In the published version of this article, the contents of Table 1 (‘Demographic characteristics of subjects’) are incorrect.

As the pharmaceutical industry in Korea is reaching the golden era of drug discovery due to increased investments in research and development and government funds, the need for a more efficient tool for the quantitative analysis has emerged. Therefore, the demand for pharmacometrics (PMx) consultancy services increased. Higher quality service suitable for regulatory submission and out-licensing deals were desired. In this analysis, we compiled and summarized 3 years of experiences of Q-fitter, the first PMx consultancy service company providing PMx analysis to the pharmaceutical industry in Korea. The projects were organized by companies, company types, indications, therapeutic areas, drug development stages, purposes, and scope of services. Within each category, we subcategorized the sections and assessed proportions and a year-over-year trend. As a result, we observed an increase in the number of projects in an average of ~170% per year, with the most frequent types of companies collaborated being the domestic pharmaceutical companies. Among the projects, ~72% involved modeling and simulation using population pharmacokinetic (PK) models, and the other included non-compartmental analysis (NCA), drug-drug interaction (DDI) prediction, and interpretation of the modeling results. The most sought-after purpose in PMx analysis was first-in-human (FIH) dose prediction followed by PK analysis, next clinical trial prediction, and scenario-based simulation. Oncology has been the top therapeutic area of interest every year consisting of ~38% of total projects, followed by Neurology (~13%). From this review, we were able to characterize the PMx service needs and spot the trend of current PMx practices in Korea.
Drug Discovery ; Drug Industry ; Financial Management ; Investments ; Korea ; Neurology

The importance of precise information and knowledge on the initial estimates (IEs) in modeling has not been paid its due attention so far. By focusing on the IE, this tutorial may serve as a practical guide for beginners in pharmacometrics. A 'good' set of IEs rather than arbitrary values is required because the IEs where NONMEM kicks off its estimation may influence the subsequent objective function minimization. To provide NONMEM with acceptable IEs, modelers should understand the exact meaning of THETA, OMEGA and SIGMA based on physiology. In practice, problems related to the value of the IE are more likely to occur for THETAs rather than the random-effect terms. Because it is almost impossible for a modeler to give a precise IE for OMEGAs at the beginning, it may be a good practice to start at relatively small IEs for them. NONMEM may fail to converge when too small IEs are provided for residual error parameters; thus, it is recommended to give sufficiently large values for them. The understandings on the roles, meanings and implications of IEs even help modelers in troubleshooting situations which frequently occur over the whole modeling process.
Physiology

BACKGROUND: Levodropropizine is non-opioid agent whose peripheral antitussive action may result from its modulation of sensory neuropeptide levels. Currently, levodropropizine 60 mg is taken three-times daily. A controlled release formulation of levodropropizine (levodropropizine CR) 90 mg was developed, which can be taken twice daily. The aim of this study was to evaluate the safety and pharmacokinetic characteristics after multiple oral administrations of levodropropizine CR 90 mg tablets in healthy male volunteers. METHODS: A randomized, open-label, cross-over study was conducted in 24 healthy male volunteers. Each subject received levodropropizine syrup 60 mg three times daily or levodropropizine CR 90 mg twice daily for 3 days. Blood samples for pharmacokinetic analysis were collected pre-dose and up to 24 hours on day 4. Pharmacokinetic analysis was conducted by non-compartmental method. Safety assessments including monitoring adverse events, laboratory tests, vital signs, physical examinations and ECGs were performed throughout the study. RESULTS: A total of 20 male volunteers completed the study. The maximum steady-state plasma concentration (Css,max) of levodropropizine syrup and levodropropizine CR were 313.28 ng/mL and 285.31 ng/mL and time to reach Css,max (Tmax,ss) were 0.48 hr and 0.88 hr, respectively. The area under the concentration-time curve to the last measured concentration of two groups were 2345.36 hr x ng/mL and 2553.81 hr x ng/mL, respectively. There was no serious adverse event. CONCLUSION: Levodropropizine CR 90 mg tablet was safe and well-tolerated when administered twice daily for 3 days. No statistically significant differences were seen in Css,max and AUCss,24hr between the two formulations. This study provided pharmacokinetic evidences that the twice-daily dosing regimen of levodropropizine 90 mg may substitute the conventional 3-times-daily regimen of levodropropizine 60 mg.
Administration, Oral ; Cross-Over Studies ; Electrocardiography ; Humans ; Male* ; Methods ; Neuropeptides ; Pharmacokinetics* ; Physical Examination ; Plasma ; Tablets ; Vital Signs

PURPOSE: A phase I clinical trial was conducted to evaluate the immunogenicity and safety of newly developed egg-cultivated trivalent inactivated split influenza vaccine (TIV) in Korea. MATERIALS AND METHODS: The TIV was administered to 43 healthy male adults. Subjects with high pre-existing titers were excluded in a screening step. Immune response was measured by a hemagglutination inhibition (HI) assay. RESULTS: The seroprotection rates against A/California/7/2009 (H1N1), A/Perth/16/2009 (H3N2) and B/Brisbane/60/2009 were 74.42% [95% confidence interval (CI): 61.38–87.46], 72.09% (95% CI: 58.69–85.50), and 86.05% (95% CI: 75.69–96.40), respectively. Calculated seroconversion rates were 74.42% (95% CI: 61.38–87.46), 74.42% (95% CI: 61.38–87.46), and 79.07% (95% CI: 66.91–91.23), respectively. There were 25 episodes of solicited local adverse events in 21 subjects (47.73%), 21 episodes of solicited general adverse events in 16 subjects (36.36%) and 5 episodes of unsolicited adverse events in 5 subjects (11.36%). All adverse events were grade 1 or 2 and disappeared within three days. CONCLUSION: The immunogenicity and safety of TIV established in this phase I trial are sufficient to plan a larger scale clinical trial.
Adult* ; Hemagglutination ; Humans ; Influenza Vaccines* ; Influenza, Human* ; Korea ; Male ; Mass Screening ; Seroconversion

Fixed-dose combinations development requires pharmacokinetic drugdrug interaction (DDI) studies between active ingredients. For some drugs, pharmacokinetic properties such as long half-life or delayed distribution, make it difficult to conduct such clinical trials and to estimate the exact magnitude of DDI. In this study, the conventional (non-compartmental analysis and bioequivalence [BE]) and modelbased analyses were compared for their performance to evaluate DDI using amlodipine as an example. Raw data without DDI or simulated data using pharmacokinetic models were compared to the data obtained after concomitant administration.Regardless of the methodology, all the results fell within the classical BE limit. It was shown that the model-based approach may be valid as the conventional approach and reduce the possibility of DDI overestimation. Several advantages (i.e., quantitative changes in parameters and precision of confidence interval) of the model-based approach were demonstrated, and possible application methods were proposed. Therefore, it is expected that the model-based analysis is appropriately utilized according to the situation and purpose.

Metformin, an oral antihyperglycemic agent, is widely used as the first-line pharmacotherapy for type 2 diabetes mellitus (T2DM). It has been in use for several decades as numerous different formulations. However, despite its use, population pharmacokinetic (PK) modeling of metformin is not well developed. The aim of the present study was to evaluate the effect of formulation on PK parameters by developing a population PK model of metformin in Koreans and using this model to assess bioequivalence. We used a comparative PK study of a single agent and a fixed-dose combination of metformin in 36 healthy volunteers. The population PK model of metformin was developed using NONMEM (version 7.3). Visual predictive checks and bootstrap methods were performed to determine the adequacy of the model. The plasma concentration-time profile was best described by a two-compartment, first-order elimination model with first-order absorption followed by zeroorder absorption with lag time. From the covariate analysis, formulation had significant effect (p < 0.01) on relative bioavailability (F = 0.94) and first-order absorption constant (Ka = 0.83), but the difference was within the range of bioequivalence criteria. No other covariate was shown to have significant effect on PK parameters. The PK profile of the disposition phase was consistent with the published literature. However, in the present study, the multiple peaks found during the absorption phase implied the possible diversity of absorption PK profile depending on formulation or population. Unlike traditional bioequivalence analysis, the population PK model reflects formulation differences on specific parameters and reflected simulation can be performed.
Absorption ; Adult ; Biological Availability ; Diabetes Mellitus, Type 2 ; Drug Therapy ; Healthy Volunteers ; Humans ; Metformin ; Pharmacokinetics ; Plasma ; Therapeutic Equivalency

Plasma ionized calcium (Ca2+) concentrations are tightly regulated in the body and maintained within a narrow range; thus it is challenging to quantify calcium absorption under normal physiologic conditions. This study aimed to develop a mechanistic model for the parathyroid hormone (PTH) response after calcium intake and indirectly compare the difference in oral calcium absorption from PTH responses. PTH and Ca2+ concentrations were collected from 24 subjects from a clinical trial performed to evaluate the safety and calcium absorption of Geumjin Thermal Water in comparison with calcium carbonate tablets in healthy subjects. Indirect response models (NONMEM Ver. 7.2.0) were fitted to observed Ca2+ and PTH data, respectively, in a manner that absorbed but unobserved Ca2+ inhibits the secretion of PTH. Without notable changes in Ca2+ levels, PTH responses were modeled and used as a marker for the extent of calcium absorption.
Absorption ; Calcium Carbonate ; Calcium* ; Parathyroid Hormone* ; Plasma ; Tablets ; Water

The coronavirus disease 2019 pandemic has exacerbated global mental health challenges, underscoring the urgent need for advancements in digital healthcare technologies. Digital therapeutics have demonstrated clinical utility across various domains; however, their development and implementation in the mental health remain constrained within the traditional clinical paradigm. This study conceptualizes and classifies digital interventions for mental health (DIMH), delineates their core technologies, and discusses their strengths and limitations.Current Concepts: DIMH interventions predominantly utilize cognitive behavioral therapy frameworks, targeting conditions such as anxiety, depression, and psychological distress. Despite their potential, low user engagement remains a persistent challenge, necessitating personalized approaches tailored to individual needs. Platforms bridge users and therapists, facilitating hybrid online-offline care; however, service delivery may falter due to shortages in provider availability. Emerging social chatbots, while not specifically designed for treatment, show promising outcomes but are limited by insufficient consideration of social contexts and potential interactional errors. Digital phenotyping, which leverages behavioral data such as location tracking and smartphone usage patterns, enhances the personalization of interventions by embedding social context. Additionally, virtual reality (VR) offers effective solutions for exposure therapy and social interaction training, serving as a viable alternative to traditional therapy.Discussion and Conclusion: This review underscores the complementary nature of DIMH technologies and advocates for an integrated approach. The convergence of group-based interventions, chatbots, digital phenotyping, and VR technology presents opportunities for more effective and personalized mental health care. Such advancements could redefine mental health services, addressing unmet needs and fostering innovation.

The coronavirus disease 2019 pandemic has exacerbated global mental health challenges, underscoring the urgent need for advancements in digital healthcare technologies. Digital therapeutics have demonstrated clinical utility across various domains; however, their development and implementation in the mental health remain constrained within the traditional clinical paradigm. This study conceptualizes and classifies digital interventions for mental health (DIMH), delineates their core technologies, and discusses their strengths and limitations.Current Concepts: DIMH interventions predominantly utilize cognitive behavioral therapy frameworks, targeting conditions such as anxiety, depression, and psychological distress. Despite their potential, low user engagement remains a persistent challenge, necessitating personalized approaches tailored to individual needs. Platforms bridge users and therapists, facilitating hybrid online-offline care; however, service delivery may falter due to shortages in provider availability. Emerging social chatbots, while not specifically designed for treatment, show promising outcomes but are limited by insufficient consideration of social contexts and potential interactional errors. Digital phenotyping, which leverages behavioral data such as location tracking and smartphone usage patterns, enhances the personalization of interventions by embedding social context. Additionally, virtual reality (VR) offers effective solutions for exposure therapy and social interaction training, serving as a viable alternative to traditional therapy.Discussion and Conclusion: This review underscores the complementary nature of DIMH technologies and advocates for an integrated approach. The convergence of group-based interventions, chatbots, digital phenotyping, and VR technology presents opportunities for more effective and personalized mental health care. Such advancements could redefine mental health services, addressing unmet needs and fostering innovation.