First-in-human study of IM156, a novel potent biguanide oxidative phosphorylation (OXPHOS) inhibitor, in patients with advanced solid tumors.

Preclinical models suggest anticancer activity of IM156, a novel biguanide mitochondrial protein complex 1 inhibitor of oxidative phosphorylation (OXPHOS). This first-in-human dose-escalation study enrolled patients with refractory advanced solid tumors to determine the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D). Eligible patients received oral IM156 every other day (QOD) or daily (QD) and were assessed for safety, dose-limiting toxicities (DLTs), pharmacokinetics, and preliminary signals of efficacy. 22 patients with advanced cancers (gastric, n = 8; colorectal, n = 3; ovarian, n = 3; other, n = 8) received IM156 100 to 1,200 mg either QOD or QD. There were no DLTs. However, 1,200 mg QD was not well tolerated due to nausea; 800 mg QD was determined as the RP2D. The most frequent treatment-related AEs (TRAEs) were nausea (n = 15; 68%), diarrhea (n = 10; 46%), emesis (n = 9; 41%), fatigue (n = 4; 18%) and abdominal pain, constipation, and blood lactate increased (n = 2 each; 9%). Grade 3 nausea (n = 3; 14%) was the only grade ≥ 3 TRAE. Plasma exposures increased dose proportionally; mean Day 27 area under the curve (AUC0-24) values were higher following QD administration compared to the respective QOD regimen. Stable disease (SD), observed in 7 (32%) patients (confirmed in 2 [9%]), was the best response. To our knowledge, this is the first phase 1 study of an OXPHOS inhibitor that established a RP2D for further clinical development in cancer. Observed AEs of IM156 were manageable and SD was the best response.

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.

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.

A partial imputation EM-algorithm to adjust the overestimated shape parameter of the Weibull distribution fitted to the clinical time-to-event data.

BACKGROUND AND OBJECTIVES: Typical clinical data can suffer routine information loss when event times are rounded to the nearest day and right-censored at the end of follow-up. Because of the daily basis recording system, for the first 24 h, there are no events, which can damage the estimation of the Weibull survival model. Its estimation bias is inevitable since, for this short period, massive events might have occurred, the data is missing, and the fitted Weibull model is to show a steep slope. This phenomenon of estimation bias caused by the information loss caused by the problem of measurement resolution has not been properly discussed so far. METHODS: We propose a partial imputation Expectation Maximization (PIEM)-algorithm to estimate missing lifetimes only for day 1 at the mode among the whole clinical follow-up days. Based on various Weibull distributions, we simulated clinical sets after rounding and censoring raw event times and prepared chimera sets by partially substituting the imputed lifetimes only for the 24 h at the mode among the entire clinical sets. RESULTS: For shape parameter ≤ 1, almost all the 95% prediction intervals (PIs) of both parameters in the chimera sets include their true values, while those in the clinical sets miss most of the true shape parameters and some of the true scale parameters. Estimating a small proportion of missing data only for the 24 h period, while keeping the rest as they are, greatly reduces biases of both scale and shape parameters. For shape parameter >1, the chimera sets consistently outperform the clinical sets. CONCLUSIONS: The PIEM-algorithm may be applied as an intuitive tool for time-to-event modeling of survival data with this kind of information loss.

A Population Pharmacokinetic and Pharmacodynamic Model of CKD-519.

CKD-519 is a selective and potent cholesteryl ester transfer protein (CETP) inhibitor that is being developed for dyslipidemia. Even though CKD-519 has shown potent CETP inhibition, the exposure of CKD-519 was highly varied, depending on food and dose. For highly variable exposure drugs, it is crucial to use modeling and simulation to plan proper dose selection. This study aimed to develop population pharmacokinetic (PK) and pharmacodynamics (PD) models of CKD-519 and to predict the proper dose of CKD-519 to achieve target levels for HDL-C and LDL-C using results from multiple dosing study of CKD-519 with a standard meal for two weeks in healthy subjects. The results showed that a 3-compartment with Erlang's distribution, followed by the first-order absorption, adequately described CKD-519 PK, and the bioavailability, which decreased by dose and time was incorporated into the model (NONMEM version 7.3). After the PK model development, the CETP activity and cholesterol (HDL-C and LDL-C) levels were sequentially modeled using the turnover model, including the placebo effect. According to PK-PD simulation results, 200 to 400 mg of CKD-519 showing a 40% change in HDL-C and LDL-C from baselines was recommended for proof of concept studies in patients with dyslipidemia.

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.

Usefulness of Bnet, a Simple Linear Metric in Discerning Torsades De Pointes Risks in 28 CiPA Drugs.

The Comprehensive in vitro Proarrhythmia Assay (CiPA) project suggested the torsade metric score (TMS) which requires substantial computing resources as a useful biomarker to predict proarrhythmic risk from human ether-à-go-go-related gene (hERG) and a few other ion channel block data. The TMS was useful to predict low TdP risks of drugs blocking Na+ (ranolazine) and Ca2+ (verapamil) channels as well as the hERG channel. However, Mistry asserted that the simple linear metric, Bnet reflecting net blockade of a few influential ion channels has similar predictive power. Here we compared the predictability of Bnet and TMS for the 12 training and 16 validation CiPA drugs which were pre-classified into three categories according to the known TdP risks (low, intermediate, and high risk) by CiPA. Bnet at 5×Cmax (Bnet5×Cmax) was calculated using the ion-channel IC50 and Hill coefficients of CiPA drugs collected from previous reports by the CiPA team and others. The receiver operating characteristic curve area under curve (ROC AUC) values for TMS and Bnet5×Cmax as performance metrics in discerning low versus intermediate/high risk categories for the 28 CiPA drugs were similar. However, Bnet5×Cmax was much inferior to TMS at discerning between intermediate- and high-risk drugs. Dynamic Bnet, which used in silico hERG dynamic parameters unlike conventional Bnet, improved the misspecification. Thus, we propose that Bnet5×Cmax is used for quick screening of TdP risks of drug candidates and if the "intermediate/high" risk is predicted by Bnet5×Cmax, in silico approaches, such as dynamic Bnet or TMS, may be further considered.

Three-Dimensional Heart Model-Based Screening of Proarrhythmic Potential by in silico Simulation of Action Potential and Electrocardiograms.

The proarrhythmic risk is a major concern in drug development. The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative has proposed the JTpeak interval on electrocardiograms (ECGs) and qNet, an in silico metric, as new biomarkers that may overcome the limitations of the hERG assay and QT interval. In this study, we simulated body-surface ECGs from patch-clamp data using realistic models of the ventricles and torso to explore their suitability as new in silico biomarkers for cardiac safety. We tested seven drugs in this study: dofetilide (high proarrhythmic risk), ranolazine, verapamil (QT increasing, but safe), bepridil, cisapride, mexiletine, and diltiazem. Human ventricular geometry was reconstructed from computed tomography (CT) images, and a Purkinje fiber network was mapped onto the endocardial surface. The electrical wave propagation in the ventricles was obtained by solving a reaction-diffusion equation using finite-element methods. The body-surface ECG data were calculated using a torso model that included the ventricles. The effects of the drugs were incorporated in the model by partly blocking the appropriate ion channels. The effects of the drugs on single-cell action potential (AP) were examined first, and three-dimensional (3D) body-surface ECG simulations were performed at free Cmax values of 1×, 5×, and 10×. In the single-cell and ECG simulations at 5× Cmax, dofetilide, but not verapamil or ranolazine, caused arrhythmia. However, the non-increasing JTpeak caused by verapamil and ranolazine that has been observed in humans was not reproduced in our simulation. Our results demonstrate the potential of 3D body-surface ECG simulation as a biomarker for evaluation of the proarrhythmic risk of candidate drugs.

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.

Potency and plasma protein binding of drugs in vitro-a potentially misleading pair for predicting in vivo efficacious concentrations in humans.

In drug discovery or preclinical stages of development, potency parameters such as IC50, K i, or K d in vitro have been routinely used to predict the parameters of efficacious exposure (AUC, C min, etc.) in humans. However, to our knowledge, the fundamental assumption that the potency in vitro is correlated with the efficacious concentration in vivo in humans has not been investigated extensively. Thus, the present review examined this assumption by comparing a wide range of published pharmacokinetic (PK) and potency data. If the drug potency in vitro and its in vivo effectiveness in humans are well correlated, the steady-state average unbound concentrations in humans [C u_ss.avg = f u·F·Dose/(CL·τ) = f u·AUCss/τ] after treatment with approved dosage regimens should be higher than, or at least comparable to, the potency parameters assessed in vitro. We reviewed the ratios of C u_ss.avg/potency in vitro for a total of 54 drug entities (13 major therapeutic classes) using the dosage, PK, and in vitro potency reported in the published literature. For 54 drugs, the C u_ss.avg/in vitro potency ratios were < 1 for 38 (69%) and < 0.1 for 22 (34%) drugs. When the ratios were plotted against f u (unbound fraction), "ratio < 1" was predominant for drugs with high protein binding (90% of drugs with f u ≤ 5%; i.e., 28 of 31 drugs). Thus, predicting the in vivo efficacious unbound concentrations in humans using only in vitro potency data and f u should be avoided, especially for molecules with high protein binding.

Application of Pharmacometrics in Pharmacotherapy: Open-Source Software for Vancomycin Therapeutic Drug Management.

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.

What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing.

Model-informed precision dosing (MIPD) is modeling and simulation in healthcare to predict the drug dose for a given patient based on their individual characteristics that is most likely to improve efficacy and/or lower toxicity in comparison to traditional dosing. This paper describes the background and status of MIPD and the activities at the 1st Asian Symposium of Precision Dosing. The theme of the meeting was the question, "What does it take to make MIPD common practice?" Formal presentations highlighted the distinction between genetic and non-genetic sources of variability in drug exposure and response, the use of modeling and simulation as decision support tools, and the facilitators to MIPD implementation. A panel discussion addressed the types of models used for MIPD, how the pharmaceutical industry views MIPD, ways to upscale MIPD beyond academic hospital centers, and the essential role of healthcare professional education as a way to progress. The meeting concluded with an ongoing commitment to use MIPD to improve patient care.

Evaluation of Omeprazole Limited Sampling Strategies to Estimate Constitutive Cytochrome P450 2C19 Activity in Healthy Adults.

BACKGROUND: Limited sampling strategy (LSS) is a validated method to estimate pharmacokinetic (PK) parameters from a reduced number of samples. Omeprazole is used to phenotype in vivo cytochrome P450 (CYP) 2C19 activity. This study examined an LSS using 2 estimation methods to determine apparent oral clearance (CL/F) and thus CYP2C19 activity. METHODS: Data from 7 previously published studies included healthy subjects receiving a single, oral dose of omeprazole with intensive PK sampling. CL/F was estimated using noncompartmental analysis (NCA) and population PK modeling. LSS was simulated by selecting the 1, 2, 4, and/or 6-hour postdose time points. Linear regression was performed to assess whether CL/F estimated from limited sampling could accurately predict CL/F from the full PK profile. RESULTS: Median CL/F was 23.7 L/h by NCA and 19.3 L/h by population PK modeling. In comparing the LSS NCA estimated versus observed CL/F, all evaluated linear regression models had unacceptable coefficients of determination (r, range: 0.14-0.81). With the population PK approach, 737 plasma concentrations (n = 71) and CYP2C19 genotype data were described with a 1-compartment structural model with mixed zero and first-order absorption and lag time. In comparing the population PK LSS estimated versus observed CL/F, all evaluated linear regression models had unacceptable r (range: 0.02-0.74). Post hoc comparison of CYP2C19 poor metabolizers versus CYP2C19 extensive metabolizers resulted in significantly lower CL/F in poor metabolizers versus extensive metabolizers. CONCLUSIONS: Omeprazole LSS performed poorly in estimating CL/F using 2 separate estimation approaches and does not seem to be a suitable method for determining CYP2C19 activity.

Physiologically-based pharmacokinetic predictions of intestinal BCRP-mediated drug interactions of rosuvastatin in Koreans.

It was recently reported that the Cmax and AUC of rosuvastatin increases when it is coadministered with telmisartan and cyclosporine. Rosuvastatin is known to be a substrate of OATP1B1, OATP1B3, NTCP, and BCRP transporters. The aim of this study was to explore the mechanism of the interactions between rosuvastatin and two perpetrators, telmisartan and cyclosporine. Published (cyclosporine) or newly developed (telmisartan) PBPK models were used to this end. The rosuvastatin model in Simcyp (version 15)'s drug library was modified to reflect racial differences in rosuvastatin exposure. In the telmisartan-rosuvastatin case, simulated rosuvastatin CmaxI/Cmax and AUCI/AUC (with/without telmisartan) ratios were 1.92 and 1.14, respectively, and the Tmax changed from 3.35 h to 1.40 h with coadministration of telmisartan, which were consistent with the aforementioned report (CmaxI/Cmax: 2.01, AUCI/AUC:1.18, Tmax: 5 h → 0.75 h). In the next case of cyclosporine-rosuvastatin, the simulated rosuvastatin CmaxI/Cmax and AUCI/AUC (with/without cyclosporine) ratios were 3.29 and 1.30, respectively. The decrease in the CLint,BCRP,intestine of rosuvastatin by telmisartan and cyclosporine in the PBPK model was pivotal to reproducing this finding in Simcyp. Our PBPK model demonstrated that the major causes of increase in rosuvastatin exposure are mediated by intestinal BCRP (rosuvastatin-telmisartan interaction) or by both of BCRP and OATP1B1/3 (rosuvastatin-cyclosporine interaction).

Erratum: R-based reproduction of the estimation process hidden behind NONMEM Part 2: First-order conditional estimation.

[This corrects the article on p. 161 in vol. 24.].

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.].

Five years of the CiPA project (2013-2018): what did we learn?

Cases of drug-induced QT prolongation and sudden cardiac deaths resulted in market withdrawal of many drugs and world-wide regulatory changes through accepting the ICH guidelines E14 and S7B. However, because the guidelines were not comprehensive enough to cover the electrophysiological changes by drug-induced cardiac ion channel blocking, CiPA was initiated by experts in governments and academia in the USA, Europe, and Japan in 2013. Five years have passed since the launch of the CiPA initiative that aimed to improve the current ICH guidelines. This report reviews the current achievements of the CiPA initiative and explores unresolved issues.