Special Issue "Application of Translational Mathematical Modeling in Drug Development"

A special issue of Pharmaceutics (ISSN 1999-4923).

Deadline for manuscript submissions: closed (31 January 2019)

Special Issue Editors

Guest Editor
Prof. Beom Soo Shin

Sungkyunkwan University, School of Pharmacy, Suwon, Gyeonggi-do 16419, Republic of Korea
Website | E-Mail
Phone: +82-31-290-7705
Interests: pharmacokinetics; translational PKPD modeling; PBPK modeling; in vitro–in vivo correlation; pharmaceutical analysis
Guest Editor
Prof. Jürgen B. Bulitta

University of Florida, College of Pharmacy, Orlando FL 32827, USA
Website | E-Mail
Interests: drug discovery; drug development; optimal patient therapies; pharmacokinetics; pharmacodynamics; translational pharmacology

Special Issue Information

Dear Colleagues,

Despite great advances in biomedical science and technology, as well as increasing research and development spending, the success rates in drug development remain low with a declining trend. Translational, model-based drug development can improve the rigor and efficiency of drug development by employing pharmacokinetic and pharmacodynamic principles to describe and predict drug behavior. This allows us to better understand mechanisms and exploit them for drug development. Modelling and simulations presents a powerful approach to integrate information from different stages of drug development and support decision making. In turn, this enables the design of more informative studies, saving cost and time, and ultimately enhance the success rates of drug development. Model-based drug development is a paradigm that covers the whole spectrum of the drug development process.

This Special Issue is intended to cover a broad range of topics in translational mathematical modelling applied to drug development. This includes, but is not limited to, pharmacokinetic/pharmacodynamic (PK/PD) models, physiologically-based pharmacokinetic (PBPK) models, population models, in vitro-in vivo correlations (IVIVC), and systems pharmacology approaches. We seek to highlight recent advances and innovations in this area and invite the researchers and drug developers to contribute their original research work or review articles.

Prof. Beom Soo Shin
Prof. Jürgen B. Bulitta
Guest Editors

Manuscript Submission Information

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Keywords

  • Pharmacokinetics
  • Pharmacodynamics
  • Modeling and simulation
  • Physiologically based pharmacokinetic modeling
  • Population modeling
  • Translational pharmacology
  • Quantitative systems pharmacology
  • In vitro-in vivo correlations
  • Interspecies scaling

Published Papers (13 papers)

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Research

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Open AccessArticle
Novel Population Pharmacokinetic Approach to Explain the Differences between Cystic Fibrosis Patients and Healthy Volunteers via Protein Binding
Pharmaceutics 2019, 11(6), 286; https://doi.org/10.3390/pharmaceutics11060286 (registering DOI)
Received: 31 March 2019 / Revised: 16 May 2019 / Accepted: 17 May 2019 / Published: 18 June 2019
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Abstract
The pharmacokinetics in patients with cystic fibrosis (CF) has long been thought to differ considerably from that in healthy volunteers. For highly protein bound β-lactams, profound pharmacokinetic differences were observed between comparatively morbid patients with CF and healthy volunteers. These differences could be [...] Read more.
The pharmacokinetics in patients with cystic fibrosis (CF) has long been thought to differ considerably from that in healthy volunteers. For highly protein bound β-lactams, profound pharmacokinetic differences were observed between comparatively morbid patients with CF and healthy volunteers. These differences could be explained by body weight and body composition for β-lactams with low protein binding. This study aimed to develop a novel population modeling approach to describe the pharmacokinetic differences between both subject groups by estimating protein binding. Eight patients with CF (lean body mass [LBM]: 39.8 ± 5.4kg) and six healthy volunteers (LBM: 53.1 ± 9.5kg) received 1027.5 mg cefotiam intravenously. Plasma concentrations and amounts in urine were simultaneously modelled. Unscaled total clearance and volume of distribution were 3% smaller in patients with CF compared to those in healthy volunteers. After allometric scaling by LBM to account for body size and composition, the remaining pharmacokinetic differences were explained by estimating the unbound fraction of cefotiam in plasma. The latter was fixed to 50% in male and estimated as 54.5% in female healthy volunteers as well as 56.3% in male and 74.4% in female patients with CF. This novel approach holds promise for characterizing the pharmacokinetics in special patient populations with altered protein binding. Full article
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Open AccessArticle
Physiologically Relevant In Vitro-In Vivo Correlation (IVIVC) Approach for Sildenafil with Site-Dependent Dissolution
Pharmaceutics 2019, 11(6), 251; https://doi.org/10.3390/pharmaceutics11060251
Received: 9 May 2019 / Revised: 28 May 2019 / Accepted: 29 May 2019 / Published: 1 June 2019
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Abstract
This study aimed to establish a physiologically relevant in vitro-in vivo correlation (IVIVC) model reflecting site-dependent dissolution kinetics for sildenafil based on population-pharmacokinetic (POP-PK) modeling. An immediate release (IR, 20 mg) and three sustained release (SR, 60 mg) sildenafil tablets were prepared by [...] Read more.
This study aimed to establish a physiologically relevant in vitro-in vivo correlation (IVIVC) model reflecting site-dependent dissolution kinetics for sildenafil based on population-pharmacokinetic (POP-PK) modeling. An immediate release (IR, 20 mg) and three sustained release (SR, 60 mg) sildenafil tablets were prepared by wet granulation method. In vitro dissolutions were determined by the paddle method at pH 1.2, 4.5, and 6.8 media. The in vivo pharmacokinetics were assessed after oral administration of the prepared IR and SR formulations to Beagle dogs (n = 12). The dissolution of sildenafil from SR formulations was incomplete at pH 6.8, which was not observed at pH 1.2 and pH 4.5. The relative bioavailability was reduced with the decrease of the dissolution rate. Moreover, secondary peaks were observed in the plasma concentration-time curves, which may result from site-dependent dissolution. Thus, a POP-PK model was developed to reflect the site-dependent dissolution by separately describing the dissolution and absorption processes, which allowed for estimation of the in vivo dissolution of sildenafil. Finally, an IVIVC was established and validated by correlating the in vitro and in vivo dissolution rates. The present approach may be applied to establish IVIVC for various drugs with complex dissolution kinetics for the development of new formulations. Full article
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Open AccessArticle
Application of Pharmacometrics in Pharmacotherapy: Open-Source Software for Vancomycin Therapeutic Drug Management
Pharmaceutics 2019, 11(5), 224; https://doi.org/10.3390/pharmaceutics11050224
Received: 18 February 2019 / Revised: 31 March 2019 / Accepted: 30 April 2019 / Published: 9 May 2019
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Abstract
The population pharmacokinetic (PK) parameters that are implemented in therapeutic drug management (TDM) software were generally obtained from a Western population and might not be adequate for PK prediction with a Korean population. This study aimed to develop a population PK model for [...] Read more.
The population pharmacokinetic (PK) parameters that are implemented in therapeutic drug management (TDM) software were generally obtained from a Western population and might not be adequate for PK prediction with a Korean population. This study aimed to develop a population PK model for vancomycin using Korean data to improve the quality of TDM for Korean patients. A total of 220 patients (1020 observations) who received vancomycin TDM services were included in the dataset. A population PK analysis was performed using non-linear mixed effects modeling, and a covariate evaluation was conducted. A two-compartment model with first-order elimination best explained the vancomycin PK, with estimates of 2.82 L/h, 31.8 L, 11.7 L/h, and 75.4 L for CL, V1, Q, and V2, respectively. In the covariate analysis, weight correlated with the volume of the peripheral compartment, and creatinine clearance, hemodialysis, and continuous renal replacement therapy treatments contributed to the clearance of vancomycin. The results show the clear need to optimize the PK parameters used for TDM in Korean patients. Specifically, V1 should be smaller for Korean patients, and renal replacement therapies should be considered in TDM practice. This final model was successfully applied in R shiny as open-source software for Koreans. Full article
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Open AccessArticle
Biodistribution and Physiologically-Based Pharmacokinetic Modeling of Gold Nanoparticles in Mice with Interspecies Extrapolation
Pharmaceutics 2019, 11(4), 179; https://doi.org/10.3390/pharmaceutics11040179
Received: 14 February 2019 / Revised: 4 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
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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 [...] Read more.
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. Full article
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Open AccessArticle
Translational PBPK Modeling of the Protein Therapeutic and CD95L Inhibitor Asunercept to Develop Dose Recommendations for Its First Use in Pediatric Glioblastoma Patients
Pharmaceutics 2019, 11(4), 152; https://doi.org/10.3390/pharmaceutics11040152
Received: 27 January 2019 / Revised: 19 March 2019 / Accepted: 22 March 2019 / Published: 1 April 2019
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Abstract
The protein therapeutic and CD95L inhibitor asunercept is currently under clinical investigation for the treatment of glioblastoma and myelodysplastic syndrome. The purpose of this study was to predict the asunercept pharmacokinetics in children and to give dose recommendations for its first use in [...] Read more.
The protein therapeutic and CD95L inhibitor asunercept is currently under clinical investigation for the treatment of glioblastoma and myelodysplastic syndrome. The purpose of this study was to predict the asunercept pharmacokinetics in children and to give dose recommendations for its first use in pediatric glioblastoma patients. A physiologically-based pharmacokinetic (PBPK) model of asunercept in healthy and diseased adults was successfully developed using the available clinical Phase I and Phase II study data. This model was then extrapolated to different pediatric populations, to predict the asunercept exposure in children and to find equivalent starting doses. Simulation of the asunercept serum concentration-time curves in children between 1–18 years of age shows that a dosing regimen based on body weight results in a similar asunercept steady-state exposure in all patients (pediatric or adult) above 12 years of age. For children between 1–12 years, higher doses per kg body weight are recommended, with the highest dose for the very young patients. Translational PBPK modeling is strongly encouraged by regulatory agencies to help with the initial dose selection for pediatric trials. To our knowledge, this is the first report of pediatric PBPK to support the dose selection of a therapeutic protein before its administration to children. Full article
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Open AccessArticle
Effects of Verapamil and Diltiazem on the Pharmacokinetics and Pharmacodynamics of Rivaroxaban
Pharmaceutics 2019, 11(3), 133; https://doi.org/10.3390/pharmaceutics11030133
Received: 30 January 2019 / Revised: 8 March 2019 / Accepted: 15 March 2019 / Published: 19 March 2019
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Abstract
Concomitant use of rivaroxaban with non-dihydropyridine calcium channel blockers (non-DHPs) might lead to an increase of systemic rivaroxaban exposure and anticoagulant effects in relation to the inhibition of metabolic enzymes and/or transporters by non-DHPs. This study was designed to evaluate the effects of [...] Read more.
Concomitant use of rivaroxaban with non-dihydropyridine calcium channel blockers (non-DHPs) might lead to an increase of systemic rivaroxaban exposure and anticoagulant effects in relation to the inhibition of metabolic enzymes and/or transporters by non-DHPs. This study was designed to evaluate the effects of verapamil and diltiazem on the pharmacokinetics and the prolongation of prothrombin time of rivaroxaban in rats. The data were analyzed using a pharmacokinetic/pharmacodynamics (PK/PD) modeling approach to quantify the influence of verapamil. Verapamil increased the systemic exposure of rivaroxaban by 2.8-fold (p <0.001) which was probably due to the inhibition of efflux transportation rather than metabolism. Prothrombin time was also prolonged in a proportional manner; diltiazem did not show any significant effects, however. A transit PK model in the absorption process comprehensively describes the double-peaks of rivaroxaban plasma concentrations and the corresponding change of prothrombin time with a simple linear relationship. The slope of prothrombin time vs. rivaroxaban plasma concentration in rats was retrospectively found to be insensitive by about 5.4-fold compared to than in humans. More than a 67% dose reduction in rivaroxaban is suggested in terms of both a pharmacokinetic point of view, and the sensitivity differences on the prolongation of prothrombin time when used concomitantly with verapamil. Full article
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Open AccessArticle
Mathematical Modelling of Intravenous Thrombolysis in Acute Ischaemic stroke: Effects of Dose Regimens on Levels of Fibrinolytic Proteins and Clot Lysis Time
Pharmaceutics 2019, 11(3), 111; https://doi.org/10.3390/pharmaceutics11030111
Received: 4 February 2019 / Revised: 28 February 2019 / Accepted: 3 March 2019 / Published: 7 March 2019
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Abstract
Thrombolytic therapy is one of the medical procedures in the treatment of acute ischaemic stroke (AIS), whereby the tissue plasminogen activator (tPA) is intravenously administered to dissolve the obstructive blood clot. The treatment of AIS by thrombolysis can sometimes be ineffective and it [...] Read more.
Thrombolytic therapy is one of the medical procedures in the treatment of acute ischaemic stroke (AIS), whereby the tissue plasminogen activator (tPA) is intravenously administered to dissolve the obstructive blood clot. The treatment of AIS by thrombolysis can sometimes be ineffective and it can cause serious complications, such as intracranial haemorrhage (ICH). In this study, we propose an efficient mathematical modelling approach that can be used to evaluate the therapeutic efficacy and safety of thrombolysis in various clinically relevant scenarios. Our model combines the pharmacokinetics and pharmacodynamics of tPA with local clot lysis dynamics. By varying the drug dose, bolus-infusion delay time, and bolus-infusion ratio, with the FDA approved dosing protocol serving as a reference, we have used the model to simulate 13 dose regimens. Simulation results are compared for temporal concentrations of fibrinolytic proteins in plasma and the time that is taken to achieve recanalisation. Our results show that high infusion rates can cause the rapid degradation of plasma fibrinogen, indicative of increased risk for ICH, but they do not necessarily lead to fast recanalisation. In addition, a bolus-infusion delay results in an immediate drop in plasma tPA concentration, which prolongs the time to achieve recanalisation. Therefore, an optimal administration regimen should be sought by keeping the tPA level sufficiently high throughout the treatment and maximising the lysis rate while also limiting the degradation of fibrinogen in systemic plasma. This can be achieved through model-based optimisation in the future. Full article
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Open AccessArticle
Physiologically-Based Pharmacokinetic Modeling for Drug-Drug Interactions of Procainamide and N-Acetylprocainamide with Cimetidine, an Inhibitor of rOCT2 and rMATE1, in Rats
Pharmaceutics 2019, 11(3), 108; https://doi.org/10.3390/pharmaceutics11030108
Received: 18 February 2019 / Revised: 1 March 2019 / Accepted: 3 March 2019 / Published: 6 March 2019
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Abstract
Previous observations demonstrated that cimetidine decreased the clearance of procainamide (PA) and/or N-acetylprocainamide (NAPA; the primary metabolite of PA) resulting in the increased systemic exposure and the decrease of urinary excretion. Despite an abundance of in vitro and in vivo data regarding [...] Read more.
Previous observations demonstrated that cimetidine decreased the clearance of procainamide (PA) and/or N-acetylprocainamide (NAPA; the primary metabolite of PA) resulting in the increased systemic exposure and the decrease of urinary excretion. Despite an abundance of in vitro and in vivo data regarding pharmacokinetic interactions between PA/NAPA and cimetidine, however, a mechanistic approach to elucidate these interactions has not been reported yet. The primary objective of this study was to construct a physiological model that describes pharmacokinetic interactions between PA/NAPA and cimetidine, an inhibitor of rat organic cation transporter 2 (rOCT2) and rat multidrug and toxin extrusion proteins (rMATE1), by performing extensive in vivo and in vitro pharmacokinetic studies for PA and NAPA performed in the absence or presence of cimetidine in rats. When a single intravenous injection of PA HCl (10 mg/kg) was administered to rats, co-administration of cimetidine (100 mg/kg) significantly increased systemic exposure and decreased the systemic (CL) and renal (CLR) clearance of PA, and reduced its tissue distribution. Similarly, cimetidine significantly decreased the CLR of NAPA formed by the metabolism of PA and increased the AUC of NAPA. Considering that these drugs could share similar renal secretory pathways (e.g., via rOCT2 and rMATE1), a physiologically-based pharmacokinetic (PBPK) model incorporating semi-mechanistic kidney compartments was devised to predict drug-drug interactions (DDIs). Using our proposed PBPK model, DDIs between PA/NAPA and cimetidine were successfully predicted for the plasma concentrations and urinary excretion profiles of PA and NAPA observed in rats. Moreover, sensitivity analyses of the pharmacokinetics of PA and NAPA showed the inhibitory effects of cimetidine via rMATE1 were probably important for the renal elimination of PA and NAPA in rats. The proposed PBPK model may be useful for understanding the mechanisms of interactions between PA/NAPA and cimetidine in vivo. Full article
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Open AccessArticle
Simulation-Based Analysis of the Impact of Renal Impairment on the Pharmacokinetics of Highly Metabolized Compounds
Pharmaceutics 2019, 11(3), 105; https://doi.org/10.3390/pharmaceutics11030105
Received: 29 January 2019 / Revised: 25 February 2019 / Accepted: 27 February 2019 / Published: 2 March 2019
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Abstract
Renal impairment (RI) is a highly prevalent disease which can alter the pharmacokinetics (PK) of xenobiotics, including those that are predominately metabolized. The expression and activity of drug metabolizing enzymes (DMEs) and protein binding of compounds has been demonstrated to be affected in [...] Read more.
Renal impairment (RI) is a highly prevalent disease which can alter the pharmacokinetics (PK) of xenobiotics, including those that are predominately metabolized. The expression and activity of drug metabolizing enzymes (DMEs) and protein binding of compounds has been demonstrated to be affected in RI. A simulation based approach allows for the characterization of the impact of changes in these factors on the PK of compounds which are highly metabolized and allows for improved prediction of PK in RI. Simulations with physiologically based pharmacokinetic (PBPK) modeling was utilized to define the impact of these factors in PK in RI for a model substrate, nifedipine. Changes in fraction unbound and DME expression/activity had profound effects on PK in RI. Increasing fraction unbound and DME expression resulted in a reduction in exposure of nifedipine, while the reduction of DME activity resulted in an increase in exposure. In vitro and preclinical data were utilized to inform simulations for nifedipine, sildenafil and zidovudine. Increasing fraction unbound and changes in the expression/activity of DMEs led to improved predictions of PK. Further characterization of the impact of RI on these factors is warranted in order to better inform a priori predictions of PK in RI. Full article
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Open AccessArticle
A Cell-Level Systems PK-PD Model to Characterize In Vivo Efficacy of ADCs
Pharmaceutics 2019, 11(2), 98; https://doi.org/10.3390/pharmaceutics11020098
Received: 25 January 2019 / Revised: 18 February 2019 / Accepted: 20 February 2019 / Published: 25 February 2019
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Abstract
Here, we have presented the development of a systems pharmacokinetics-pharmacodynamics (PK-PD) model for antibody-drug conjugates (ADCs), which uses intracellular target occupancy to drive in-vivo efficacy. The model is built based on PK and efficacy data generated using Trastuzumab-Valine-Citrulline-Monomethyl Auristatin E (T-vc-MMAE) ADC in [...] Read more.
Here, we have presented the development of a systems pharmacokinetics-pharmacodynamics (PK-PD) model for antibody-drug conjugates (ADCs), which uses intracellular target occupancy to drive in-vivo efficacy. The model is built based on PK and efficacy data generated using Trastuzumab-Valine-Citrulline-Monomethyl Auristatin E (T-vc-MMAE) ADC in N87 (high-HER2) and GFP-MCF7 (low-HER2) tumor bearing mice. It was observed that plasma PK of all ADC analytes was similar between the two tumor models; however, total trastuzumab, unconjugated MMAE, and total MMAE exposures were >10-fold, ~1.6-fold, and ~1.8-fold higher in N87 tumors. In addition, a prolonged retention of MMAE was observed within the tumors of both the mouse models, suggesting intracellular binding of MMAE to tubulin. A systems PK model, developed by integrating single-cell PK model with tumor distribution model, was able to capture all in vivo PK data reasonably well. Intracellular occupancy of tubulin predicted by the PK model was used to drive the efficacy of ADC using a novel PK-PD model. It was found that the same set of PD parameters was able to capture MMAE induced killing of GFP-MCF7 and N87 cells in vivo. These observations highlight the benefit of adopting a systems approach for ADC and provide a robust and predictive framework for successful clinical translation of ADCs. Full article
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Review

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Open AccessReview
Interpretation of Non-Clinical Data for Prediction of Human Pharmacokinetic Parameters: In Vitro-In Vivo Extrapolation and Allometric Scaling
Pharmaceutics 2019, 11(4), 168; https://doi.org/10.3390/pharmaceutics11040168
Received: 31 January 2019 / Revised: 22 March 2019 / Accepted: 2 April 2019 / Published: 5 April 2019
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Abstract
Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the [...] Read more.
Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the prediction of human PKs prior to the first-in-human clinical trials. In vitro-in vivo extrapolation and allometric scaling are the choice of method for projection to human situations. Although these methods are useful tools for the estimation of PK parameters, it is a challenge to apply these methods since underlying biochemical, mathematical, physiological, and background knowledge of PKs are required. In addition, it is difficult to select an appropriate methodology depending on the data available. Therefore, this review covers the principles of PK parameters pertaining to the clearance, volume of distribution, elimination half-life, absorption rate constant, and prediction method from the original idea to recently developed models in order to introduce optimal models for the prediction of PK parameters. Full article
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Open AccessReview
Mathematical Modeling of Release Kinetics from Supramolecular Drug Delivery Systems
Pharmaceutics 2019, 11(3), 140; https://doi.org/10.3390/pharmaceutics11030140
Received: 31 January 2019 / Revised: 7 March 2019 / Accepted: 18 March 2019 / Published: 21 March 2019
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Abstract
Embedding of active substances in supramolecular systems has as the main goal to ensure the controlled release of the active ingredients. Whatever the final architecture or entrapment mechanism, modeling of release is challenging due to the moving boundary conditions and complex initial conditions. [...] Read more.
Embedding of active substances in supramolecular systems has as the main goal to ensure the controlled release of the active ingredients. Whatever the final architecture or entrapment mechanism, modeling of release is challenging due to the moving boundary conditions and complex initial conditions. Despite huge diversity of formulations, diffusion phenomena are involved in practically all release processes. The approach in this paper starts, therefore, from mathematical methods for solving the diffusion equation in initial and boundary conditions, which are further connected with phenomenological conditions, simplified and idealized in order to lead to problems which can be analytically solved. Consequently, the release models are classified starting from the geometry of diffusion domain, initial conditions, and conditions on frontiers. Taking into account that practically all solutions of the models use the separation of variables method and integral transformation method, two specific applications of these methods are included. This paper suggests that “good modeling practice” of release kinetics consists essentially of identifying the most appropriate mathematical conditions corresponding to implied physicochemical phenomena. However, in most of the cases, models can be written but analytical solutions for these models cannot be obtained. Consequently, empiric models remain the first choice, and they receive an important place in the review. Full article
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Open AccessReview
Pharmacokinetics and Pharmacodynamics Modeling and Simulation Systems to Support the Development and Regulation of Liposomal Drugs
Pharmaceutics 2019, 11(3), 110; https://doi.org/10.3390/pharmaceutics11030110
Received: 30 January 2019 / Revised: 25 February 2019 / Accepted: 28 February 2019 / Published: 7 March 2019
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Abstract
Liposomal formulations have been developed to improve the therapeutic index of encapsulated drugs by altering the balance of on- and off-targeted distribution. The improved therapeutic efficacy of liposomal drugs is primarily attributed to enhanced distribution at the sites of action. The targeted distribution [...] Read more.
Liposomal formulations have been developed to improve the therapeutic index of encapsulated drugs by altering the balance of on- and off-targeted distribution. The improved therapeutic efficacy of liposomal drugs is primarily attributed to enhanced distribution at the sites of action. The targeted distribution of liposomal drugs depends not only on the physicochemical properties of the liposomes, but also on multiple components of the biological system. Pharmacokinetic–pharmacodynamic (PK–PD) modeling has recently emerged as a useful tool with which to assess the impact of formulation- and system-specific factors on the targeted disposition and therapeutic efficacy of liposomal drugs. The use of PK–PD modeling to facilitate the development and regulatory reviews of generic versions of liposomal drugs recently drew the attention of the U.S. Food and Drug Administration. The present review summarizes the physiological factors that affect the targeted delivery of liposomal drugs, challenges that influence the development and regulation of liposomal drugs, and the application of PK–PD modeling and simulation systems to address these challenges. Full article
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