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In healthcare situations, time-to-event (TTE) data are common outcomes. A parametric approach is often employed to handle TTE data because it is possible to easily visualize different scenarios via simulation. Not all pharmacometricians are familiar with the use of non-linear mixed effects models (NONMEMs) to deal with TTE data. Therefore, this tutorial simply explains how to analyze TTE data using NONMEM. We show how to write the code and evaluate the model. We also provide an example of a hands-on model for training.
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Background@#Pembrolizumab, an anti-cancer drug, is known to increase the activity of the immune system, leading to side effects called immune-related adverse events (irAE), including type 1 diabetes. This study analyzed the correlation between blood glucose level and pembrolizumab administration and investigated the covariates that affect those changes in cancer treatment. @*Methods@#The information of 133 adult cancer patients was obtained from the electronic medical record (EMR) to identify the changes in random blood glucose (RBG) levels during the pembrolizumab treatment. Subjects were classified into subgroups according to their baseline RBG level, history of diabetes, and the use of steroids, and linear regression analysis was conducted. In addition, a secondary analysis was performed within the group of subjects having a strong correlation to glycemic change, which was based on the Pearson correlation coefficient being less than -0.7 or greater than +0.7. Univariate and multivariate logistic regressions were conducted to identify the risk factors to glycemic increase. @*Results@#The RBG level tended to descend without significant differences in total patients during the administration period of pembrolizumab. Despite the insignificance, the logistic regression analysis presents that the odds ratios of baseline RBG less than 130 mg/dL, prophylactic steroid use, and higher dose of pembrolizumab per cycle (mg/kg/ cycle) were greater than 1. @*Conclusions@#Prophylactic administration of steroids and a higher dose of pembrolizumab per cycle may increase the blood glucose level as irAE in cancer patients with a strong tendency to glycemic change.
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Background@#Generally, pharmacokinetics (PK) models could be stratified into two models. The compartment PK model uses the concept of simple compartmentalization to describe complex bodies, and the physiologically based pharmacokinetic (PBPK) model describes the body using multi-compartment networking. Notwithstanding sharing a theoretical background in both models, there was still a lack of knowledge to enhance compatibility in both models. @*Objective@#This study aimed to evaluate the compatibility among PBPK, lumping model and compartment PK model with voriconazole PK case study. @*Methods@#The number of compartments and blood flow on each tissue in the PBPK model were modified using the lumping method, considering physiological similarities. The concentration-time profiles and area under the concentration-time curve (AUC) parameters were simulated at each model, assuming taken voriconazole oral 400 mg single dose. After that, those mentioned PK parameters were compared. @*Results@#The PK profiles and parameters of voriconazole in the three models were similar that proves their compatibility. The AUC of central compartment in the PBPK and lumping model was within a 2-fold range compared to those in the 2-compartment model. The AUC of non-eliminating tissues compartment in the PBPK model was similar to those in the lumping model. @*Conclusion@#Regarding the compatibility of the three PK models, the utilization of the lumping method was confirmed by suggesting its reliable PK parameters with PBPK and compartment PK models. Further case studies are recommended to confirm our findings.
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Background@#Pembrolizumab, an anti-cancer drug, is known to increase the activity of the immune system, leading to side effects called immune-related adverse events (irAE), including type 1 diabetes. This study analyzed the correlation between blood glucose level and pembrolizumab administration and investigated the covariates that affect those changes in cancer treatment. @*Methods@#The information of 133 adult cancer patients was obtained from the electronic medical record (EMR) to identify the changes in random blood glucose (RBG) levels during the pembrolizumab treatment. Subjects were classified into subgroups according to their baseline RBG level, history of diabetes, and the use of steroids, and linear regression analysis was conducted. In addition, a secondary analysis was performed within the group of subjects having a strong correlation to glycemic change, which was based on the Pearson correlation coefficient being less than -0.7 or greater than +0.7. Univariate and multivariate logistic regressions were conducted to identify the risk factors to glycemic increase. @*Results@#The RBG level tended to descend without significant differences in total patients during the administration period of pembrolizumab. Despite the insignificance, the logistic regression analysis presents that the odds ratios of baseline RBG less than 130 mg/dL, prophylactic steroid use, and higher dose of pembrolizumab per cycle (mg/kg/ cycle) were greater than 1. @*Conclusions@#Prophylactic administration of steroids and a higher dose of pembrolizumab per cycle may increase the blood glucose level as irAE in cancer patients with a strong tendency to glycemic change.
ABSTRACT
Background@#Generally, pharmacokinetics (PK) models could be stratified into two models. The compartment PK model uses the concept of simple compartmentalization to describe complex bodies, and the physiologically based pharmacokinetic (PBPK) model describes the body using multi-compartment networking. Notwithstanding sharing a theoretical background in both models, there was still a lack of knowledge to enhance compatibility in both models. @*Objective@#This study aimed to evaluate the compatibility among PBPK, lumping model and compartment PK model with voriconazole PK case study. @*Methods@#The number of compartments and blood flow on each tissue in the PBPK model were modified using the lumping method, considering physiological similarities. The concentration-time profiles and area under the concentration-time curve (AUC) parameters were simulated at each model, assuming taken voriconazole oral 400 mg single dose. After that, those mentioned PK parameters were compared. @*Results@#The PK profiles and parameters of voriconazole in the three models were similar that proves their compatibility. The AUC of central compartment in the PBPK and lumping model was within a 2-fold range compared to those in the 2-compartment model. The AUC of non-eliminating tissues compartment in the PBPK model was similar to those in the lumping model. @*Conclusion@#Regarding the compatibility of the three PK models, the utilization of the lumping method was confirmed by suggesting its reliable PK parameters with PBPK and compartment PK models. Further case studies are recommended to confirm our findings.
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Background@#The indication of denosumab for osteoporosis was expanded from second-line to first-line therapy in 2019. The aim of this study was to evaluate the efficacy of denosumab as both first- and second-line therapy in postmenopausal women with osteoporosis and osteopenia with risk factors by using the Fracture Risk Assessment Tool (FRAX). @*Methods@#We conducted a medication use evaluation of denosumab in 98 patients who had been treated three or more times for osteoporosis or osteopenia at Chungnam National University Hospital from July 1st , 2017 to January 31st , 2020. Risk factors were identified using quantitative Ngram analyses of FRAX estimations. Patient information, including menopause status and results of bone mineral density tests (Tscore), was obtained from electronic medical records. @*Results@#Age, body mass index (BMI), prior medication use, and T-score were identified as risk factors and were included as variables in the evaluation of denosumab use. Since no significant differences were detected between groups, denosumab is likely effective regardless of age or BMI. In addition, no significant difference was detected in T-scores following denosumab treatment, between groups who took bisphosphonates and selective estrogen receptor modulators (SERMs) with denosumab as first-line therapy for postmenopausal osteoporosis. Denosumab may, therefore, be effective as second-line therapy. @*Conclusion@#Efficacy of denosumab was evaluated in postmenopausal women with osteoporosis.Denosumab may be used as first- and second-line therapy regardless of age, BMI, and prior use of bisphosphonates and SERMs.
ABSTRACT
Background@#The indication of denosumab for osteoporosis was expanded from second-line to first-line therapy in 2019. The aim of this study was to evaluate the efficacy of denosumab as both first- and second-line therapy in postmenopausal women with osteoporosis and osteopenia with risk factors by using the Fracture Risk Assessment Tool (FRAX). @*Methods@#We conducted a medication use evaluation of denosumab in 98 patients who had been treated three or more times for osteoporosis or osteopenia at Chungnam National University Hospital from July 1st , 2017 to January 31st , 2020. Risk factors were identified using quantitative Ngram analyses of FRAX estimations. Patient information, including menopause status and results of bone mineral density tests (Tscore), was obtained from electronic medical records. @*Results@#Age, body mass index (BMI), prior medication use, and T-score were identified as risk factors and were included as variables in the evaluation of denosumab use. Since no significant differences were detected between groups, denosumab is likely effective regardless of age or BMI. In addition, no significant difference was detected in T-scores following denosumab treatment, between groups who took bisphosphonates and selective estrogen receptor modulators (SERMs) with denosumab as first-line therapy for postmenopausal osteoporosis. Denosumab may, therefore, be effective as second-line therapy. @*Conclusion@#Efficacy of denosumab was evaluated in postmenopausal women with osteoporosis.Denosumab may be used as first- and second-line therapy regardless of age, BMI, and prior use of bisphosphonates and SERMs.
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Alterations in sulfur amino acid metabolism are associated with an increased risk of a number of common late-life diseases, which raises the possibility that metabolism of sulfur amino acids may change with age. The present study was conducted to understand the age-related changes in hepatic metabolism of sulfur amino acids in 2-, 6-, 18- and 30-month-old male C57BL/6 mice. For this purpose, metabolite profiling of sulfur amino acids from methionine to taurine or glutathione (GSH) was performed. The levels of sulfur amino acids and their metabolites were not significantly different among 2-, 6- and 18-month-old mice, except for plasma GSH and hepatic homocysteine. Plasma total GSH and hepatic total homocysteine levels were significantly higher in 2-month-old mice than those in the other age groups. In contrast, 30-month-old mice exhibited increased hepatic methionine and cysteine, compared with all other groups, but decreased hepatic S-adenosylmethionine (SAM), S-adenosylhomocysteine and homocysteine, relative to 2-month-old mice. No differences in hepatic reduced GSH, GSH disulfide, or taurine were observed. The hepatic changes in homocysteine and cysteine may be attributed to upregulation of cystathionine β-synthase and down-regulation of γ-glutamylcysteine ligase in the aged mice. The elevation of hepatic cysteine levels may be involved in the maintenance of hepatic GSH levels. The opposite changes of methionine and SAM suggest that the regulatory role of SAM in hepatic sulfur amino acid metabolism may be impaired in 30-month-old mice.
Subject(s)
Animals , Child, Preschool , Humans , Infant , Male , Mice , Aging , Amino Acids, Sulfur , Cystathionine , Cysteine , Down-Regulation , Glutathione , Homocysteine , Metabolism , Metabolomics , Methionine , Plasma , S-Adenosylhomocysteine , S-Adenosylmethionine , Sulfur , Taurine , Up-RegulationABSTRACT
As the population ages, the life of women after menopause becomes much longer than the past, and the quality of life of old age becomes increasingly principal issue. There is a period that women experience the physical symptoms of menopause, although there are differences in degree, and the management of this period is a suitable time for women to improve their quality of life. According to the menopausal hormone therapy (MHT) and Timing Hypothesis, which has been proven in the Kronos Early Estrogen Prevention Study (KEEPS) and the Early vs Late Intervention Trial with Estradiol (ELITE) study, a relatively young woman before and after menopause can benefit from long-term beneficial effects such as prevention of osteoporosis and cardiovascular disease by early initiation of hormone therapy to alleviate menopausal symptoms. MHT should be considered for all women in healthy (without other important diseases) menopausal years, expecting to improve their quality of life through symptom relief in menopausal women and, in the long term, to prevent cardiovascular disease and osteoporosis. When applying hormone therapy to individuals, it is necessary to establish various treatment strategies according to the menopausal symptoms of individual patients (individualization of treatment) and judge the suitability of clinical application.
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OBJECTIVE: To develop a population pharmacokinetics (PK)/pharmacodynamics (PD) model for alcohol in healthy volunteers and to elucidate individual characteristics to affects alcohol's PK or PD including dissolved oxygen. METHODS: Following multiple intakes of total 540 mL alcohol (19.42 v/v%) to healthy volunteer, blood alcohol concentration was measured using a Breathe alcohol analyser (Lion SD-400 Alcolmeter®). A sequential population PK/PD modeling was performed using NONMEM (ver 7.3). RESULTS: Eighteen healthy volunteer were included in the study. PK model of alcohol was well explained by one-compartment model with first-order absorption and Michaelis-Menten elimination kinetics. K(a), V/F, V(max), K(m) is 8.1 hr⁻¹, 73.7 L, 9.65 g/hr, 0.041 g/L, respectively. Covariate analysis revealed that gender significantly influenced V(max) (Male vs Female, 9.65 g/hr vs 7.38 g/hr). PD model of temporary systolic blood pressure decreasing effect of alcohol was explained by biophase model with inhibitory E(max) model. K(e0), I(max), E(0), IC(50) were 0.23 hr⁻¹, 44.9 mmHg, 138 mmHg, 0.693 g/L, respectively. CONCLUSION: Model evaluation results suggested that this PK/PD model was robust and has good precision.