Quantitative risk factor analysis of prior disease condition and socioeconomic status with the multiple myeloma development: nationwide cohort study.

Early diagnosis and following management are important determinants of the prognosis of multiple myeloma (MM). However, screening for MM is not routinely performed because it is rare disease. In this study, we evaluated the association of prior disease condition and socioeconomic status (SES) with MM diagnosis and developed a simple predictive model that can identify patients at high risk of developing MM who may need screening using nationwide database from South Korea. According to multivariate logistic regression analysis, eight prior disease conditions and SES before diagnosis were shown to be predictors of MM development and selected for score development. Total prediction scores were categorized into four groups: patients without any risk (≤ 0) intermediate-1 (0.5-9), intermediate-2 (9-14), and high risk (> 14). The odds ratios for developing MM in the intermediate-1, intermediate-2, and high-risk groups were 1.29, 3.07, and 4.62, respectively. The association of prior disease conditions and SES with MM diagnosis were demonstrated and the simple scoring system to predict the MM risk was developed. This scoring system is also provided by web-based application and could be a useful tool to support clinicians in identifying potential candidates for MM screening.

A multicenter, retrospective comparison of pregnancy outcomes between groups of preterm labor nulliparous mothers treated with atosiban vs. ritodrine in singleton and multiple pregnancies.

OBJECTIVE: To evaluate the safety and efficacy of atosiban and ritodrine in pregnant women who were hospitalized for threatened preterm labor (TPL). MATERIALS AND METHODS: Diagnosis records of preterm labor and subsequent pregnancy-related records and medical records of newborns were extracted from the Clinical Data Warehouse of the Catholic Medical Center's affiliated hospital. Since 2009, cases of preterm labor diagnosed before 34 weeks of pregnancy for first-time mothers who delivered at any one of three hospitals and who received drug treatment for more than 2 days to delay delivery were included in the dataset. Based on characteristics of Korea's national health insurance system, the drug treatment after diagnosis of preterm labor could be classified into cases using only ritodrine (571 women), cases using only atosiban (244 women), and cases where ritodrine treatment was started and then changed to atosiban (275 women). Demographic factors, obstetric outcomes, neonatal outcomes of the two groups were analyzed. RESULTS: The duration and maintenance of pregnancy were found to be similar between the two groups, although the initial cervical length was significantly shorter in the atosiban cohort (AC). Only in multifetal pregnancies, the maintenance of pregnancy was significantly longer in the AC. The total duration of pregnancy did not show any significant difference between the two groups regardless of singleton or multiple pregnancy. However, the distribution graph showed non-responders in the ritodrine cohort (RC). Our study showed a difference in neonatal birth weight of singleton between the two groups. The length of hospitalization and the NICU admission rate were also significantly higher in the RC for singleton. Although not significant, the proportion of numbers with an Apgar score less than 7 was higher in the RC. Neonatal death was more common in the RG (8 cases in AC and 18 cases in RC). CONCLUSIONS: Using atosiban for TPL is more effective than using ritodrine for maintaining pregnancy in the case of a multifetal pregnancy. In singleton pregnancies, neonatal outcomes of the atosiban group were superior to those of the ritodrine group. There seems to be a non-responder group when using ritodrine for TPL. Further studies are needed to determine causes of non-responders of ritodrine and effects of ritodrine on the fetus.

Establishing Rationale for the Clinical Development of Cell Therapy Products: Consensus between Risk and Benefit.

Despite long-term research achievements, the development of cell therapy (CT) products remains challenging. This is because the risks experienced by the subject and therapeutic effects in the clinical trial stage are unclear due to the various uncertainties of CT when administered to humans. Nevertheless, as autologous cell products for systemic administration have recently been approved for marketing, CT product development is accelerating, particularly in the field of unmet medical needs. The human experience of CT remains insufficient compared with other classes of pharmaceuticals, while there are countless products for clinical development. Therefore, for many sponsors, understanding the rationale of human application of an investigational product based on the consensus and improving the ability to apply it appropriately for CT are necessary. Thus, defining the level of evidence for safety and efficacy fundamentally required for initiating the clinical development and preparing it using a reliable method for CT. Furthermore, the expertise should be strengthened in the design of the first-in-human trial, such as the starting dose and dose-escalation plan, based on a sufficiently acceptable rationale. Cultivating development professionals with these skills will increase the opportunity for more candidates to enter the clinical development phase.

Pharmacokinetic properties of a new sustained-release pregabalin tablet in subjects with reduced renal function.

A new sustained-release (SR) pregabalin tablet, YHD1119, was formulated for once-daily dosing. In the current study, we aimed to evaluate the pharmacokinetics of YHD1119 tablets in patients with reduced renal function. Subjects were grouped by creatinine clearance: > 60 mL/min/1.73m2 (Cohort A) and 30-60 mL/min/1.73m2 (Cohort B). Eight subjects in Cohort A received a YHD1119 75 mg tablet (Y75T) and a YHD1119 150 mg tablet (Y150T) in each period, and eight subjects in Cohort B received a Y75T. Non-compartment analysis and population pharmacokinetic analysis using a one-compartment model with first-order elimination and first-order absorption with lag time were performed. Sixteen subjects completed the study. The geometric mean ratio (GMR) (90% confidence intervals [CI]) for maximum concentration (Cmax), and area under the concentration-time profile from 0 to the last measurable time (AUClast) after Y75T of Cohort B to those of Y75T of Cohort A were 1.2273 (1.0245-1.4701), and 2.4146 (1.8142-3.2138), respectively. The GMR (90% CI) for Cmax, and AUClast after Y75T of Cohort B to those of Y150T of Cohort A were 0.6476 (0.5229-0.8021), and 1.1471 (0.8418-1.5632), respectively. Simulated steady-steady pregabalin concentrations after once-daily Y75T dosing in subjects with eGFR 45 mL/min/1.73 m2 were within the range of steady-state concentrations simulated after once-daily Y150T dosing in subjects with eGFR 90 mL/min/1.73 m2. The total pregabalin exposure of Y75T in patients with moderate renal impairment was comparable with that of Y150T in subjects with near-normal renal function. Trial Registration: ClinicalTrials.gov Identifier: NCT05012436.

Pharmacokinetic Model Based on Stochastic Simulation and Estimation for Therapeutic Drug Monitoring of Tacrolimus in Korean Adult Transplant Recipients.

BACKGROUND: Tacrolimus shows high variability in inter- and intraindividual pharmacokinetics (PK); therefore, it is important to develop an appropriate model for accurate therapeutic drug monitoring (TDM) procedures. This study aimed to develop a pharmacokinetic model for tacrolimus that can be used for TDM procedures in Korean adult transplant recipients by integrating published models with acquired real-world TDM data and evaluating clinically meaningful covariates. METHODS: Clinical data of 1829 trough blood samples from 269 subjects were merged with simulated data sets from published models and analyzed using a nonlinear mixed-effect model. The stochastic simulation and estimation (SSE) method was used to obtain the final parameter estimates. RESULTS: The final estimated values for apparent clearance, the volume of distribution, and absorption rate were 21.2 L/h, 510 L, and 3.1/h, respectively. The number of postoperative days, age, body weight, and type of transplant organs were the major clinical factors affecting tacrolimus PK. CONCLUSIONS: A tacrolimus PK model that can incorporate published PK models and newly collected data from the Korean population was developed using the SSE method. Despite the limitations in model development owing to the nature of TDM data, the SSE method was useful in retrieving complete information from the TDM data by integrating published PK models while maintaining the variability of the model.

Urinary Profile of Endogenous Gamma-Hydroxybutyric Acid and its Biomarker Metabolites in Healthy Korean Females: Determination of Age-Dependent and Intra-Individual Variability and Identification of Metabolites Correlated With Gamma-Hydroxybutyric Acid.

Gamma-hydroxybutyric acid (GHB), used as a therapeutic and an illegal anesthetic, is a human neurotransmitter produced during gamma-aminobutyric acid (GABA) biosynthesis and metabolism. Potential biomarker metabolites of GHB intoxication have been identified previously; however, reference concentrations have not been set due to the lack of clinical study data. Urinary profiling of endogenous GHB and its biomarker metabolites in urine samples (n = 472) of 206 healthy females was performed based on differences in age and time of sample collection using liquid chromatography-tandem mass spectrometry following validation studies. The unadjusted and creatinine-adjusted urinary concentrations ranges were obtained after urinary profiling. The creatinine-adjusted concentrations of glutamic and succinic acids and succinylcarnitine significantly increased, whereas that of glycolic acid significantly decreased with advancing age. Significant inter-day variation of GABA concentration and intra-day variation of 3,4-dihydroxybutyric acid and succinylcarnitine concentrations were observed. The urinary concentrations of 2,4-dihydroxybutyric acid, succinic acid, and 3,4-dihydroxybutyric acid showed the highest correlation with that of GHB. Data from this study suggest population reference limits to facilitate clinical and forensic decisions related to GHB intoxication and could be useful for identification of biomarkers following comparison with urinary profiles of GHB-administered populations.

Prediction of metabolizing enzyme-mediated clinical drug interactions using in vitro information.

Evaluation of drug interactions is an essential step in the new drug development process. Regulatory agencies, including U.S. Food and Drug Administrations and European Medicines Agency, have been published documents containing guidelines to evaluate potential drug interactions. Here, we have streamlined in vitro experiments to assess metabolizing enzyme-mediated drug interactions and provided an overview of the overall process to evaluate potential clinical drug interactions using in vitro data. An experimental approach is presented when an investigational drug (ID) is either a victim or a perpetrator, respectively, and the general procedure to obtain in vitro drug interaction parameters is also described. With the in vitro inhibitory and/or inductive parameters of the ID, basic, static, and/or dynamic models were used to evaluate potential clinical drug interactions. In addition to basic and static models which assume the most conservative conditions, such as the concentration of perpetrators as Cmax, dynamic models including physiologically-based pharmacokinetic models take into account changes in in vivo concentrations and metabolizing enzyme levels over time.

DallphinAtoM: Physiologically based pharmacokinetics software predicting human PK parameters based on physicochemical properties, in vitro and animal in vivo data.

BACKGROUND AND OBJECTIVES: In silico experiments and simulations using physiologically based pharmacokinetic (PBPK) and allometric approaches have played an important role in pharmaceutical research and drug development. These methods integrate diverse data from preclinical and clinical development, and have been widely applied to in vitro-in vivo extrapolation (IVIVE) of absorption, distribution, metabolism, and excretion (ADME). METHODS: To develop a user-friendly open tool predicting human PK, we assessed various references on PBPK and allometric methods published so far. They were integrated into a software system named "DallphinAtoM" (Drugs with ALLometry and PHysiology Inside-Animal to huMan), which has a user-friendly platform that can handle complex PBPK models and allometric models with a relatively small amount of essential information of the drug. The models of DallphinAtoM support the integration of data gained during the nonclinical development phase, enable translation from animal to human, and allow the prediction of concentration-time profiles with predicted PK parameters. RESULTS: We presented two illustrative applications using DallphinAtoM: (1) human PK simulation of an orally administered drug using PBPK method; and (2) simulation of intravenous infusion following a two-compartment model using the allometric scaling method. CONCLUSIONS: We conclude that this is a straightforward and transparent tool allowing fast and reliable human PK simulation based on the latest knowledge on biochemical processes and physiology and provides valuable information for decision making during the early-phase drug development.

An experience on the model-based evaluation of pharmacokinetic drug-drug interaction for a long half-life drug.

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.

Predicting human pharmacokinetics from preclinical data: clearance.

We have streamlined known in vitro methods used to predict the clearance (CL) of small molecules in humans in this tutorial. There have been many publications on in vitro methods that are used at different steps of human CL prediction. The steps from initial intrinsic CL measurement in vitro to the final application of the well-stirred model to obtain predicted hepatic CL (CLH) are somewhat complicated. Except for the experts on drug metabolism and PBPK, many drug development scientists found it hard to figure out the entire picture of human CL prediction. To help readers overcome this barrier, we introduce each method briefly and demonstrate its usage in the chain of related equations destined to the CLH. Despite efforts in the laboratory steps, huge in vitro (predicted CLH)-in vivo (observed CLH) discrepancy is not rare. A simple remedy to this discrepancy is to correct human predicted CLH using the ratio of in vitro-in vivo CLH obtained from animal species.

Predicting human pharmacokinetics from preclinical data: absorption.

Predicting the rate and extent of oral absorption of drugs in humans has been a challenging task for new drug researchers. This tutorial reviews in vitro and PBPK methods reported in the past decades that are widely applied to predicting oral absorption in humans. The physicochemical property and permeability (typically obtained using Caco-2 system) data is the first necessity to predict the extent of absorption from the gut lumen to the intestinal epithelium (Fa). Intrinsic clearance measured using the human microsome or hepatocytes is also needed to predict the gut (Fg) and hepatic (Fh) bioavailability. However, there are many issues with the correction of the inter-laboratory variability, hepatic cell membrane permeability, CYP3A4 dependency, etc. The bioavailability is finally calculated as F = Fa × Fg × Fh. Although the rate of absorption differs by micro-environments and locations in the intestine, it may be simply represented by ka. The ka, the first-order absorption rate constant, is predicted from in vitro and in vivo data. However, human PK-predicting software based on these PBPK theories should be carefully used because there are many assumptions and variances. They include differences in laboratory methods, inter-laboratory variances, and theories behind the methods. Thus, the user's knowledge and experiences in PBPK and in vitro methods are necessary for proper human PK prediction.

Contribution of Trough Concentration Data in the Evaluation of Multiple-Dose Pharmacokinetics for Drugs with Delayed Distributional Equilibrium and Long Half-Life.

PURPOSE: The performance of "trough sampling before reaching steady-state" and "serial sampling beyond the interval between steady-state" in a multiple-dose pharmacokinetic evaluation was compared. Drugs with long half-lives, following multi-compartment pharmacokinetics, and whose distribution-related characteristics are less likely to be assessed within one dosing interval are focused. PATIENTS AND METHODS: Amlodipine pharmacokinetic data were collected from a human pharmacology study performed in Seoul St. Mary's Hospital (Seoul, Korea). Plasma concentration data until 144 hrs after a single administration was used. Nonlinear mixed-effects modeling was conducted to obtain the "true" model structure and pharmacokinetic parameter estimates. Then, stochastic simulation and estimation were performed using multiple-dose scenarios in various sampling strategies. Parameter accuracy and precision from each scenario were evaluated. RESULTS: A two-compartment model with first-order absorption followed by zero-order absorption with a lag time then first-order elimination was chosen as the final model and used in the stochastic simulation and estimation. In terms of parameter precision, the scenario incorporating data only within one dosing interval showed the worst results (V p /F = 313%, Q/F = 64.3%). Some scenarios including early trough samples yielded comparable outcomes (V p /F = 18.4%, Q/F = 32.1%) to the extended full-PK sampling scenario (V p /F = 15.9%, Q/F = 30.3%), which was the best case. The quality of distribution-related parameters was the major difference between scenarios. CONCLUSION: In multiple-dose studies on drugs with delayed distributional equilibrium, information from a few trough samples can augment the limit of serial sampling within the dosing interval for parameter estimation. With informative trough samples, extended hospitalization for serial sampling (until 3-5 half-lives after the last dose), which is particularly problematic for long half-life drugs, may be avoided. Trough samples obtained at the beginning of the repeated dose were more effective for mixed-effects modeling.

Predicting human pharmacokinetics from preclinical data: volume of distribution.

This tutorial introduces background and methods to predict the human volume of distribution (Vd) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: Vd = Vp + ∑ T (VT × ktp ). In this equation, Vp (plasma volume) and VT (tissue volume) are known physiological values, and ktp (tissue plasma partition coefficient) is experimentally measured. Here, the ktp may be predicted by PBPK models because it is known to be correlated with the physicochemical property of drugs and tissue composition (fraction of lipid and water). Thus, PBPK models' evolution to predict human Vd has been the efforts to find a better function giving a more accurate ktp. When animal PK parameters estimated using i.v. PK data in ≥ 3 species are available, allometric methods can also be used to predict human Vd. Unlike the PBPK method, many different models may be compared to find the best-fitting one in the allometry, a kind of empirical approach. Also, compartmental Vd parameters (e.g., Vc, Vp, and Q) can be predicted in the allometry. Although PBPK and allometric methods have long been used to predict Vd, there is no consensus on method choice. When the discrepancy between PBPK-predicted Vd and allometry-predicted Vd is huge, physiological plausibility of all input and output data (e.g., r2-value of the allometric curve) may be reviewed for careful decision making.

Quantitative Prediction of Human Pharmacokinetics and Pharmacodynamics of CKD519, a Potent Inhibitor of Cholesteryl Ester Transfer Protein (CETP).

CKD519, a selective inhibitor of cholesteryl ester transfer protein(CETP), is undergoing development as an oral agent for the treatment of primary hypercholesterolemia and mixed hyperlipidemia. The aim of this study was to predict the appropriate efficacious dose of CKD519 for humans in terms of the inhibition of CETP activity by developing a CKD519 pharmacokinetic/pharmacodynamic (PK/PD) model based on data from preclinical studies. CKD519 was intravenously and orally administered to hamsters, rats, and monkeys for PK assessment. Animal PK models of all dose levels in each species were developed using mixed effect modeling analysis for exploration, and an interspecies model where allometric scaling was applied was developed based on the integrated animal PK data to predict the human PK profile. PD parameters and profile were predicted using in vitro potency and same-in-class drug information. The two-compartment first-order elimination model with Weibull-type absorption and bioavailability following the sigmoid Emax model was selected as the final PK model. The PK/PD model was developed by linking the interspecies PK model with the Emax model of the same-in-class drug. The predicted PK/PD profile and parameters were used to simulate the human PK/PD profiles for different dose levels, and based on the simulation result, the appropriate efficacious dose was estimated as 25 mg in a 60 kg human. However, there were some discrepancies between the predicted and observed human PK/PD profiles compared to the phase I clinical data. The huge difference between the observed and predicted bioavailability suggests that there is a hurdle in predicting the absorption parameter only from animal PK data.

Population pharmacokinetic analysis of metformin administered as fixed-dose combination in Korean healthy adults.

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.

Erratum: Population Pharmacokinetic Analysis of Metformin Administered as Fixed-Dose Combination in Korean Healthy Adults.

[This corrects the article on p. 25 in vol. 26.].