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Background: The advent of cystic fibrosis transmembrane conductance regulator protein (CFTR) modulators like ivacaftor have revolutionised the treatment of cystic fibrosis (CF). However, due to the plethora of variances in disease manifestations in CF, there are inherent challenges in unified responses under CFTR modulator treatment arising from variability in patient outcomes. The pharmacokinetic (PK) data available for ivacaftor-lumacaftor cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator drug combination is limited.Methods: Secondary objectives were to identify (1) patient characteristics and (2) the interactions between ivacaftor-lumacaftor responsible for interindividual variability (IIV).Results: Peak plasma concentrations (Cmax) of ivacaftor - lumacaftor were >10 fold lower than expected compared to label information. The one-way ANOVA indicated that the patient site had an effect on Cmax values of ivacaftor metabolites ivacaftor-M1, ivacaftor-M6, and lumacaftor (p < 0.001, p < 0.001, and p < 0.001, respectively). The Spearman’s rho test indicated that patient weight and age have an effect on the Cmax of lumacaftor (p = 0.003 and p < 0.001, respectively) and ivacaftor metabolite M1 (p = 0.020 and p < 0.001, respectively). Age (p < 0.001) was found to effect on Cmax of ivacaftor M6 and on Tmax of ivacaftor M1 (p = 0.026). A large impact of patient characteristics on the IIV of PK parameters Cmax and Tmax, was observed among the CF patients.Conclusion: Understanding the many sources of variability can help reduce this individual patient variability and ensure consistent patient outcomes.

Background: The advent of cystic fibrosis transmembrane conductance regulator protein (CFTR) modulators like ivacaftor have revolutionised the treatment of cystic fibrosis (CF). However, due to the plethora of variances in disease manifestations in CF, there are inherent challenges in unified responses under CFTR modulator treatment arising from variability in patient outcomes. The pharmacokinetic (PK) data available for ivacaftor-lumacaftor cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator drug combination is limited. Methods: Secondary objectives were to identify (1) patient characteristics and (2) the interactions between ivacaftor-lumacaftor responsible for interindividual variability (IIV). Results: Peak plasma concentrations (Cmax) of ivacaftor - lumacaftor were >10 fold lower than expected compared to label information. The one-way ANOVA indicated that the patient site had an effect on Cmax values of ivacaftor metabolites ivacaftor-M1, ivacaftor-M6, and lumacaftor (p < 0.001, p < 0.001, and p < 0.001, respectively). The Spearman's rho test indicated that patient weight and age have an effect on the Cmax of lumacaftor (p = 0.003 and p < 0.001, respectively) and ivacaftor metabolite M1 (p = 0.020 and p < 0.001, respectively). Age (p < 0.001) was found to effect on Cmax of ivacaftor M6 and on Tmax of ivacaftor M1 (p = 0.026). A large impact of patient characteristics on the IIV of PK parameters Cmax and Tmax, was observed among the CF patients. Conclusion: Understanding the many sources of variability can help reduce this individual patient variability and ensure consistent patient outcomes. [ABSTRACT FROM AUTHOR]

Introduction: There are several clinically significant outcomes of drug-drug interactions (DDIs) which have been classified as one of the serious forms of adverse drug reactions that may lead to prolongation of hospital stays along with severe cases of mortality and morbidities. It may cause due to the selection of two or more interacting drugs to be prescribed to patient. Objectives: Therefore it is indispensable to attain a collective level of therapeutic decision making so that any potential DDIs can be minimized that ultimately turn out to be safe and beneficial to patient. Study Design: The current study is based upon surveys to evaluate utilization of medications that have a narrow therapeutic range with high incidence to develop DDIs and to access the knowledge, attitude as well as practice of using such drug products in relation to these facts, though very few such studies have been identified, yet the relevant data is insufficient locally. The study design was selected to be qualitative and cross sectional. Period: January 2016 till August 2016 in Karachi, Pakistan. Settings: The questionnaire was well constructed for physicians, pharmacists as well as nurses who were selected as the participant of the study and a former consent from the respondents was obtained. Method: Coefficient of spearman correlation & Cronbach's α values were calculated in order to validate the questionnaire (α = 0.927 and p = 0.918). The information based on practice along with demographics of study participant was included as first segment of questionnaire while their knowledge regarding drug interactions was included as second part. Mean scores were calculated and responses were analysed by ANOVA in relation to the knowledge of members relating to drug interactions of vancomycin, warfarin and valproic acid. Results: Mean scores of perception were found in order of 1.590.16, 1.549.02 and 2.020.83 for physicians, pharmacists and nurses. No significant differences were observed between physicians and pharmacists cohorts in identifying the drug interactions whereas noteworthy variations were observed in the group of nurses (p < 0.05). Conclusion: Such investigations are vital in their prospect to highlight the importance for the design, implementation and monitoring of an effectual tool for the guidance of various healthcare members involved in identification and management of DDIs. Furthermore, results also signify the need of sophisticated support systems for valuable clinical judgments. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to examine the effect of ketoconazole, a potent cytochrome P450 (CYP) 3A4 and P-glycoprotein (P-gp) inhibitor, on teneligliptin pharmacokinetics and to evaluate the safety of combined administration of teneligliptin with ketoconazole. Methods: This open-label, fixed-sequence study was conducted in 16 healthy adult volunteers in Germany. On day 1, under fasting conditions, 20 mg of teneligliptin was administered to evaluate the pharmacokinetics of teneligliptin alone. For 3 days (days 8–10), 400 mg of ketoconazole was administered once daily. On day 11, teneligliptin 20 mg and ketoconazole 400 mg were concurrently administered, and for 2 days (days 12 and 13), ketoconazole was administered once daily. The pharmacokinetic parameters (C, Tmax, AUC, terminal t½, apparent total plasma clearance, and Vd during the terminal phase) of teneligliptin on days 1 and 11 were calculated. The safety profile was evaluated based on adverse events and clinical findings. To investigate the role of human P-gp in membrane permeation of teneligliptin, an in vitro study was performed to measure the transcellular transport of teneligliptin across monolayers of human P-gp-expressing cells and control cells. Results: For Cmax and AUC, the geometric least squares mean ratios (90% CIs) of teneligliptin with ketoconazole to teneligliptin alone were 1.37 (1.25– 1.50) and 1.49 (1.39–1.60), respectively. There was no change in t½ of the terminal elimination phase. In addition, the tolerability of teneligliptin coadministered with ketoconazole was acceptable. The in vitro study revealed corrected efflux ratios for teneligliptin of 6.81 and 5.27 at teneligliptin concentrations of 1 and 10 μM, respectively. Conclusions: Because the exposure to teneligliptin in combined administration with ketoconazole, a potent CYP3A4 and P-gp inhibitor, was less than twice that of administration of teneligliptin alone, it is suggested that combined administration of teneligliptin with drugs and foods that inhibit CYP3A4 should not cause a marked increase in exposure. The results of our in vitro study suggest that teneligliptin is a substrate of P-gp. [ABSTRACT FROM AUTHOR]

Introduction: Drug-Drug Interactions (DDIs) account for 6-30% of the adverse drug events, pose a significant risk to the patient's health outcome and they put an economic burden on the health care system. Polypharmacy significantly contributes to these interactions. This study was aimed at assessing the drug-drug interactions in the in-patients in the medicine department in a tertiary care hospital. Materials and Methods: The case records of 250 patients who were admitted in the medicine ward were analyzed regarding the demography of the patient, the prescription and the interaction details like the object drug, severity, management and the outcome. Results: The patients received drugs which ranged from 5 to 18. 66% of the patients had DDIs, with a majority being moderate in severity and occurring in the patients who received cardiovascular drugs. Age and gender did not have a significant effect on the drug- drug interactions. Conclusion: Most of the DDIs are preventable. The frequently occurring DDIs are seen between fluoroquinolones and oral anti-diabetics, iron and pantoprazole, aspirin and clopidogrel. [ABSTRACT FROM AUTHOR]

Aims Success of the quantitative prediction of drug–drug interactions via inhibition of CYP-mediated metabolism from the inhibitor concentration at the enzyme active site ([ I]) and the in vitro inhibition constant ( K i) is variable. The aim of this study was to examine the impact of the fraction of victim drug metabolized by a particular CYP ( f mCYP) and the inhibitor absorption rate constant ( k a) on prediction accuracy. Methods Drug–drug interaction studies involving inhibition of CYP2C9, CYP2D6 and CYP3A4 ( n = 115) were investigated. Data on f mCYP for the probe substrates of each enzyme and k a values for the inhibitors were incorporated into in vivo predictions, alone or in combination, using either the maximum hepatic input or the average systemic plasma concentration as a surrogate for [ I]. The success of prediction (AUC ratio predicted within twofold of in vivo value) was compared using nominal values of f mCY P = 1 and k a = 0.1 min−1. Results The incorporation of f mCYP values into in vivo predictions using the hepatic input plasma concentration resulted in 84% of studies within twofold of in vivo value. The effect of k a values alone significantly reduced the number of over-predictions for CYP2D6 and CYP3A4; however, less precision was observed compared with the f mCYP. The incorporation of both f mCYP and k a values resulted in 81% of studies within twofold of in vivo value. Conclusions The incorporation of substrate and inhibitor-related information, namely f mCYP and k a, markedly improved prediction of 115 interaction studies with CYP2C9, CYP2D6 and CYP3A4 in comparison with [ I]/ K i ratio alone. [ABSTRACT FROM AUTHOR]