Elsevier]

In whole-body physiologically based pharmacokinetic (PBPK) models, each tissue or organ is frequently portrayed as a single well-mixed compartment with distribution, perfusion rate limited. However, single-pass profiles from isolated organ studies are more adequately described by models which display an intermediate degree of mixing. One such model is the dispersion model, which successfully describes the outflow profiles from the liver and the perfused hindlimb of many compounds, under a variety of conditions. A salient parameter of this model is the dispersion number, a dimensionless term, which characterizes the relative axial spreading of compound on transit through the organ. We have developed a whole-body PBPK model wherein the distribution of drug on transit through each organ is described by the dispersion model with closed boundary conditions incorporated. The model equations were numerically solved using finite differencing methods, in particular, the method of lines. An integrating routine suitable for solving stiff sets of equations was used. Physiological parameters, blood flows, and tissue volumes, were taken from the literature, as were the tissue dispersion numbers, which characterize the mixing properties of each tissue; where none could be found, the value was set as that for liver. On solution, tissue, venous and arterial blood concentration–time profiles are generated. The profiles exhibited both short and long time characteristics. Oscillations were observed in the venous and arterial profiles over the first 10 min of simulation for the rat. On scale-up to human, the effects were seen over a 30 min period. Longer time effects of tissue distribution involve buildup of drug in the large tissues of distribution: skeletal muscle, skin, and adipose. The extent of distribution in the large tissues was somewhat dependent on the magnitude of the dispersion number, the lower the dispersion number, the greater the extent of distribution after an intravenous bolus dose. The model has a distinct advantage over the well-stirred organ whole-body PBPK model in its ability to describe both short and long time characteristics. [ABSTRACT FROM AUTHOR]

The kinetics of disposition of drugs and environmental chemicals will be altered as a result of the rapid and pronounced anatomic and physiologic changes that occur during pregnancy. These include changes in maternal intestinal motility, pulmonary tidal volume and minute volume, cardiac output, and renal function as well as in maternal tissue and fluid volumes and in the weight of the embryo/fetus and its developing organs. Physiologically-based models of pregnancy are capable of taking these temporal changes into account. Several such models have been developed. They vary in their characteristics, depending on the chemical under consideration and the period of gestation of concern to the developers of the models. Several physiologically-based models of gestation are outlined, and an example is given of the application of a physiologically-based model of gestation to predict dose to the rat and mouse fetus. [ABSTRACT FROM AUTHOR]

The parameters in a physiologically based pharmacokinetic (PBPK) model of methylene chloride were varied systematically, and the resulting variation in a number of model outputs was determined as a function of time for mice and humans at several exposure concentrations. The importance of the various parameters in the model was highly dependent on the conditions (concentration, species) for which the simulation was performed and the model output (dose surrogate) being considered. Model structure also had a significant impact on the results. For sensitivity analysis, particular attention must be paid to conservation equations to ensure that the variational calculations do not alter mass balance, introducing extraneous effects into the model. All of the normalized sensitivity coefficients calculated in this study ranged between -1.12 and 1, and most were much less than 1 in absolute value, indicating that individual input errors are not greatly amplified in the outputs. In addition to ranking parameters in terms of their impact on model predictions, time-dependent sensitivity analysis can also be used as an aid in the design of experiments to estimate parameters by predicting the experimental conditions and sampling points which will maximize parameter identifiability. [ABSTRACT FROM AUTHOR]

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)

Single-pass intestinal perfusion( SPIP) is the common carrier of biopharmaceutics classification system( BCS) to study compound permeability. With the application and deepening study of BCS in the field of traditional Chinese medicine( TCM),SPIP model is becoming more and more common to study the intestinal absorption of TCM ingredients. Based on the limitations of the SPIP model in some researches on TCM permeability,it was speculated in this study that aglycone may be more suitable than the glycoside to study the intestinal absorption problem by using SPIP model. Furthermore,applicability of aglycone components was analyzed and evaluated. In this study,with quercetin,daidzein,formononetin,genistein and glycyrrhetinic acid used as research objects,the quantitative study of SPIP was used to evaluate the intestinal permeability of these aglycones and to predict the effective permeability coefficient( Peff) and absorption fraction( Fa) in human body. By combining studies comparison and analysis on multiple permeability research methods and prediction of human body absorption of aglycones in physiological-based pharmacokinetic models,this paper can further illustrate that the SPIP model is a good tool for studying the permeability of aglycones and predicting human absorption,which can provide data foundation and theoretical reference for researches on SPIP technique and BCS in intestinal absorption of TCM ingredients.

Central-nervous-system, physiologically based pharmacokinetic (PBPK) models predict exposure profiles in the brain, that is, the rate and extent of distribution. The current work develops one such model and presents improved methods for determining key input parameters. A simple linear regression statistical model estimates the passive permeability at the blood-brain barrier from brain uptake index data and descriptors, and a novel analysis extracts the relative active transport parameter from in vitro assays taking into consideration both paracellular transport and unstirred water layers. The integrated PBPK model captures the concentration profiles of both rate-restricted and effluxed compounds with high passive permeability. In many cases, compounds distribute rapidly into the brain and are, therefore, not rate limited. The PBPK model is then simplified to a straightforward equation to describe brain-to-plasma ratios at steady state. The equation can estimate brain penetration either from in vitro efflux data or from in vivo results from another species and, therefore, is a valuable tool in the discovery setting., (Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)