Prediction of drug clearance in a smoking population: modeling the impact of variable cigarette consumption on the induction of CYP1A2

CYP1A2 contributes to the metabolism of mefloquine: Exploration using in vitro metabolism and physiologically-based pharmacokinetic modelling

Mefloquine is an antimalarial drug routinely used for prophylaxis and in the treatment of malaria. Approximately 50% of mefloquine metabolism, both in vitro and in vivo, is mediated by CYP3A4 with the remaining contributions by other CYP450 isoforms unaccounted for. This study aimed to determine the contribution of CYP450s to mefloquine metabolism and incorporate this knowledge into a physiologically-based pharmacokinetic model. The data in human liver microsomes demonstrated the involvement of CYP3A4/5 as well as the previously unreported contribution of CYP1A2 to mefloquine metabolism. The fraction metabolized by CYP1A2 (fm,CYP1A2) was estimated to be at least 50% using chemical inhibitors and pooled human liver microsomes and confirmed using recombinant human CYP450 enzymes. A physiologically-based pharmacokinetic model built in Simcyp using the fm,CYP values recaptured observed clinical pharmacokinetic data-71 % of the simulated area under the curve (AUC) values were within 1.25-fold of the observed clinical data, and all simulated AUC values were within 2-fold of observed data. Simulated mefloquine exposures increased by 88% when an interaction with fluvoxamine, a CYP1A2 inhibitor was modeled. Modeling showed that heavy smoking, and subsequent induction of CYP1A2, had a notable effect on mefloquine exposure. CYP1A2 genotype status also influenced mefloquine exposure with a predicted AUC ratio of 1.68 in a simulated population of CYP1A2 poor metabolizers. The involvement of CYP1A2 in mefloquine metabolism suggests a previously unreported drug-drug interaction risk. Looking forward, the analysis here suggests the clinical exploration of the interaction between mefloquine and CYP1A2. SIGNIFICANCE STATEMENT: Despite the widespread use of mefloquine in malaria prophylaxis and treatment, its metabolism is not completely characterized. This has implications for understanding and predicting drug-drug interactions involving mefloquine. Here, we identify CYP1A2 as a key enzyme involved in mefloquine metabolism and use physiologically-based pharmacokinetic modeling to demonstrate the contribution of this route to interactions with mefloquine. The in vitro data and revised physiologically-based pharmacokinetic model are important starting points for future exploration of this pathway using clinical data.

Virtual twins for model-informed precision dosing of clozapine in patients with treatment-resistant schizophrenia

Model-informed precision dosing using virtual twins (MIPD-VTs) is an emerging strategy to predict target drug concentrations in clinical practice. Using a high virtualization MIPD-VT approach (Simcyp version 21), we predicted the steady-state clozapine concentration and clozapine dosage range to achieve a target concentration of 350 to 600 ng/mL in hospitalized patients with treatment-resistant schizophrenia (N = 11). We confirmed that high virtualization MIPD-VT can reasonably predict clozapine concentrations in individual patients with a coefficient of determination (R2 ) ranging between 0.29 and 0.60. Importantly, our approach predicted the final dosage range to achieve the desired target clozapine concentrations in 73% of patients. In two thirds of patients treated with fluvoxamine augmentation, steady-state clozapine concentrations were overpredicted two to four-fold. This work supports the application of a high virtualization MIPD-VT approach to inform the titration of clozapine doses in clinical practice. However, refinement is required to improve the prediction of pharmacokinetic drug-drug interactions, particularly with fluvoxamine augmentation.

Seeing what is behind the smokescreen: A systematic review of methodological aspects of smoking interaction studies over the last three decades and implications for future clinical trials

Smoking drug interaction studies represent a common approach for the clinical investigation of CYP1A2 induction. Despite this important role, they remain an "orphan topic" in the existing regulatory framework of drug interaction studies, and important methodological aspects remain unaddressed. The University of Washington Drug Interaction Database (DIDB) was used to systematically review the published literature on dedicated smoking pharmacokinetic interaction studies in healthy subjects (1990 to 2021, inclusive). Various methodological aspects of identified studies were reviewed. A total of 51 studies met all inclusion criteria and were included in the analysis. Our review revealed that methods applied in smoking interaction studies are heterogeneous and often fall short of established methodological standards of other interaction trials. Methodological deficiencies included incomplete description of study populations, poor definition and lack of objective confirmation of smoker and nonsmoker characteristics, under-representation of female subjects, small sample sizes, frequent lack of statistical sample size planning, frequent lack of use of existing markers of nicotine exposure and CYP1A2 activity measurements, and frequent lack of control of extrinsic CYP1A2 inducing or inhibiting factors. The frequent quality issues in the assessment and reporting of smoking interaction trials identified in this review call for a concerted effort in this area, if the results of these studies are meant to be followed by actionable decisions on dose optimization, when needed, for the effects of smoking on CYP1A2 victim drugs in smokers.

Delineating gene-environment effects using virtual twins of patients treated with clozapine

Studies that focus on individual covariates, while ignoring their interactions, may not be adequate for model-informed precision dosing (MIPD) in any given patient. Genetic variations that influence protein synthesis should be studied in conjunction with environmental covariates, such as cigarette smoking. The aim of this study was to build virtual twins (VTs) of real patients receiving clozapine with interacting covariates related to genetics and environment and to delineate the impact of interacting covariates on predicted clozapine plasma concentrations. Clozapine-treated patients with schizophrenia (N = 42) with observed clozapine plasma concentrations, demographic, environmental, and genotype data were used to construct VTs in Simcyp. The effect of increased covariate virtualization was assessed by performing simulations under three conditions: "low" (demographic), "medium" (demographic and environmental interaction), and "high" (demographic and environmental/genotype interaction) covariate virtualization. Increasing covariate virtualization with interaction improved the coefficient of variation (R² ) from 0.07 in the low model to 0.391 and 0.368 in the medium and high models, respectively. Whereas R² was similar between the medium and high models, the high covariate virtualization model had improved accuracy, with systematic bias of predicted clozapine plasma concentration improving from -138.48 ng/ml to -74.65 ng/ml. A high level of covariate virtualization (demographic, environmental, and genotype) may be required for MIPD using VTs.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

Understanding Interindividual Variability in the Drug Interaction of a Highly Extracted CYP1A2 Substrate Tizanidine: Application of a Permeability-Limited Multicompartment Liver Model in a Population Based Physiologically Based Pharmacokinetic Framework

Tizanidine, a centrally acting skeletal muscle relaxant, is predominantly metabolized by CYP1A2 and undergoes extensive hepatic first-pass metabolism after oral administration. As a highly extracted drug, the systemic exposure to tizanidine exhibits considerable interindividual variability and is altered substantially when coadministered with CYP1A2 inhibitors or inducers. The aim of the current study was to compare the performance of a permeability-limited multicompartment liver (PerMCL) model, which operates as an approximation of the dispersion model, and the well stirred model (WSM) for predicting tizanidine drug-drug interactions (DDIs). Physiologically based pharmacokinetic models were developed for tizanidine, incorporating the PerMCL model and the WSM, respectively, to simulate the interaction of tizanidine with a range of CYP1A2 inhibitors and inducers. Whereas the WSM showed a tendency to underpredict the fold change of tizanidine area under the plasma concentration-time curve (AUC ratio) in the presence of perpetrators, the use of PerMCL model increased precision (absolute average-fold error: 1.32-1.42 versus 1.58) and decreased bias (average-fold error: 0.97-1.25 versus 0.63) for the predictions of mean AUC ratios as compared with the WSM. The PerMCL model captured the observed range of individual AUC ratios of tizanidine as well as the correlation between individual AUC ratios and CYP1A2 activities without interactions, whereas the WSM was not able to capture these. The results demonstrate the advantage of using the PerMCL model over the WSM in predicting the magnitude and interindividual variability of DDIs for a highly extracted sensitive substrate tizanidine. SIGNIFICANCE STATEMENT: This study demonstrates the advantages of the PerMCL model, which operates as an approximation of the dispersion model, in mitigating the tendency of the WSM to underpredict the magnitude and variability of DDIs of a highly extracted CYP1A2 substrate tizanidine when it is administered with CYP1A2 inhibitors or inducers. The physiologically based pharmacokinetic modeling approach described herein is valuable to the understanding of drug interactions of highly extracted substrates and the source of its interindividual variability.

Impact of aerosols on liver xenobiotic metabolism: A comparison of two methods of exposure

Assessment of aerosols effects on liver CYP function generally involves aqueous fractions (AF). Although easy and efficient, this method has not been optimized recently or comparatively assessed against other aerosol exposure methods. Here, we comparatively evaluated the effects of the AFs of cigarette smoke (CS) and Tobacco Heating System (THS) aerosols on CYP activity in liver spheroids. We then used these data to develop a physiological aerosol exposure system combining a multi-organs-on-a-chip, 3D lung tissues, liver spheroids, and a direct aerosol exposure system. Liver spheroids incubated with CS AF showed a dose-dependent increase in CYP1A1/1B1, CYP1A2, and CYP2B6 activity and a dose-dependent decrease in CYP2C9, CYP2D6, and CYP3A4 activity relative to untreated tissues. In our physiological exposure system, repeated CS exposure of the bronchial tissues also caused CYP1A1/1B1 and CYP1A2 induction in the bronchial tissues and liver spheroids; but the spheroids showed an increase in CYP3A4 activity and no effect on CYP2C9 or CYP2D6 activity relative to air-exposed tissues, which resembles the results reported in smokers. THS aerosol did not affect CYP activity in bronchial or liver tissues, even at 4 times higher concentrations than CS. In conclusion, our system allows us to physiologically test the effects of CS or other aerosols on lung and liver tissues cultured in the same chip circuit, thus delivering more in vivo like data.

Population pharmacokinetic and exposure-response analysis of apremilast in Japanese subjects with moderate to severe psoriasis

Apremilast is an orally available phosphodiesterase 4 inhibitor used for the treatment of moderate to severe psoriasis. The aims of this analysis were to develop a population pharmacokinetic (PPK) model of apremilast based on observed data from phase 1 studies combined with clinical trial data from subjects with moderate to severe psoriasis, and to develop exposure–response (E‐R) models to determine whether Japanese subjects with moderate to severe psoriasis achieve response to apremilast treatment similar to that observed in non‐Japanese, predominantly Caucasian subjects with moderate to severe psoriasis. The PPK model demonstrated that apremilast plasma concentrations and overall apparent clearance rate were comparable between the Japanese and Caucasian subgroups. The E‐R analyses of ≥75% or ≥50% improvement from baseline in Psoriasis Area and Severity Index score and achievement of static Physician Global Assessment score of 0 (clear) or 1 (almost clear) at week 16 indicated that apremilast treatment in Japanese subjects approached the maximal effect with response rates comparable to those in predominantly Caucasian subjects. Overall, the analyses confirm that the approved apremilast 30 mg b.i.d. dose is appropriate for Japanese subjects with moderate to severe psoriasis, with an efficacy profile similar to that previously observed in Caucasian subjects.

Causal relationship from coffee consumption to diseases and mortality: a review of observational and Mendelian randomization studies including cardiometabolic diseases, cancer, gallstones and other diseases

PURPOSE

High coffee consumption is associated with low risk of mortality and morbidity, but the causality remains unclear. This review aims to discuss findings from observational studies on coffee consumption in context of Mendelian randomization studies.

METHODS

The PubMed database was searched for all Mendelian randomization studies on coffee consumption and corresponding observational studies.

RESULTS

High coffee consumption is associated with low risk of all-cause and cardiovascular mortality in observational studies (HRs of 0.85-0.90 vs. no/low consumers), with no support of causality in Mendelian randomization studies. Moderate/high consumption is associated with low risk of cardiometabolic diseases, including ischemic heart disease (HRs of 0.85-0.90 vs. no/low consumption), stroke (HRs of approximately 0.80 vs. no/low consumption), type 2 diabetes (HRs of approximately 0.70 vs. no/low consumption) and obesity in observational studies, but not in Mendelian randomization studies. High consumption is associated with low risk of endometrial cancer and melanoma and high risk of lung cancer in observational studies, but with high risk of colorectal cancer in Mendelian randomization studies. In observational and Mendelian randomization studies, high coffee consumption is associated with low risk of gallstones (HRs of 0.55-0.70 for high vs. no/low self-reported and 0.81 (0.69-0.96) for highest vs. lowest genetic consumption).

CONCLUSION

High coffee consumption is associated with low risk of mortality, cardiometabolic diseases, some cancers and gallstones in observational studies, with no evidence to support causality from Mendelian randomization studies for most diseases except gallstones.

Loxapine in patient with clozapine-resistant psychosis

Clozapine is recognized as the drug of choice for treatment-refractory schizophrenia, but use may be limited because of strict monitoring requirements and adverse effects including severe neutropenia, seizures, and myocarditis. Loxapine is a first-generation antipsychotic with similarities to clozapine in both structure and receptor binding. This case describes a 57-year-old male with a history of severe paranoid schizophrenia despite treatment with clozapine and other psychotropic agents, who experienced clinical improvement after a cross titration from clozapine to loxapine. Loxapine may be a reasonable alternative in patients with treatment-refractory schizophrenia who do not tolerate or respond to clozapine.

Sex-dependent dynamics of metabolism in primary mouse hepatocytes

The liver is one of the most sexually dimorphic organs. The hepatic metabolic pathways that are subject to sexual dimorphism include xenobiotic, amino acid and lipid metabolism. Non-alcoholic fatty liver disease and hepatocellular carcinoma are among diseases with sex-dependent prevalence, progression and outcome. Although male and female livers differ in their abilities to metabolize foreign compounds, including drugs, sex-dependent treatment and pharmacological dynamics are rarely applied in all relevant cases. Therefore, it is important to consider hepatic sexual dimorphism when developing new treatment strategies and to understand the underlying mechanisms in model systems. We isolated primary hepatocytes from male and female C57BL6/N mice and examined the sex-dependent transcriptome, proteome and extracellular metabolome parameters in the course of culturing them for 96 h. The sex-specific gene expression of the general xenobiotic pathway altered and the female-specific expression of Cyp2b13 and Cyp2b9 was significantly reduced during culture. Sex-dependent differences of several signaling pathways increased, including genes related to serotonin and melatonin degradation. Furthermore, the ratios of male and female gene expression were inversed for other pathways, such as amino acid degradation, beta-oxidation, androgen signaling and hepatic steatosis. Because the primary hepatocytes were cultivated without the influence of known regulators of sexual dimorphism, these results suggest currently unknown modulatory mechanisms of sexual dimorphism in vitro. The large sex-dependent differences in the regulation and dynamics of drug metabolism observed during cultivation can have an immense influence on the evaluation of pharmacodynamic processes when conducting initial preclinical trials to investigate potential new drugs.

Using physiologically-based pharmacokinetic modeling for predicting the effects of hepatic impairment on the pharmacokinetics of olanzapine and samidorphan given as a combination tablet

A combination of olanzapine and samidorphan (OLZ/SAM) was recently approved by the US Food and Drug Administration for treatment of patients with schizophrenia or bipolar I disorder. The effects of moderate hepatic impairment on the pharmacokinetics (PKs) of olanzapine and samidorphan after a single dose of OLZ/SAM were characterized in a clinical study. Physiologically-based pharmacokinetic (PBPK) modeling was used to extend the clinical findings to predict the effects of varying degrees of hepatic impairment on the PKs of olanzapine and samidorphan. A previously developed PBPK model for OLZ/SAM was refined to recover the observed pharmacokinetic differences between individuals with moderate hepatic impairment and healthy controls. The optimized model was applied to predict changes in olanzapine and samidorphan PKs after multiple once-daily doses of OLZ/SAM in subjects with mild, moderate, and severe hepatic impairment relative to healthy controls. Modifications to model parameters, including absorption rate constant and fraction unbound to plasma protein, were made to recover the observed change in the PKs of olanzapine and samidorphan in individuals with moderate hepatic impairment. In applying the optimized model, mild, moderate, and severe hepatic impairment were predicted to increase steady-state total systemic exposures by 1.1-, 1.5-, and 1.6-fold, respectively, for olanzapine, and by 1.2-, 1.9-, and 2.3-fold, respectively, for samidorphan. PBPK modeling allowed for prediction of untested clinical scenarios of varying degrees of hepatic impairment in lieu of additional clinical studies.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs-Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug’s pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients’ drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior—both clinically relevant in psychiatry—that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs—Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug’s pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients’ drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior—both clinically relevant in psychiatry—that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Therapeutic Drug Monitoring of Second- and Third-Generation Antipsychotic Drugs-Influence of Smoking Behavior and Inflammation on Pharmacokinetics

Both inflammation and smoking can influence a drug's pharmacokinetic properties, i.e., its liberation, absorption, distribution, metabolism, and elimination. Depending on, e.g., pharmacogenetics, these changes may alter treatment response or cause serious adverse drug reactions and are thus of clinical relevance. Antipsychotic drugs, used in the treatment of psychosis and schizophrenia, should be closely monitored due to multiple factors (e.g., the narrow therapeutic window of certain psychotropic drugs, the chronicity of most mental illnesses, and the common occurrence of polypharmacotherapy in psychiatry). Therapeutic drug monitoring (TDM) aids with drug titration by enabling the quantification of patients' drug levels. Recommendations on the use of TDM during treatment with psychotropic drugs are presented in the Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology; however, data on antipsychotic drug levels during inflammation or after changes in smoking behavior-both clinically relevant in psychiatry-that can aid clinical decision making are sparse. The following narrative review provides an overview of relevant literature regarding TDM in psychiatry, particularly in the context of second- and third-generation antipsychotic drugs, inflammation, and smoking behavior. It aims to spread awareness regarding TDM (most pronouncedly of clozapine and olanzapine) as a tool to optimize drug safety and provide patient-tailored treatment.

Associations of coffee and tea consumption with lung cancer risk

Associations of coffee and tea consumption with lung cancer risk have been inconsistent, and most lung cancer cases investigated were smokers. Included in this study were over 1.1 million participants from 17 prospective cohorts. Cox regression analyses were conducted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Potential effect modifications by sex, smoking, race, cancer subtype and coffee type were assessed. After a median 8.6 years of follow-up, 20 280 incident lung cancer cases were identified. Compared with noncoffee and nontea consumption, HRs (95% CIs) associated with exclusive coffee drinkers (≥2 cups/d) among current, former and never smokers were 1.30 (1.15-1.47), 1.49 (1.27-1.74) and 1.35 (1.15-1.58), respectively. Corresponding HRs for exclusive tea drinkers (≥2 cups/d) were 1.16 (1.02-1.32), 1.10 (0.92-1.32) and 1.37 (1.17-1.61). In general, the coffee and tea associations did not differ significantly by sex, race or histologic subtype. Our findings suggest that higher consumption of coffee or tea is associated with increased lung cancer risk. However, these findings should not be assumed to be causal because of the likelihood of residual confounding by smoking, including passive smoking, and change of coffee and tea consumption after study enrolment.

Cigarette smoking enhances the metabolic activation of the polycyclic aromatic hydrocarbon phenanthrene in humans

Although it is well established that human cytochrome P450 1 family enzymes are induced by cigarette smoking through activation of the Ah receptor, it is not known whether this leads to increased metabolic activation or detoxification of carcinogenic polycyclic aromatic hydrocarbons (PAH), which are present in cigarette smoke and the general environment. We gave oral doses of deuterated phenanthrene ([D10]Phe), a non-carcinogenic surrogate of carcinogenic PAH such as benzo[a]pyrene, to smokers (N = 170, 1 or 10 μg doses) and non-smokers (N = 57, 1 μg dose). Bioactivation products (dihydrodiol and tetraol) and detoxification products (phenols) of [D10]Phe were determined in 6-h urine to obtain a comprehensive metabolic profile. Cigarette smoking increased the bioactivation of [D10]Phe and decreased its detoxification resulting in significantly different metabolic patterns between smokers and non-smokers (P < 0.01), consistent with increased cancer risk in smokers. The Phe bioactivation ratios ([D10]PheT/total [D9]OHPhe) were significantly higher (2.3 (P < 0.01) to 4.8 (P < 0.001) fold) in smokers than non-smokers. With solid human in vivo evidence, our results for the first time demonstrate that cigarette smoking enhances the metabolic activation of Phe, structurally representative of carcinogenic PAH, in humans, strongly supporting their causal role in cancers caused by smoking. The results suggest potential new methods for identifying smokers who could be at particularly high risk for cancer.

Physiologically based pharmacokinetic modeling of altered tizanidine systemic exposure by CYP1A2 modulation: Impact of drug-drug interactions and cigarette consumption

Tizanidine is an alpha2-adrenergic agonist, used to treat spasticity associated with multiple sclerosis and spinal injury. Tizanidine is primarily metabolized by CYP1A2 and is considered a sensitive index substrate for this enzyme. The physiologically based pharmacokinetic (PBPK) modeling platform Simcyp® was used to evaluate the impact of CYP1A2 modulation on tizanidine exposure through drug-drug interactions (DDIs) and host-dependent habits (cigarette smoking). A PBPK model was developed to predict tizanidine disposition in healthy volunteers following oral administration. The model was verified based on agreement between model-simulated and clinically observed systemic exposure metrics (C_max, AUC). The model was then used to carry-out DDI simulations to predict alterations in tizanidine systemic exposure when co-administered with various CYP1A2 perpetrators including competitive inhibitors (fluvoxamine, ciprofloxacin), a mechanism-based inhibitor (rofecoxib), and an inducer (rifampin). Additional simulations were performed to evaluate the impact of cigarette smoking on systemic exposure. Under each scenario, the PBPK model was able to capture the observed fold changes in tizanidine C_max and AUC of tizanidine when coadministered with CYP1A2 inhibitors or inducers. These results add to the available research findings in the literature on PBPK predictions of drug-drug interactions and illustrate the potential application in drug development, specifically to support product labeling.

Coffee consumption and risk of bladder cancer: a pooled analysis of 501,604 participants from 12 cohort studies in the BLadder Cancer Epidemiology and Nutritional Determinants (BLEND) international study

Recent epidemiological studies have shown varying associations between coffee consumption and bladder cancer (BC). This research aims to elucidate the association between coffee consumption and BC risk by bringing together worldwide cohort studies on this topic. Coffee consumption in relation to BC risk was examined by pooling individual data from 12 cohort studies, comprising of 2601 cases out of 501,604 participants. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs), were obtained using multilevel Weibull regression models. Furthermore, dose-response relationships were examined using generalized least squares regression models. The association between coffee consumption and BC risk showed interaction with sex (P-interaction < 0.001) and smoking (P-interaction = 0.001). Therefore, analyses were stratified by sex and smoking. After adjustment for potential confounders, an increased BC risk was shown for high (> 500 ml/day, equivalent to > 4 cups/day) coffee consumption compared to never consumers among male smokers (current smokers: HR = 1.75, 95% CI 1.27-2.42, P-trend = 0.002; former smokers: HR = 1.44, 95% CI 1.12-1.85, P-trend = 0.001). In addition, dose-response analyses, in male smokers also showed an increased BC risk for coffee consumption of more than 500 ml/day (4 cups/day), with the risk of one cup (125 ml) increment as 1.07 (95% CI 1.06-1.08). This research suggests that positive associations between coffee consumption and BC among male smokers but not never smokers and females. The inconsistent results between sexes and the absence of an association in never smokers indicate that the associations found among male smokers is unlikely to be causal and is possibly caused by residual confounding of smoking.

Pharmacokinetic interactions between clozapine and sertraline in smokers and non-smokers

Clozapine is an effective antipsychotic drug for treatment-resistant schizophrenia. Sertraline is a widely prescribed antidepressant and often concomitantly applied to address negative symptoms or depression. However, data on interactions between clozapine and sertraline are inconsistent. The aim of our study was to evaluate pharmacokinetic interactions between clozapine and sertraline analysing a therapeutic drug monitoring database of 1644 clozapine-medicated patients. We compared four groups: non-smokers (n = 250) and smokers (n = 326) with co-medication without known effects on cytochrome P450 and without sertraline, and non-smokers (n = 18) and smokers (n = 17) with sertraline co-medication. Measured and dose-corrected concentrations (C/D) of clozapine were compared between the groups using non-parametrical tests with a significance level of 0.05. Post hoc analyses included pairwise comparisons to account for smoking status. Although we detected significant differences for clozapine levels and C/D values between study groups (P < .001 for Kruskal-Wallis test in both cases), post hoc analyses revealed no differences for concentrations and C/D values of clozapine (P > .05 for Mann-Whitney U test in both cases). A negative correlation between the sertraline dose and the clozapine concentration was found in non-smokers (Spearman's rank correlation, rs = -0.535, P = .048). A potential pharmacokinetic interaction between clozapine and a standard therapeutic sertraline dose seems to be of minor clinical importance.

Physiologically-Based Pharmacokinetic Modeling for Predicting Drug Interactions of a Combination of Olanzapine and Samidorphan

A combination of the antipsychotic olanzapine and the opioid receptor antagonist samidorphan (OLZ/SAM) is intended to provide the antipsychotic efficacy of olanzapine while mitigating olanzapine-associated weight gain. As cytochrome P450 (CYP) 1A2 and CYP3A4 are the major enzymes involved in metabolism of olanzapine and samidorphan, respectively, physiologically-based pharmacokinetic (PBPK) modeling was applied to predict any drug-drug interaction (DDI) potential between olanzapine and samidorphan or between OLZ/SAM and CYP3A4/CYP1A2 inhibitors/inducers. A PBPK model for OLZ/SAM was developed and validated by comparing model-simulated data with observed clinical study data. Based on model-based simulations, no DDI between olanzapine and samidorphan is expected when administered as OLZ/SAM. CYP3A4 inhibition is predicted to have a weak effect on samidorphan exposure and negligible effect on olanzapine exposure. CYP3A4 induction is predicted to reduce both samidorphan and olanzapine exposure. CYP1A2 inhibition or induction is predicted to increase or decrease, respectively, olanzapine exposure only.

Effect of fluvoxamine augmentation and smoking on clozapine serum concentrations

BACKGROUND

Clozapine (CLZ) is metabolized via cytochrome P450 CYP1A2 to N-desmethylclozapine (NCLZ). Smoking induces CYP1A2 thereby increasing clozapine metabolism whereas fluvoxamine inhibits CYP1A2. Studies suggest that the beneficial effect of fluvoxamine augmentation in raising serum clozapine concentrations also occurs when serum concentrations are low due to smoking. Yet, little is known about the influence of fluvoxamine augmentation on clozapine serum concentrations in smoking versus non-smoking patients.

METHODS

A TDM database was analyzed. Serum concentrations of CLZ, NCLZ, dose-adjusted serum concentrations (C/D) and metabolite-to-parent ratios (MPR) were compared using non-parametrical tests in four groups: clozapine-monotherapy in non-smokers (V_NS, n = 28) and smokers (V_S, n = 43); combined treatment with clozapine and fluvoxamine in non-smokers (V_NS+F, n = 11) and smokers (V_S+F, n = 43).

RESULTS

The CLZ monotherapy smoking group showed lower values of C/D CLZ of -38.6% (p < 0.001), C/D NCLZ -35.6% (p < 0.001) and a higher MPR (p = 0.021) than in the non-smoking group. The combination of CLZ and fluvoxamine in non-smoking patients led to higher C/D values: C/D CLZ +117.9% (p < 0.001), C/D NCLZ +60.8% (p = 0.029) while the MPR did not differ between groups (p = 0.089). Changes were comparable to fluvoxamine augmentation in the smoking group with increased C/D CLZ of +120.1% (p < 0.001), C/D NCLZ of +85.8% (p < 0.001) and lower MPR (p = 0.006).

CONCLUSIONS

Smoking in clozapine monotherapy reduced median dose-adjusted serum concentrations more than a third. Combined treatment with fluvoxamine and clozapine led to higher median C/D values in both, smokers and non-smokers. The opposing effects of CYP1A2 induction by smoking and inhibition by fluvoxamine on clozapine serum concentrations balanced out.

Physiologically-Based Pharmacokinetic Modeling for the Prediction of CYP2D6-Mediated Gene-Drug-Drug Interactions

The aim of this work was to predict the extent of Cytochrome P450 2D6 (CYP2D6)‐mediated drug–drug interactions (DDIs) in different CYP2D6 genotypes using physiologically‐based pharmacokinetic (PBPK) modeling. Following the development of a new duloxetine model and optimization of a paroxetine model, the effect of genetic polymorphisms on CYP2D6‐mediated intrinsic clearances of dextromethorphan, duloxetine, and paroxetine was estimated from rich pharmacokinetic profiles in activity score (AS)1 and AS2 subjects. We obtained good predictions for the dextromethorphan–duloxetine interaction (Ratio of predicted over observed area under the curve (AUC) ratio (R_pred/obs) 1.38–1.43). Similarly, the effect of genotype was well predicted, with an increase of area under the curve ratio of 28% in AS2 subjects when compared with AS1 (observed, 33%). Despite an approximately twofold underprediction of the dextromethorphan–paroxetine interaction, an R_pred/obs of 0.71 was obtained for the effect of genotype on the area under the curve ratio. Therefore, PBPK modeling can be successfully used to predict gene–drug–drug interactions (GDDIs). Based on these promising results, a workflow is suggested for the generic evaluation of GDDIs and DDIs that can be applied in other situations.

The association between coffee consumption and bladder cancer in the bladder cancer epidemiology and nutritional determinants (BLEND) international pooled study

Background

Inconsistent results for coffee consumption and bladder cancer (BC) risk have been shown in epidemiological studies. This research aims to increase the understanding of the association between coffee consumption and BC risk by bringing together worldwide case–control studies on this topic.

Methods

Data were collected from 13 case–control comprising of 5,911 cases and 16,172 controls. Pooled multivariate odds ratios (ORs), with corresponding 95% confidence intervals (CIs), were obtained using multilevel logistic regression models. Furthermore, linear dose–response relationships were examined using fractional polynomial models.

Results

No association of BC risk was observed with coffee consumption among smokers. However, after adjustment for age, gender, and smoking, the risk was significantly increased for never smokers (ever vs. never coffee consumers: OR_model2 1.30, 95% CI 1.06–1.59; heavy (> 4 cups/day) coffee consumers vs. never coffee consumers: OR_model2 1.52, 95% CI 1.18–1.97, p trend = 0.23). In addition, dose–response analyses, in both the overall population and among never smokers, also showed a significant increased BC risk for coffee consumption of more than four cups per day. Among smokers, a significant increased BC risk was shown only after consumption of more than six cups per day.

Conclusion

This research suggests that positive associations between coffee consumption and BC among never smokers but not smokers.

Population pharmacokinetics of theophylline in adult Chinese patients with asthma and chronic obstructive pulmonary disease

Background Theophylline has a narrow therapeutic range and large interindividual variability in blood levels, so a thorough understanding of its pharmacokinetic characteristics is essential. Population pharmacokinetic (PPK) approaches could achieve it and many PPK studies of theophylline have been reported in infants. However, none was conducted in Chinese adults and none has explored the effect of CYP1A2 genotypes on the PPK characteristics of theophylline in adults. Objective To evaluate the PPK characteristics of theophylline and to assess the possible influence of covariates, including CYP1A2 genotypes, on theophylline clearance in Chinese adult patients. Setting The study is conducted at the department of respiration in Zhujiang Hospital, Guangzhou, China. Methods Theophylline concentrations were obtained from eligible patients and were measured by high performance liquid chromatography. The polymorphisms of - 3860G > A, - 163C > A, C5347T (CYP1A2*1B) and G-3113A were genotyped using a direct sequencing method. Then, CYP1A2 genotypes, age, fat-free mass (FFM) and other covariates were used to develop a PPK model by NONMEM software. Bootstrap analysis was used to asses the accuracy and prediction of the PPK model. Main outcome measure The concentration and clearance of theophylline. Results A total of 134 theophylline concentrations from 95 patients were obtained. The final model was as follows: CL/F(L/h) = 4.530 × (FFM/56.1)^0.75 × 0.713^CYP1A2*1B, the inter-individual variability in clearance/bioavailability (CL/F) was 44.0%, and the residual variability was 9.8%. The final model was proved to be reliable by bootstrap analysis. Conclusion Theophylline clearance was significantly associated with FFM and CYP1A2*1B genotypes in Chinese adult patients.

Biases Inherent in Studies of Coffee Consumption in Early Pregnancy and the Risks of Subsequent Events

Consumption of coffee by women early in their pregnancy has been viewed as potentially increasing the risk of miscarriage, low birth weight, and childhood leukemias. Many of these reports of epidemiologic studies have not acknowledged the potential biases inherent in studying the relationship between early-pregnancy-coffee consumption and subsequent events. I discuss five of these biases, recall bias, misclassification, residual confounding, reverse causation, and publication bias. Each might account for claims that attribute adversities to early-pregnancy-coffee consumption. To what extent these biases can be avoided remains to be determined. As a minimum, these biases need to be acknowledged wherever they might account for what is reported.

Decreased expression of hepatic cytochrome P450 1A2 (CYP1A2) in a chronic intermittent hypoxia mouse model

Background

Hepatic cytochrome P450 (CYP) isoforms, CYP1A2, is one of important enzymes for many drugs metabolism. Studies have confirmed that sustained hypoxia can influence the expression of hepatic CYP, including CYP1A2. The impact of chronic intermittent hypoxia (CIH), a marked characteristic of sleep apnea, on CYP1A2 remains unclear. The aim of the present study was to evaluate the effect of CIH on the expression of hepatic CYP1A2 in a mouse model with sleep apnea.

Methods

Twenty four old male (6-8 weeks) C57BL/6J mice (n=12 in each group) were randomly assigned to either normoxia group or CIH group. Mice in CIH group underwent 12 weeks intermittent hypoxia exposure. The different gene expression of hepatic CYP1A2 between two groups was analyzed by quantity real-time polymerase chain reaction. The protein levels of hepatic CYP1A2 in each group were observed by using western blotting and immunohistochemistry.

Results

After 12 weeks of exposure to intermittent hypoxia, the expression of hepatic CYP1A2, at the mRNA and protein levels was decreased more significantly in the CIH group than the normoxia group (P<0.01).

Conclusions

CIH contributes to inhibiting the expression of hepatic CYP1A2. This implies that the dosage of drugs metabolized by CYP1A2, should be adjusted in patients with sleep apnea.

Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis

Background

There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake.

Methods

We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies.

Results

Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption.

Conclusions

Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking.

The impact of non-genetic and genetic factors on a stable warfarin dose in Thai patients

Purpose

The aim of this study was to investigate the contributions of non-genetic and genetic factors on the variability of stable warfarin doses in Thai patients.

Methods

A total of 250 Thai patients with stable warfarin doses were enrolled in the study. Demographics and clinical data, e.g., age, body mass index, indications for warfarin and concomitant medications, were documented. Four single nucleotide polymorphisms in the VKORC1 − 1639G > A, CYP2C9*3, CYP4F2 rs2108622, and UGT1A1 rs887829 genes were detected from gDNA using TaqMan allelic discrimination assays.

Results

The patients with variant genotypes of VKORC1 − 1639G > A required significantly lower warfarin stable weekly doses (SWDs) than those with wild-type genotype (p < 0.001). Similarly, the patients with CYP2C9*3 variant allele required significantly lower warfarin SWDs than those with homozygous wild-type (p = 0.006). In contrast, there were no significant differences in the SWDs between the patients who carried variant alleles of CYP4F2 rs2108622 and UGT1A1 rs887829 as compared to wild-type allele carriers. Multivariate analysis, however, showed that CYP4F2 rs2108622 TT genotype accounted for a modest part of warfarin dose variability (1.2%). In contrast, VKORC1 − 1639G > A, CYP2C9*3, CYP4F2 rs2108622 genotypes and non-genetic factors accounted for 51.3% of dose variability.

Conclusions

VKORC1 − 1639G > A, CYP2C9*3, and CYP4F2 rs2108622 polymorphisms together with age, body mass index, antiplatelet drug use, amiodarone use, and current smoker status explained 51.3% of individual variability in stable warfarin doses. In contrast, the UGT1A1 rs887829 polymorphism did not contribute to dose variability.

Electronic supplementary material

The online version of this article (doi:10.1007/s00228-017-2265-8) contains supplementary material, which is available to authorized users.

PBPK modeling and simulation in drug research and development

Physiologically based pharmacokinetic (PBPK) modeling and simulation can be used to predict the pharmacokinetic behavior of drugs in humans using preclinical data. It can also explore the effects of various physiologic parameters such as age, ethnicity, or disease status on human pharmacokinetics, as well as guide dose and dose regiment selection and aid drug-drug interaction risk assessment. PBPK modeling has developed rapidly in the last decade within both the field of academia and the pharmaceutical industry, and has become an integral tool in drug discovery and development. In this mini-review, the concept and methodology of PBPK modeling are briefly introduced. Several case studies were discussed on how PBPK modeling and simulation can be utilized through various stages of drug discovery and development. These case studies are from our own work and the literature for better understanding of the absorption, distribution, metabolism and excretion (ADME) of a drug candidate, and the applications to increase efficiency, reduce the need for animal studies, and perhaps to replace clinical trials. The regulatory acceptance and industrial practices around PBPK modeling and simulation is also discussed.

A multi-factorial analysis of response to warfarin in a UK prospective cohort

Background

Warfarin is the most widely used oral anticoagulant worldwide, but it has a narrow therapeutic index which necessitates constant monitoring of anticoagulation response. Previous genome-wide studies have focused on identifying factors explaining variance in stable dose, but have not explored the initial patient response to warfarin, and a wider range of clinical and biochemical factors affecting both initial and stable dosing with warfarin.

Methods

A prospective cohort of 711 patients starting warfarin was followed up for 6 months with analyses focusing on both non-genetic and genetic factors. The outcome measures used were mean weekly warfarin dose (MWD), stable mean weekly dose (SMWD) and international normalised ratio (INR) > 4 during the first week. Samples were genotyped on the Illumina Human610-Quad chip. Statistical analyses were performed using Plink and R.

Results

VKORC1 and CYP2C9 were the major genetic determinants of warfarin MWD and SMWD, with CYP4F2 having a smaller effect. Age, height, weight, cigarette smoking and interacting medications accounted for less than 20 % of the variance. Our multifactorial analysis explained 57.89 % and 56.97 % of the variation for MWD and SMWD, respectively. Genotypes for VKORC1 and CYP2C9*3, age, height and weight, as well as other clinical factors such as alcohol consumption, loading dose and concomitant drugs were important for the initial INR response to warfarin. In a small subset of patients for whom data were available, levels of the coagulation factors VII and IX (highly correlated) also played a role.

Conclusion

Our multifactorial analysis in a prospectively recruited cohort has shown that multiple factors, genetic and clinical, are important in determining the response to warfarin. VKORC1 and CYP2C9 genetic polymorphisms are the most important determinants of warfarin dosing, and it is highly unlikely that other common variants of clinical importance influencing warfarin dosage will be found. Both VKORC1 and CYP2C9*3 are important determinants of the initial INR response to warfarin. Other novel variants, which did not reach genome-wide significance, were identified for the different outcome measures, but need replication.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0255-y) contains supplementary material, which is available to authorized users.

Effect of smoking on the pharmacokinetics of inhaled loxapine

Background:

Loxapine inhalation powder delivered by a hand-held device as a thermally generated aerosol (ADASUVE) was recently approved in the United States and European Union for use in the acute treatment of agitation in patients with bipolar disorder or schizophrenia. As smokers comprise a large subpopulation of these patients, and many antipsychotic drugs require dose adjustments for smokers, the objective of this study was to compare the pharmacokinetics of inhaled loxapine administered to smokers and nonsmokers.

Methods:

Pharmacokinetics and sedation pharmacodynamics using a visual analog scale were studied in 35 male and female adult subjects (18 nonsmokers and 17 smokers) following a single dose of 10 mg of inhaled loxapine. Blood samples were drawn at predose, 30 seconds, 1, 2, 3, 10, 30, and 60 minutes, and 2, 6, 12, and 24 hours after dosing. Loxapine and 8-OH-loxapine were analyzed using reverse-phase liquid chromatography coupled with a tandem mass spectrometer. Pharmacokinetic parameters assessed included C_max, T_max, AUC_inf, and T_1/2 for loxapine and 8-OH-loxapine. Geometric mean ratios (GMRs) were determined for smokers to nonsmokers.

Results:

Loxapine C_max was similar in smokers and nonsmokers with a GMR of 99.0%. The median loxapine T_max was 1.88 and 1.01 minutes for nonsmokers and smokers, respectively. Loxapine AUC_inf and AUC_last values in nonsmokers were comparable with smokers (GMRs of 85.3% and 86.7%, respectively). A slight decrease in the observed mean terminal half-life values was observed for smokers (6.52 hours for smokers and 7.30 hours for nonsmokers).

Conclusions:

Sedation profiles and visual analog scale scores at each time point were similar for nonsmokers and smokers. It was concluded that inhaled loxapine does not require dosage adjustment based on smoking behavior.

Meta-analysis: the effects of smoking on the disposition of two commonly used antipsychotic agents, olanzapine and clozapine

OBJECTIVE

To clarify the effects of smoking on the disposition of two commonly used antipsychotics, olanzapine and clozapine, and to create standards to adjust the doses of these drugs in clinical practice based on the smoking status.

DESIGN

A meta-analysis was conducted by searching MEDLINE, Scopus and the Cochrane Library for relevant prospective and retrospective studies.

INCLUDED STUDIES

We included the studies that investigated the effects of smoking on the concentration to dose (C/D) ratio of olanzapine or clozapine.

PRIMARY OUTCOME MEASURE

The weighted mean difference was calculated using a DerSimonian-Laird random effects model, along with 95% CI.

RESULTS

Seven association studies, comprising 1094 patients (652 smokers and 442 non-smokers) with schizophrenia or other psychiatric disorders, were included in the meta-analysis of olanzapine. The C/D ratio was significantly lower in smokers than in non-smokers (p<0.00001), and the mean difference was -0.75 (ng/mL)/(mg/day) (95% CI -0.89 to -0.61). Therefore, it was estimated that if 10 and 20 mg/day of olanzapine would be administered to smokers, about 7 and 14 mg/day, respectively, should be administered to non-smokers in order to obtain the equivalent olanzapine concentration. Four association studies of clozapine were included in the meta-analysis of clozapine, comprising 196 patients (120 smokers and 76 non-smokers) with schizophrenia or other psychiatric disorders. The C/D ratio was significantly lower in smokers than in non-smokers (p<0.00001), and the mean difference was -1.11 (ng/mL)/(mg/day) (95% CI -1.53 to -0.70). Therefore, it was estimated that if 200 and 400 mg/day of clozapine would be administered to smokers, about 100 and 200 mg/day, respectively, should be administered to non-smokers.

CONCLUSIONS

We suggest that the doses of olanzapine and clozapine should be reduced by 30% and 50%, respectively, in non-smokers compared with smokers in order to obtain an equivalent olanzapine or clozapine concentration.

Identification and characterization of psoralen and isopsoralen as potent CYP1A2 reversible and time-dependent inhibitors in human and rat preclinical studies

Naturally occurring furanocoumarin compounds psoralen (PRN) and isopsoralen (IPRN) are bioactive constituents found in herbaceous plants. They are widely used as active ingredients in several Chinese herbal medicines. In this study, the CYP1A2 inhibitory potential of PRN and IPRN was investigated in rats in vitro and in vivo as well as in human liver microsomes. Both compounds exhibited reversible and time-dependent inhibition toward rat microsomal cyp1a2. The IC(50), k(inact), and K(I) values were 10.4 ± 1.4 μM, 0.060 ± 0.002 min(-1), and 1.13 ± 0.12 μM for PRN, and 7.1 ± 0.6 μM, 0.10 ± 0.01 min(-1), and 1.95 ± 0.31 μM for IPRN, respectively. In human liver microsomal incubations, potent reversible CYP1A2 inhibition was observed for both compounds, with IC(50) values of 0.26 ± 0.01 μM and 0.22 ± 0.03 μM for PRN and IPRN, respectively. However, time-dependent inhibition was only observed for IPRN, with kinact and KI values of 0.050 ± 0.002 min(-1) and 0.40 ± 0.06 μM, respectively. Coadministration with PRN or IPRN significantly inhibited cyp1a2 activity in rats, with the area under the curve (AUC) of phenacetin increasing more than 5-fold. Simcyp simulation predicted that PRN would cause 1.71- and 2.12-fold increases in the phenacetin AUC in healthy volunteers and smokers, respectively. IPRN, on the other hand, would result in 3.24- and 5.01-fold increases in phenacetin AUCs in healthy volunteers and smokers, respectively. These findings represent the first detailed report comparing the potential drug-drug interactions of PRN and IPRN, and provide useful information for balancing safe and efficacious doses of PRN and IPRN.

Predicting drug-drug interactions: application of physiologically based pharmacokinetic models under a systems biology approach

The development of in vitro-in vivo extrapolation (IVIVE), a 'bottom-up' approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in the understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems that act as surrogates for delineating various elements of the interactions relevant to absorption, distribution, metabolism and elimination. Recent advances in the knowledge of the population variables required for IVIVE (demographic, anatomical, genetic and physiological parameters) have also contributed to the appreciation of the sources of variability and wider use of this approach for different scenarios within the pharmaceutical industry. Initially, the authors present an overview of the integration of IVIVE into 'static' and 'dynamic' models for the quantitative prediction of DDIs. The main purpose of this review is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic modeling under a systems biology approach to characterize the potential DDIs in individual patients, including those who cannot be investigated in formal clinical trials for ethical reasons. In addition, we address the issues related to the prediction of complex DDIs involving the inhibition of cytochrome P- and transporter-mediated activities through multiple drugs.

Second- and third-hand smoke exposure: Selected literature for healthcare professionals providing home-based services to the severely mentally ill

Purpose: To develop recommendations for healthcare professionals at risk for exposure to secondhand (SHS) and thirdhand smoke (THS) while providing home-based services to patients with severe mental illnesses (SMIs), such as schizophrenia.

Summary: Healthcare professionals who provide services to those with SMIs have the potential to be exposed to SHS and THS. Smoking rates in persons diagnosed with schizophrenia are significantly higher compared to the general population (up to 90% versus approximately 30%). According to one study, only 31.5% of patients with SMIs are likely to have smoke-free homes. Currently there are no guidelines available for minimizing the effects of SHS and THS on healthcare professionals. Strategies for minimizing the effects are proposed.

Conclusion: Literature dealing with the effects of SHS, potential occupational hazards of exposure, and the results of anti-public smoking laws to address the problem were reviewed. The health hazards of THS exposure are an emerging area. Data are limited on alternative strategies for healthcare professionals to minimize SHS and THS exposure. Suggestions to minimize exposure are provided.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.