Clinical Significance of Long Non-Coding RNA SNHG5 in the Diagnosis and Prognosis of Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is preventable and requires early screening. The study aimed to examine the clinical values of long non-coding RNA (lncRNA) SNHG5 in COPD diagnosis and prognosis. Out of 160 COPD patients, 80 were in the stable stage and 80 were in the acute exacerbation of COPD stage (AECOPD). SNHG5 expression was detected via qRT-PCR. The survival analysis was conducted using Cox regression analysis and K-M curve. SNHG5 levels significantly reduced in both stable COPD and AECOPD groups compared with the control group, with AECOPD group recording the lowest values. SNHG5 levels were negatively correlated with GOLD stage. Serum SNHG5 can differentiate stable COPD patients from healthy individuals (AUC = 0.805), and can screen AECOPD from stable ones (AUC = 0.910). SNHG5 negatively influenced the release of inflammatory cytokines. For AECOPD patients, those with severe cough and wheezing dyspnea symptoms exhibited the lowest values of SNUG5. Among the 80 AECOPD patients, 16 cases died in the one-year follow-up, all of whom had low levels of SNHG5. SNHG5 levels independently influenced survival outcomes, patients with low SNHG5 levels had a poor prognosis. Thus, lncRNA SNHG5, which is downregulated in patients with COPD (especially AECOPD), can potentially protect against AECOPD and serve as a novel prognostic biomarker for AECOPD.

Development and validation of an HPLC coupled with tandem mass spectrometry method for the determination of HSK7653, a novel super long-acting dipeptidyl peptidase-4 inhibitor, in human plasma and urine and its application to a pharmacokinetic study.

HSK7653 is a novel super long-acting dipeptidyl peptidase-4 inhibitor, which is promising for the treatment of type 2 diabetes mellitus with the twice-monthly dosing regimen. In this article, a robust and sensitive HPLC coupled with tandem mass spectrometry method for determining the concentration of HSK7653 in human plasma and urine was developed and validated for the first time. Plasma and urine samples were prepared by protein precipitation. After that, the extracts were analyzed using an LC-20A HPLC system coupled with API 4000 tandem MS equipped with an electrospray ionization source in positive mode. Separation was obtained using an XBridge Phenyl column (2.1 × 50 mm, 3.5 µm) with a gradient elution of acetonitrile and water containing 0.1% formic acid and 5% acetonitrile at room temperature. This bioanalysis method has been fully validated and the results showed good sensitivity and specificity. In brief, the standard curves were linear over the concentration range of 2.00-2000 ng/ml for plasma and 20.0-20,000 ng/ml for urine, respectively. In addition, the precisions of inter- and intra-run of HSK7653 were less than 12.7% and the accuracies were -3.3% to 6.3% for both plasma and urine. Finally, this method was successfully applied to explore the pharmacokinetic characteristics of HSK7653 in Chinese healthy volunteers in a first-in-human study.

Model-informed drug development: The mechanistic HSK3486 physiologically based pharmacokinetic model informing dose decisions in clinical trials of specific populations.

HSK3486, a central nervous system inhibitor, has demonstrated superior anesthetic properties in comparison with propofol. Owing to the high liver extraction ratio of HSK3486 and the limited susceptibility to the multi-enzyme inducer, rifampicin, the indicated population of HSK3486 is substantial. Nevertheless, in order to expand the population with indications, it is crucial to assess the systemic exposure of HSK3486 in specific populations. Moreover, the main metabolic enzyme of HSK3486 is UGT1A9, which shows a gene polymorphism in the population. Thus, to scientifically design the dose regimen for clinical trials in specific populations, a HSK3486 physiologically based pharmacokinetic model was developed in 2019 to support model-informed drug development (MIDD). Several untested scenarios of HSK3486 administration in specific populations, and the effect of the UGT1A9 gene polymorphism on HSK3486 exposure were estimated as well. The predicted systemic exposure was increased slightly in patients with hepatic impairment and in the elderly, consistent with later clinical trial data. Meanwhile, there was no change in the systemic exposure of patients with severe renal impairment and in neonates. However, under the same dose, the predicted exposure of pediatric patients aged 1 month to 17 years was decreased significantly (about 21%-39%). Although these predicted results in children have not been validated by clinical data, they are comparable to clinical findings for propofol in children. The dose of HSK3486 in pediatrics may need to be increased and can be adjusted according to the predicted results. Moreover, the predicted HSK3486 systemic exposure in the obese population was increased by 28%, and in poor metabolizers of UGT1A9 might increase by about 16%-31% compared with UGT1A9 extensive metabolizers. Combined with the relatively flat exposure-response relationship for efficacy and safety (unpublished), obesity and genetic polymorphisms are unlikely to result in clinically significant changes in the anesthetic effect at the 0.4 mg/kg dose in adults. Therefore, MIDD can indeed provide supportive information for dosing decisions and facilitate the efficient and effective development of HSK3486.

Development of a physiologically based pharmacokinetic (PBPK) population model for Chinese elderly subjects.

AIMS: This study aims to develop and verify a physiologically based pharmacokinetic (PBPK) population model for the Chinese geriatric population in Simcyp. METHODS: Firstly, physiological information for the Chinese geriatric population was collected and later employed to develop the Chinese geriatric population model by recalibration of corresponding physiological parameters in the Chinese adult population model available in Simcyp (i.e., Chinese healthy volunteer model). Secondly, drug-dependent parameters were collected for six drugs with different elimination pathways (i.e., metabolized by CYP1A2, CYP3A4 or renal excretion). The drug models were then developed and verified by clinical data from Chinese adults, Caucasian adults and Caucasian elderly subjects to ensure that drug-dependent parameters are correctly inputted. Finally, the tested drug models in combination with the newly developed Chinese geriatric population model were applied to simulate drug concentration in Chinese elderly subjects. The predicted results were then compared with the observations to evaluate model prediction performance. RESULTS: Ninety-eight per cent of predicted AUC, 95% of predicted Cmax , and 100% of predicted CL values were within two-fold of the observed values, indicating all drug models were properly developed. The drug models, combined with the newly developed population model, were then used to predict pharmacokinetics in Chinese elderly subjects aged 60-93. The predicted AUC, Cmax , and CL values were all within two-fold of the observed values. CONCLUSION: The population model for the Chinese elderly subjects appears to adequately predict the concentration of the drug that was metabolized by CYP1A2, CYP3A4 or eliminated by renal clearance.

Population-based meta-analysis of chloroquine: informing chloroquine pharmacokinetics in COVID-19 patients.

AIMS: Chloroquine (CQ) has been repurposed to treat coronavirus disease 2019 (COVID-19). Understanding the pharmacokinetics (PK) in COVID-19 patients is essential to study its exposure-efficacy/safety relationship and provide a basis for a possible dosing regimen optimization. SUBJECT AND METHODS: In this study, we used a population-based meta-analysis approach to develop a population PK model to characterize the CQ PK in COVID-19 patients. An open-label, single-center study (ethical review approval number: PJ-NBEY-KY-2020-063-01) was conducted to assess the safety, efficacy, and pharmacokinetics of CQ in patients with COVID-19. The sparse PK data from 50 COVID-19 patients, receiving 500 mg CQ phosphate twice daily for 7 days, were combined with additional CQ PK data from 18 publications. RESULTS: A two-compartment model with first-order oral absorption and first-order elimination and an absorption lag best described the data. Absorption rate (ka) was estimated to be 0.559 h-1, and a lag time of absorption (ALAG) was estimated to be 0.149 h. Apparent clearance (CL/F) and apparent central volume of distribution (V2/F) was 33.3 l/h and 3630 l. Apparent distribution clearance (Q/F) and volume of distribution of peripheral compartment (Q3/F) were 58.7 l/h and 5120 l. The simulated CQ concentration under five dosing regimens of CQ phosphate were within the safety margin (400 ng/ml). CONCLUSION: Model-based simulation using PK parameters from the COVID-19 patients shows that the concentrations under the currently recommended dosing regimen are below the safety margin for side-effects, which suggests that these dosing regimens are generally safe. The derived population PK model should allow for the assessment of pharmacokinetics-pharmacodynamics (PK-PD) relationships for CQ when given alone or in combination with other agents to treat COVID-19.

Physiologically based pharmacokinetic model of renally cleared antibacterial drugs in Chinese renal impairment patients.

To preliminarily develop physiologically based population models for Chinese renal impairment patients and to evaluate the prediction performance of new population models by renally cleared antibacterial drugs. First, demographic data and physiological parameters of Chinese renal impairment patients were collected, and then the coefficients of the relative demographic and physiological equation were recalibrated to construct the new population models. Second, drug-independent parameters of ceftazidime, cefodizime, vancomycin, and cefuroxime were collected and verified by Chinese healthy volunteers, Caucasian healthy volunteers, and Caucasian renal impairment population models built in Simcyp. Finally, the newly developed population models were applied to predict the plasma concentration of four antibacterial drugs in Chinese renal impairment patients. The new physiologically based pharmacokinetic (PBPK) population models can predict the main pharmacokinetic parameters, including area under the plasma concentration-time curve extrapolated to infinity (AUCinf ), renal clearance (CLr ), and peak concentration (Cmax ), of ceftazidime, cefodizime, vancomycin, and cefuroxime following intravenous administrations with less than twofold error in mild, moderate, and severe Chinese renal impairment patients. The accuracy and precision of the predictions were improved compared with the Chinese healthy volunteers and Caucasian renal impairment population models. The PBPK population models were preliminarily developed and the first-step validation results of four antibacterial drugs following intravenous administration showed acceptable accuracy and precision. The population models still need more systematic validation by using more drugs and scenarios in future studies to support their applications on dosage recommendation for Chinese renal impairment patients.

In Vitro Antiviral Activity and Projection of Optimized Dosing Design of Hydroxychloroquine for the Treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2).

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first broke out in 2019 and subsequently spread worldwide. Chloroquine has been sporadically used in treating SARS-CoV-2 infection. Hydroxychloroquine shares the same mechanism of action as chloroquine, but its more tolerable safety profile makes it the preferred drug to treat malaria and autoimmune conditions. We propose that the immunomodulatory effect of hydroxychloroquine also may be useful in controlling the cytokine storm that occurs late phase in critically ill patients with SARS-CoV-2. Currently, there is no evidence to support the use of hydroxychloroquine in SARS-CoV-2 infection. METHODS: The pharmacological activity of chloroquine and hydroxychloroquine was tested using SARS-CoV-2-infected Vero cells. Physiologically based pharmacokinetic (PBPK) models were implemented for both drugs separately by integrating their in vitro data. Using the PBPK models, hydroxychloroquine concentrations in lung fluid were simulated under 5 different dosing regimens to explore the most effective regimen while considering the drug's safety profile. RESULTS: Hydroxychloroquine (EC50 = 0.72 µM) was found to be more potent than chloroquine (EC50 = 5.47 µM) in vitro. Based on PBPK models results, a loading dose of 400 mg twice daily of hydroxychloroquine sulfate given orally, followed by a maintenance dose of 200 mg given twice daily for 4 days is recommended for SARS-CoV-2 infection, as it reached 3 times the potency of chloroquine phosphate when given 500 mg twice daily 5 days in advance. CONCLUSIONS: Hydroxychloroquine was found to be more potent than chloroquine to inhibit SARS-CoV-2 in vitro.

Early metabolic characterization of brain tissues after whole body radiation based on gas chromatography-mass spectrometry in a rat model.

Radiation-induced brain injury involves acute, early delayed and late delayed damage based on the time-course and clinical manifestations. The acute symptoms are mostly transient and reversible, whereas the late delayed radiation-induced changes are progressive and irreversible. Therefore, evaluation of the organ-specific early response to ionizing radiation exposure is necessary for improving treatment strategies and minimizing possible damage at an early stage after radiation exposure. In the current study, the gas chromatography-mass spectrometry technique based on metabolomics coupled with metabolic correlation network was applied to investigate the early metabolic characterization of rat brain tissues following irradiation. Our findings showed that the metabolic response to irradiation was not just limited to the variations of individual metabolite levels, but also accompanied by alterations of network correlations among various metabolites. Metabolite clustering indicated that energy metabolism disorder and inflammation response were induced following radiation exposure. The correlation networks revealed that the strong positive correlations of differential metabolites were highly reduced and significant negative linkages were highlighted in irradiated groups even without statistical changes in metabolic levels. Our findings provided new insights into our understanding of the radiation-induced acute brain injury mechanism and clues as to the therapy target for clinical applications.

Development of a simple HPLC-MS/MS method to simultaneously determine teriflunomide and its metabolite in human plasma and urine: Application to clinical pharmacokinetic study of teriflunomide sodium and leflunomide.

A simple high-performance liquid chromatography coupled with tandem mass spectrometry method was developed and fully validated to simultaneously determine teriflunomide (TER) and its metabolite 4-trifluoro-methylaniline oxanilic acid (4-TMOA) in human plasma and urine. Merely 50 µL plasma and 20 µL urine were employed in sample preparation using protein precipitation and direct dilution method, respectively. An Agilent Zorbax eclipse plus C18 column was selected to achieve rapid separation for TER and 4-TMOA within 3 min. Electrospray ionization under multiple reaction monitoring was used to monitor the ion transitions for TER (m/z 269.0 → 159.9), 4-TMOA (m/z 231.9 → 160.0), internal standard teriflunomide-d4 (m/z 273.0 → 164.0) and 2-amino-4-trifluoromethyl benzoic acid (m/z 203.8 → 120.1), operating in the negative ion mode. This method proved to have better accuracy and precision over concentration range of 10-5000 ng/mL in plasma as well as 10-10,000 ng/mL in urine. After a full validation, this method was successfully applied in a pharmacokinetic study of teriflunomide sodium and leflunomide in Chinese healthy volunteers.

Bacteria and poisonous plants were the primary causative hazards of foodborne disease outbreak: a seven-year survey from Guangxi, South China.

BACKGROUND: Foodborne diseases are a worldwide public health problem. However, data regarding epidemiological characteristics are still lacking in China. We aimed to analyze the characteristics of foodborne diseases outbreak from 2010 to 2016 in Guangxi, South China. METHODS: A foodborne disease outbreak is the occurrence of two or more cases of a similar foodborne disease resulting from the ingestion of a common food. All data are obtained from reports in the Public Health Emergency Report and Management Information System of the China Information System for Disease Control and Prevention, and also from special investigation reports from Guangxi province. RESULTS: A total of 138 foodborne diseases outbreak occurred in Guangxi in the past 7 years, leading to 3348 cases and 46 deaths. Foodborne disease outbreaks mainly occurred in the second and fourth quarters, and schools and private homes were the most common sites. Ingesting toxic food by mistake, improper cooking and cross contamination were the main routes of poisoning which caused 2169 (64.78%) cases and 37 (80.43%) deaths. Bacteria (62 outbreaks, 44.93%) and poisonous plants (46 outbreaks, 33.33%) were the main etiologies of foodborne diseases in our study. In particular, poisonous plants were the main cause of deaths involved in the foodborne disease outbreaks (26 outbreaks, 56.52%). CONCLUSIONS: Bacteria and poisonous plants were the primary causative hazard of foodborne diseases. Some specific measures are needed for ongoing prevention and control against the occurrence of foodborne diseases.

A high-performance liquid chromatography-tandem mass spectrometry method for simultaneous determination of imigliptin, its five metabolites and alogliptin in human plasma and urine and its application to a multiple-dose pharmacokinetic study.

Imigliptin is a novel DPP-4 inhibitor, designed to treat type 2 diabetes mellitus (T2DM). A selective and sensitive method was developed using high performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) to simultaneously quantify imigliptin, its five metabolites, and alogliptin in human plasma and urine. Solid-phase extraction (SPE) and direct dilution were used to extract imigliptin, its five metabolites, alogliptin from plasma and urine, respectively. The extracts were injected onto a SymmetryShield RP8 column with a gradient elution of methanol and water containing 10 mM ammonium formate (pH = 7). Ionization of all analytes was performed using an electrospray ionization (ESI) source in positive mode and detection was carried out with multiple reaction monitoring (MRM) mode. The results revealed that the method had excellent selectivity and linearity. Inter- and intra-batch precisions of all analytes were less than 15% and the accuracies were within 85%-115% for both plasma and urine. The sensitivity, matrix effect, extraction recovery, linearity, and stabilities were validated for all analytes in human plasma and urine. In conclusion, the validation results showed that this method was robust, specific, and sensitive and it can successfully applied to a pharmacokinetic study of Chinese T2DM subjects after oral dose of imigliptin and alogliptin.

The multiple roles of autophagy in uveal melanoma and the microenvironment.

PURPOSE: Uveal melanoma (UM) is the most common primary malignant intraocular tumor in adults, and effective clinical treatment strategies are still lacking. Autophagy is a lysosome-dependent degradation system that can encapsulate abnormal proteins, damaged organelles. However, dysfunctional autophagy has multiple types and plays a complex role in tumorigenicity depending on many factors, such as tumor stage, microenvironment, signaling pathway activation, and application of autophagic drugs. METHODS: A systematic review of the literature was conducted to analyze the role of autophagy in UM, as well as describing the development of autophagic drugs and the link between autophagy and the tumor microenvironment. RESULTS: In this review, we summarize current research advances regarding the types of autophagy, the mechanisms of autophagy, the application of autophagy inhibitors or agonists, autophagy and the tumor microenvironment. Finally, we also discuss the relationship between autophagy and UM. CONCLUSION: Understanding the molecular mechanisms of how autophagy differentially affects tumor progression may help to design better therapeutic regimens to prevent and treat UM.

Dose Prediction and Pharmacokinetic Simulation of XZP-5610, a Small Molecule for NASH Therapy, Using Allometric Scaling and Physiologically Based Pharmacokinetic Models.

The objectives of this study were to support dose selection of a novel FXR agonist XZP-5610 in first-in-human (FIH) trials and to predict its liver concentrations in Chinese healthy adults. Key parameters for extrapolation were measured using in vitro and in vivo models. Allometric scaling methods were employed to predict human pharmacokinetics (PK) parameters and doses for FIH clinical trials. To simulate the PK profiles, a physiologically based pharmacokinetic (PBPK) model was developed using animal data and subsequently validated with clinical data. The PBPK model was employed to simulate XZP-5610 concentrations in the human liver across different dose groups. XZP-5610 exhibited high permeability, poor solubility, and extensive binding to plasma proteins. After a single intravenous or oral administration of XZP-5610, the PK parameters obtained from rats and beagle dogs were used to extrapolate human parameters, resulting in a clearance of 138 mL/min and an apparent volume of distribution of 41.8 L. The predicted maximum recommended starting dose (MRSD), minimal anticipated biological effect level (MABEL), and maximum tolerated dose (MTD) were 0.15, 2, and 3 mg, respectively. The PK profiles and parameters of XZP-5610, predicted using the PBPK model, demonstrated good consistency with the clinical data. By using allometric scaling and PBPK models, the doses, PK profile, and especially the liver concentrations were successfully predicted in the FIH study.

Integrated models of population pharmacokinetics and exposure response to optimize dosage regimen for anaprazole sodium in duodenal ulcer.

Anaprazole sodium enteric-coated tablet is a novel proton pump inhibitor which has been approved for the treatment of duodenal ulcer. The aim of this study is to provide reliable information for the design of an optimal dosage regimen. Population pharmacokinetics and exposure-response models were integrated to evaluate the pharmacokinetic parameters and covariates of Anaprazole and its metabolite M21-1, and subsequently provided dosage suggestions based on clinical trials and simulation data. A pharmacokinetic model incorporating two-compartment for the parent drug and one-compartment for the metabolite, with both first-order and zero-order mixed absorption was used to describe the pharmacokinetics of Anaprazole and M21-1. Age emerged as a significant covariate affecting the elimination rate constant of M21-1, with clearance decreasing as age advances. No correlation was observed between the pharmacokinetics of Anaprazole or M21-1 and the adverse reactions under the current dosages. BMI might be the influence factor of the mild gastrointestinal adverse reactions. Meanwhile, Anaprazole had a good healing rate (94.0 %) in duodenal ulcer patients and the exposure-response analysis indicated that the cured results were not influenced by the exposure parameters of parent drug or metabolite. In conclusion, the drug is safe when dosing between 20 and 100 mg once a day.

Development of a Physiologically Based Pharmacokinetic Population Model for Diabetic Patients and its Application to Understand Disease-drug-drug Interactions.

INTRODUCTION: The activity changes of cytochrome P450 (CYP450) enzymes, along with the complicated medication scenarios in diabetes mellitus (DM) patients, result in the unanticipated pharmacokinetics (PK), pharmacodynamics (PD), and drug-drug interactions (DDIs). Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool for assessing the influence of disease status on CYP enzymes and the resulting DDIs. This work aims to develop a novel diabetic PBPK population model to facilitate the prediction of PK and DDI in DM patients. METHODS: First, mathematical functions were constructed to describe the demographic and non-CYP physiological characteristics specific to DM, which were then incorporated into the PBPK model to quantify the net changes in CYP enzyme activities by comparing the PK of CYP probe drugs in DM versus non-DM subjects. RESULTS: The results show that the enzyme activity is reduced by 32.3% for CYP3A4/5, 39.1% for CYP2C19, and 27% for CYP2B6, while CYP2C9 activity is enhanced by 38% under DM condition. Finally, the diabetic PBPK model was developed through integrating the DM-specific CYP activities and other parameters and was further used to perform PK simulations under 12 drug combination scenarios, among which 3 combinations were predicted to result in significant PK changes in DM, which may cause DDI risks in DM patients. CONCLUSIONS: The PBPK modeling applied herein provides a quantitative tool to assess the impact of disease factors on relevant enzyme pathways and potential disease-drug-drug-interactions (DDDIs), which may be useful for dosing regimen optimization and minimizing the DDI risks associated with the treatment of DM.

Model-based exploration of the rationality of off-label use of cetirizine in Chinese pediatric patients: a prospective cohort study.

Aims: Cetirizine is frequently administered at an increased dosage in clinical practice and recommended by several guidelines. Nonetheless, the pharmacokinetic (PK) profile and real-world safety data remain insufficient in the Chinese pediatric population. The objective of the current study is to develop a population pharmacokinetic (PPK) model for cetirizine in Chinese pediatric patients and to investigate the rationale behind its off-label usage. Methods: A prospective cohort study was conducted, enrolling children who had been diagnosed with allergic diseases and prescribed cetirizine. The outcomes were safety and pharmacokinetic (PK) parameters. Cetirizine concentrations were measured using a pre-established analytical method. Subsequently, a PK model was developed, followed by model evaluation and simulation. The developed PK model was employed to investigate the drug exposure differences across various age groups and to simulate scenarios of potential overdose. Results: Sixty-three children were enrolled, and 24 of them received a cetirizine dose exceeding the recommended dosage. A PPK model, based on published literature, served as the basis of our analysis, with adjustment made to estimate certain parameters. The final model evaluation and validation indicated accurate predictive performance and robust parameter estimation. Simulations conducted for the label-dose among age 1-12 indicated median maximum concentration at steady state (Cmax,ss) of 7 year old children could be the highest. The model was also used to predict the off-label dose scenarios and overdose patient to support the clinical decision. There were no adverse drug reactions in either group. Conclusion: This study provides evidence-based and model-based exploration for optimizing cetirizine usage in Chinese pediatric patients. The cetirizine PPK model showed accurate predictive performance and could be utilized to simulate individual patient exposure in real-world clinical scenarios.

Population Pharmacokinetic/Pharmacodynamic Analysis of the Glucokinase Activator PB201 in Healthy Volunteers and Patients with Type 2 Diabetes Mellitus: Facilitating the Clinical Development of PB201 in China.

PB201 is an orally active, partial glucokinase activator targeting both pancreatic and hepatic glucokinase. As the second glucokinase activator studied beyond phase I, PB201 has demonstrated promising glycemic effects as well as favorable pharmacokinetic (PK) and safety profiles in patients with type 2 diabetes mellitus (T2DM). This study aims to develop a population PK/pharmacodynamic (PD) model for PB201 using the pooled data from nine phase I/II clinical trials conducted in non-Chinese healthy volunteers and a T2DM population and to predict the PK/PD profile of PB201 in a Chinese T2DM population. We developed the PK/PD model using the non-linear mixed-effects modeling approach. All runs were performed using the first-order conditional estimation method with interaction. The pharmacokinetics of PB201 were well fitted by a one-compartment model with saturable absorption and linear elimination. The PD effects of PB201 on reducing the fasting plasma glucose and glycosylated hemoglobin levels in the T2DM population were described by indirect response models as stimulating the elimination of fasting plasma glucose, where the production of glycosylated hemoglobin was assumed to be stimulated by fasting plasma glucose. Covariate analyses revealed enhanced absorption of PB201 by food and decreased systemic clearance with ketoconazole co-administration, while no significant covariate was identified for the pharmacodynamics. The population PK model established for non-Chinese populations was shown to be applicable to the Chinese T2DM population as verified by the PK data from the Chinese phase I study. The final population PK/PD model predicted persistent and dose-dependent reductions in fasting plasma glucose and glycosylated hemoglobin levels in the Chinese T2DM population receiving 50/50 mg, 100/50 mg, and 100/100 mg PB201 twice daily for 24 weeks independent of co-administration of metformin. Overall, the proposed population PK/PD model quantitatively characterized the PK/PD properties of PB201 and the impact of covariates on its target populations, which allows the leveraging of extensive data in non-Chinese populations with the limited data in the Chinese T2DM population to successfully supported the waiver of the clinical phase II trial and facilitate the optimal dose regimen design of a pivotal phase III study of PB201 in China.

Model informed drug development: HSK21542 PBPK model supporting dose decisions in specific populations.

HKS21542, a highly selective activator of peripheral kappa opioid receptor agonists, plays a critical role in antinociception and itch inhibition during clinical development. Due to its indication population and elimination characteristics, it is imperative to evaluate the potential HSK21542 systemic exposure in individuals with renal impairment, hepatic impairment, the elderly, and the geriatric population. Here, a physiologically-based pharmacokinetic (PBPK) model for HSK21542 was developed based on in vitro metabolism and transport characteristics and in vivo elimination mechanism. Meanwhile, the potential systemic exposure of HSK21542 in specific populations was evaluated. The predicted results indicated increased systemic exposure in patients with renal impairment, hepatic impairment and in the elderly. Compared to the healthy volunteers aged 20-60 years, the AUC0-24h increased by 52 %-71 % in population with moderate to severe renal impairment, by 46 %-77 % in those with mild to severe hepatic impairment, and by 45 %-85 % in the elderly population aged 65-95-years. Conversely, the pediatric population demonstrated a potential decrease in systemic exposure, ranging from 20 % to 37 % in patients aged 0-17 years due to the physiological characteristics. Combined with the predicted results and the exposure-response relationship observed for HSK21542 and its analog (CR845), dosage regimens were designed for the target population with renal and hepatic impairment, supporting the successfully conducted trials (CTR20201702 and CTR20211940). Moreover, the observed exposure of HSK21542 in the elderly closely matched the predicted results within the same age group. Additionally, based on the predicted results, potential reductions in systemic exposure in pediatric patients should be carefully considered to avoid potential treatment failure in future clinical trials.