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A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmaceutical Technology, Manufacturing and Devices".

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 42796

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Special Issue Editor

Prof. Dr. Yu Chul Kim

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Guest Editor

Department of Pharmaceutical Engineering, Inje University, Gimhae 50834, Republic of Korea
Interests: pharmacokinetics; drug metabolism; drug–drug interaction; PK/PD; modeling and simulation; PBPK; data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The modeling and simulation (M&S) technology has been verified to be useful in a variety of academic and industrial fields. M&S has also expanded its application into the pharmaceutical industry since it began to be used during drug development and regulatory approval process as a method to overcome the low productivity of new drug development. Currently, the M&S approach is utilized in almost all stages of drug discovery and development and as a regulatory process and has evolved from the concept of “model-based” to “model-informed”. Overall, model-informed decision making is contributing to increasing success rates in drug development.

This Special Issue aims to highlight the latest research activities using M&S from all the stages of drug discovery and development, which include PK/PD modeling, PBPK, pharmacometrics, systems pharmacology, etc. We invite researchers to submit original research articles and reviews in this field.

Prof. Dr. Yu Chul Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceutics is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

Modeling and simulation
PK/PD
PBPK
Pharmacometrics
Systems pharmacology
Drug discovery and development

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Published Papers (10 papers)

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Research

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18 pages, 3144 KiB

Open AccessEditor’s ChoiceArticle

Mechanistically Coupled PK (MCPK) Model to Describe Enzyme Induction and Occupancy Dependent DDI of Dabrafenib Metabolism

by Marco Albrecht, Yuri Kogan, Dagmar Kulms and Thomas Sauter

Pharmaceutics 2022, 14(2), 310; https://doi.org/10.3390/pharmaceutics14020310 - 28 Jan 2022

Cited by 1 | Viewed by 3122

Abstract

Dabrafenib inhibits the cell proliferation of metastatic melanoma with the oncogenic BRAF(V600)-mutation. However, dabrafenib monotherapy is associated with pERK reactivation, drug resistance, and consequential relapse. A clinical drug-dose determination study shows increased pERK levels upon daily administration of more than 300 mg dabrafenib. To clarify whether such elevated drug concentrations could be reached by long-term drug accumulation, we mechanistically coupled the pharmacokinetics (MCPK) of dabrafenib and its metabolites. The MCPK model is qualitatively based on in vitro and quantitatively on clinical data to describe occupancy-dependent CYP3A4 enzyme induction, accumulation, and drug–drug interaction mechanisms. The prediction suggests an eight-fold increase in the steady-state concentration of potent desmethyl-dabrafenib and its inactive precursor carboxy-dabrafenib within four weeks upon 150 mg b.d. dabrafenib. While it is generally assumed that a higher dose is not critical, we found experimentally that a high physiological dabrafenib concentration fails to induce cell death in embedded 451LU melanoma spheroids. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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16 pages, 4469 KiB

Open AccessArticle

A Physiologically Based Pharmacokinetic Model for Predicting Diazepam Pharmacokinetics after Intravenous, Oral, Intranasal, and Rectal Applications

by Sundus Khalid, Muhammad Fawad Rasool, Imran Imran, Abdul Majeed, Hamid Saeed, Anees ur Rehman, Waseem Ashraf, Tanveer Ahmad, Yousef A. Bin Jardan and Faleh Alqahtani

Pharmaceutics 2021, 13(9), 1480; https://doi.org/10.3390/pharmaceutics13091480 - 15 Sep 2021

Cited by 11 | Viewed by 9592

Abstract

Diazepam is one of the most prescribed anxiolytic and anticonvulsant that is administered through intravenous (IV), oral, intramuscular, intranasal, and rectal routes. To facilitate the clinical use of diazepam, there is a need to develop formulations that are convenient to administer in ambulatory settings. The present study aimed to develop and evaluate a physiologically based pharmacokinetic (PBPK) model for diazepam that is capable of predicting its pharmacokinetics (PK) after IV, oral, intranasal, and rectal applications using a whole-body population-based PBPK simulator, Simcyp^®. The model evaluation was carried out using visual predictive checks, observed/predicted ratios (R_obs/pred), and the average fold error (AFE) of PK parameters. The Diazepam PBPK model successfully predicted diazepam PK in an adult population after doses were administered through IV, oral, intranasal, and rectal routes, as the R_obs/pred of all PK parameters were within a two-fold error range. The developed model can be used for the development and optimization of novel diazepam dosage forms, and it can be extended to simulate drug response in situations where no clinical data are available (healthy and disease). Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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16 pages, 738 KiB

Open AccessArticle

Mathematical Modeling of Remdesivir to Treat COVID-19: Can Dosing Be Optimized?

by Jessica M. Conway and Pia Abel zur Wiesch

Pharmaceutics 2021, 13(8), 1181; https://doi.org/10.3390/pharmaceutics13081181 - 31 Jul 2021

Cited by 4 | Viewed by 2729

Abstract

The antiviral remdesivir has been approved by regulatory bodies such as the European Medicines Agency (EMA) and the US Food and Drug administration (FDA) for the treatment of COVID-19. However, its efficacy is debated and toxicity concerns might limit the therapeutic range of this drug. Computational models that aid in balancing efficacy and toxicity would be of great help. Parametrizing models is difficult because the prodrug remdesivir is metabolized to its active form (RDV-TP) upon cell entry, which complicates dose–activity relationships. Here, we employ a computational model that allows drug efficacy predictions based on the binding affinity of RDV-TP for its target polymerase in SARS-CoV-2. We identify an optimal infusion rate to maximize remdesivir efficacy. We also assess drug efficacy in suppressing both wild-type and resistant strains, and thereby describe a drug regimen that may select for resistance. Our results differ from predictions using prodrug dose–response curves (pseudo-EC

_{50}

s). We expect that reaching 90% inhibition (EC

_{90}

) is insufficient to suppress SARS-CoV-2 in the lungs. While standard dosing mildly inhibits viral polymerase and therefore likely reduces morbidity, we also expect selection for resistant mutants for most realistic parameter ranges. To increase efficacy and safeguard against resistance, we recommend more clinical trials with dosing regimens that substantially increase the levels of RDV-TP and/or pair remdesivir with companion antivirals. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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23 pages, 4580 KiB

Open AccessArticle

PK/PD Modeling of the PDE7 Inhibitor—GRMS-55 in a Mouse Model of Autoimmune Hepatitis

by Artur Świerczek, Hanna Plutecka, Marietta Ślusarczyk, Grażyna Chłoń-Rzepa and Elżbieta Wyska

Pharmaceutics 2021, 13(5), 597; https://doi.org/10.3390/pharmaceutics13050597 - 21 Apr 2021

Cited by 4 | Viewed by 2824

Abstract

This study aimed to assess the efficacy and explore the mechanisms of action of a potent phosphodiesterase (PDE)7A and a moderate PDE4B inhibitor GRMS-55 in a mouse model of autoimmune hepatitis (AIH). The concentrations of GRMS-55 and relevant biomarkers were measured in the serum of BALB/c mice with concanavalin A (ConA)-induced hepatitis administered with GRMS-55 at two dose levels. A semi-mechanistic PK/PD/disease progression model describing the time courses of measured biomarkers was developed. The emetogenicity as a potential side effect of the studied compound was evaluated in the α₂-adrenoceptor agonist-induced anesthesia model. The results indicate that liver damage observed in mice challenged with ConA was mainly mediated by TNF-α and IFN-γ. GRMS-55 decreased the levels of pro-inflammatory mediators and the transaminase activities in the serum of mice with AIH. The anti-inflammatory properties of GRMS-55, resulting mainly from PDE7A inhibition, led to a high hepatoprotective activity in mice with AIH, which was mediated by an inhibition of pro-inflammatory signaling. GRMS-55 did not induce the emetic-like behavior. The developed PK/PD/disease progression model may be used in future studies to assess the potency and explore the mechanisms of action of new investigational compounds for the treatment of AIH. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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14 pages, 6174 KiB

Open AccessArticle

Accelerating Development of Benziamidazole-Class Proton Pump Inhibitors: A Mechanism-Based PK/PD Model to Optimize Study Design with Ilaprazole as a Case Drug

by Ranran Jia, Fan Zhang, Ni Wu, Wen Xu, Huitao Gao, Bo Liu and Hongyun Wang

Pharmaceutics 2021, 13(3), 392; https://doi.org/10.3390/pharmaceutics13030392 - 15 Mar 2021

Cited by 3 | Viewed by 3129

Abstract

Proton pump inhibitors (PPIs) are the mainstay for treatment of acid-related diseases. This study developed a mechanism-based pharmacokinetic (PK) and pharmacodynamics (PD) model with ilaprazole as case drug, so as to support and accelerate the development of novel PPIs. The model was established and verified using the PK and PD data from 26 subjects receiving 5 to 30 mg of ilaprazole and 22 subjects receiving the loading dose of ilaprazole 20 mg followed by 10 mg once daily for 2 days. The nonlinear mixed-effects modeling approach was performed for the PK/PD model. A two-compartment model with linear elimination and covariates (body weight and gender) described the observed data well. The relationship between plasma concentrations of ilaprazole and gastric acid pH was well quantified with individual variability, in which the synthesis and degradation of H⁺/K⁺-ATPase, the food effect, the circular rhythms of gastric acid secretion, and the irreversible inhibition of H⁺/K⁺-ATPase by ilaprazole were integrated. This PK/PD model well predicted the PK and PD profile of ilaprazole in healthy subjects and patients with duodenal ulcers receiving wide range dose regimens. The mechanism-based PK/PD model provided a potential strategy to accelerate the development of novel PPIs by waiving the unnecessary clinical trials. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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14 pages, 1462 KiB

Open AccessArticle

Pharmacokinetic Characterization of Supinoxin and Its Physiologically Based Pharmacokinetic Modeling in Rats

by Yoo-Kyung Song, Yun-Hwan Seol, Min Ju Kim, Jong-Woo Jeong, Hae-In Choi, Seung-Won Lee, Yoon-Jee Chae, Sunjoo Ahn, Young-Dae Gong, Kyeong-Ryoon Lee and Tae-Sung Koo

Pharmaceutics 2021, 13(3), 373; https://doi.org/10.3390/pharmaceutics13030373 - 11 Mar 2021

Cited by 2 | Viewed by 2650

Abstract

Supinoxin is a novel anticancer drug candidate targeting the Y593 phospho-p68 RNA helicase, by exhibiting antiproliferative activity and/or suppression of tumor growth. This study aimed to characterize the in vitro and in vivo pharmacokinetics of supinoxin and attempt physiologically based pharmacokinetic (PBPK) modeling in rats. Supinoxin has good permeability, comparable to that of metoprolol (high permeability compound) in Caco-2 cells, with negligible net absorptive or secretory transport observed. After an intravenous injection at a dose range of 0.5–5 mg/kg, the terminal half-life (i.e., 2.54–2.80 h), systemic clearance (i.e., 691–865 mL/h/kg), and steady state volume of distribution (i.e., 2040–3500 mL/kg) of supinoxin remained unchanged, suggesting dose-independent (i.e., dose-proportional) pharmacokinetics for the dose ranges studied. After oral administration, supinoxin showed modest absorption with an absolute oral bioavailability of 56.9–57.4%. The fecal recovery following intravenous and oral administration was 16.5% and 46.8%, respectively, whereas the urinary recoveries in both administration routes were negligible. Supinoxin was mainly eliminated via NADPH-dependent phase I metabolism (i.e., 58.5% of total clearance), while UDPGA-dependent phase II metabolism appeared negligible in the rat liver microsome. Supinoxin was most abundantly distributed in the adipose tissue, gut, and liver among the nine major tissues studied (i.e., the brain, liver, kidneys, heart, lungs, spleen, gut, muscles, and adipose tissue), and the tissue exposure profiles of supinoxin were well predicted with physiologically based pharmacokinetics. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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18 pages, 2328 KiB

Open AccessArticle

Pharmacokinetic Estimation Models-based Approach to Predict Clinical Implications for CYP Induction by Calcitriol in Human Cryopreserved Hepatocytes and HepaRG Cells

by Yoon-Jee Chae, Min-Soo Kim, Suk-Jae Chung, Mi-Kyung Lee, Kyeong-Ryoon Lee and Han-Joo Maeng

Pharmaceutics 2021, 13(2), 181; https://doi.org/10.3390/pharmaceutics13020181 - 29 Jan 2021

Cited by 5 | Viewed by 2890

Abstract

Calcitriol, a vitamin D₃ metabolite, is approved for various indications because it is the bioactive form of vitamin D in the body. The purpose of this study was to predict the clinical significance of cytochrome P450 (CYP) induction by calcitriol using in vitro human cryopreserved hepatocytes, HepaRG experimental systems, and various pharmacokinetic estimation models. CYP2B6, 3A4, 2C8, and 2C9 mRNA levels increased in a concentration-dependent manner in the presence of calcitriol in human cryopreserved hepatocytes and HepaRG cells. Using the half maximal effective concentration (EC₅₀) and maximum induction effect (E_max) obtained from the in vitro study, a basic kinetic model was applied, suggesting clinical relevance. In addition, a static mechanistic model showed the improbability of a clinically significant effect; however, the calculated area under the plasma concentration–time curve ratio (AUCR) was marginal for CYP3A4 in HepaRG cells. To clarify the effect of CYP3A4 in vivo, physiologically based pharmacokinetic (PBPK) modeling was applied as a dynamic mechanistic model, revealing a low clinically significant effect of CYP3A4 induction by calcitriol. Therefore, we conclude that CYP induction by calcitriol treatment would not be clinically significant under typical clinical conditions. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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12 pages, 2057 KiB

Open AccessArticle

Model-Based Prediction to Evaluate Residence Time of Hyaluronic Acid Based Dermal Fillers

by Hyo-jeong Ryu, Seong-sung Kwak, Chang-hoon Rhee, Gi-hyeok Yang, Hwi-yeol Yun and Won-ho Kang

Pharmaceutics 2021, 13(2), 133; https://doi.org/10.3390/pharmaceutics13020133 - 21 Jan 2021

Cited by 8 | Viewed by 5046

Abstract

Dermal fillers are gel-type substances for nonsurgical medical-device use to achieve facial rejuvenation. Currently, the most widely used skin fillers are hyaluronic-acid-based dermal fillers. This study aimed to explain the change in the volume of injected dermal fillers by developing a mathematical kinetic model for various dermal fillers. The kinetics of the injected fillers were separated by a biphasic phenomenon. We attributed an increase in filler volume to the hydration of hyaluronic acid molecules and injection-site reaction and a decrease in volume to enzyme-mediated degradation. To explain these in vivo characteristics of dermal fillers, we proposed a two-compartment model, divided into a depot compartment (where the filler was injected) and a subcutaneous compartment (an observation compartment where the fillers swell and degrade), assuming that the swelling and degradation occurred in accordance with the swelling and degradation rate constants, respectively. The model was developed using five hyaluronic-acid-based dermal fillers and NONMEM. We determined that the rate-limiting step for the complete degradation of the dermal fillers in vivo was the swelling phase, as described by the swelling rate constant (K_swell). This study could enable scientists developing novel dermal fillers to predict the in vivo behavior of fillers. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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Review

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68 pages, 9584 KiB

Open AccessReview

Assessing Drug-Induced Mitochondrial Toxicity in Cardiomyocytes: Implications for Preclinical Cardiac Safety Evaluation

by Xiaoli Tang, Zengwu Wang, Shengshou Hu and Bingying Zhou

Pharmaceutics 2022, 14(7), 1313; https://doi.org/10.3390/pharmaceutics14071313 - 21 Jun 2022

Cited by 17 | Viewed by 5054

Abstract

Drug-induced cardiotoxicity not only leads to the attrition of drugs during development, but also contributes to the high morbidity and mortality rates of cardiovascular diseases. Comprehensive testing for proarrhythmic risks of drugs has been applied in preclinical cardiac safety assessment for over 15 years. However, other mechanisms of cardiac toxicity have not received such attention. Of them, mitochondrial impairment is a common form of cardiotoxicity and is known to account for over half of cardiovascular adverse-event-related black box warnings imposed by the U.S. Food and Drug Administration. Although it has been studied in great depth, mitochondrial toxicity assessment has not yet been incorporated into routine safety tests for cardiotoxicity at the preclinical stage. This review discusses the main characteristics of mitochondria in cardiomyocytes, drug-induced mitochondrial toxicities, and high-throughput screening strategies for cardiomyocytes, as well as their proposed integration into preclinical safety pharmacology. We emphasize the advantages of using adult human primary cardiomyocytes for the evaluation of mitochondrial morphology and function, and the need for a novel cardiac safety testing platform integrating mitochondrial toxicity and proarrhythmic risk assessments in cardiac safety evaluation. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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22 pages, 1370 KiB

Open AccessReview

The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development

by Zhengying Zhou, Jinwei Zhu, Muhan Jiang, Lan Sang, Kun Hao and Hua He

Pharmaceutics 2021, 13(5), 704; https://doi.org/10.3390/pharmaceutics13050704 - 12 May 2021

Cited by 12 | Viewed by 3686

Abstract

Human-derived in vitro models can provide high-throughput efficacy and toxicity data without a species gap in drug development. Challenges are still encountered regarding the full utilisation of massive data in clinical settings. The lack of translated methods hinders the reliable prediction of clinical outcomes. Therefore, in this study, in silico models were proposed to tackle these obstacles from in vitro to in vivo translation, and the current major cell culture methods were introduced, such as human-induced pluripotent stem cells (hiPSCs), 3D cells, organoids, and microphysiological systems (MPS). Furthermore, the role and applications of several in silico models were summarised, including the physiologically based pharmacokinetic model (PBPK), pharmacokinetic/pharmacodynamic model (PK/PD), quantitative systems pharmacology model (QSP), and virtual clinical trials. These credible translation cases will provide templates for subsequent in vitro to in vivo translation. We believe that synergising high-quality in vitro data with existing models can better guide drug development and clinical use. Full article

(This article belongs to the Special Issue Model-Informed Drug Discovery and Development)

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