Cigarette smoking and theophylline metabolism: effects of phenytoin.

The induction of theophylline clearance by phenytoin was investigated in 12 young male subjects (six nonsmokers and six cigarette smokers). Each subject received intravenous theophylline to determine baseline pharmacokinetics. This was followed by an intravenous loading dose of phenytoin sodium and oral maintenance dosing for 2 weeks, after which the intravenous theophylline study was repeated. Phenytoin concentrations were similar in nonsmokers (10.8 +/- 2.0 micrograms/ml) and smokers (11.5 +/- 0.9 micrograms/ml). Control theophylline elimination half-life was 35% less and clearance 88% greater in smokers than in nonsmokers. The proportionate changes in half-life (26.8% +/- 5.6% in smokers and 25.8% +/- 3.5% in nonsmokers) and clearance (48.0% +/- 10.1% in smokers and 39.7% +/- 7.2% in nonsmokers) as the result of phenytoin induction were similar in both groups. These results demonstrate that the induction of theophylline clearance by phenytoin is additive to that caused by cigarette smoking and provide support for the suggestion that theophylline metabolism is influenced by multiple polymorphisms.

Digoxin pharmacokinetics: role of renal failure in dosage regimen design.

Radioimmunoassayed serum concentration and urinary excretion data for digoxin from azotemic patients were characterized using a 2-compartment open model. Urinary excretion rates of digoxin as well as serum concentration data are needed to accurately characterize the disposition of the drug. Seven patients with renal failure showed highly variable steady-state volumes of distribution (V-ss-D equals 195 to 489 liters/1.73 m-minus2) and t1/2beta values (1.5 to 5.2 days). This variability is a major limiting factor in the use of dosage regimen nomograms that assume a constant V-ss-D and a rigorous relationship between t1/2beta and creatinine clearance (Cl-CR). Body clearance (Cl-B) is a parameter that is affected by both elimination and distribution of drugs. A linear relationship between Cl-B and renal clearance of digoxin or Cl-CR was found and was used to develop a model-independent approach to calculation of maintenance doses of digoxin. Several methods for calculating steady-state serum concentrations of digoxin (C-ss-p) were compared with actual measurements obtained in 16 chronically medicated patients. Optimum computation of C-ss-p is obtained by use of digoxin renal and body clearances. Variability in the digoxin:creatinine renal clearance ratio is the major limiting factor in prediction of digoxin dosage regimens.

Interaction of chloramphenicol with phenytoin and phenobarbital. Case report.

The effect of chloramphenicol therapy (48 mg/kg/day) on the serum concentrations of phenytoin and phenobarbital was studied in a patient previously stabilized on anticonvulsant medications. Phenytoin, 12 mg/kg/day, and phenobarbital, 5 mg/kg/day resulted in serum concentrations averaging 10.8 microgram/ml before and 30.5 microgram/ml, after chloramphenicol therapy. A reduction in dose of both phenytoin and phenobarbital was required to minimize adverse effects during the course of chloramphenicol therapy. An average daily dose of phenytoin of 9.1 mg/kg resulted in an average serum concentration of 17.8 microgram/ml. A daily dose of phenobarbital of 4.0 mg/kg resulted in an average serum concentration of 37.1 microgram/ml. These changes indicate 50.5% and 40.4% decreases in clearance of phenytoin and phenobarbital. Multiple-dose nonlinear regression analysis of phenytoin and phenobarbital serum concentration data obtained during chloramphenicol therapy indicated a 62.5% and a 29.5% decrease in clearance. Subsequent serum concentration monitoring demonstrated a similar reduction in phenobarbital clearance when chloramphenicol was added to phenobarbital alone.

Chloramphenicol sodium succinate kinetics in critically ill patients.

Chloramphenicol sodium succinate (SCAP) kinetics were studied in 10 critically ill patients. High-performance liquid chromatography was used to assay SCAP and chloramphenicol (CAP) in serum and urine. Total body (ClTB), metabolic (ClM), and renal (ClR) clearances of SCAP were variable. Correlations were found between creatinine clearance (Clcr) and ClTB, ClM, and ClR of SCAP (r = 0.92, p less than 0.001; r = 0.84, p less than 0.005; and r = 0.84, p less than 0.005). Recovery of SCAP in the urine also demonstrated large interpatient variability. Between 6.5% and 43.5% of the SCAP dose was recovered in the urine of 6 patients. This variability could not be explained by incomplete urine collection or by differences in renal function. Renal excretion of SCAP was shown to influence CAP serum levels. CAP ClTB was diminished, but no relationship was found between routine liver function studies and CAP ClTB. Therefore we caution the use of such relationships in using CAP in critically ill patients.

The theophylline-enoxacin interaction: II. Changes in the disposition of theophylline and its metabolites during intermittent administration of enoxacin.

The pharmacokinetics of theophylline and its three major metabolites, 3-methylxanthine, 1-methylurate, and 1,3-dimethylurate, were studied during intermittent administration of enoxacin. The addition of enoxacin (400 mg, twice daily) to a theophylline dosing regimen (150 mg, twice daily) resulted in an immediate fall in plasma theophylline metabolite concentrations. Mean steady-state theophylline concentration in plasma during the dosing interval increased from 3.17 to 8.23 micrograms/ml. The mean 12-hour recovery of total theophylline metabolite decrease from 76.3 to 38.6 mg. After the discontinuation of enoxacin, but not theophylline, the plasma theophylline metabolite levels immediately increased to near or above the concentrations observed before enoxacin coadministration. Concurrently, theophylline concentrations decreased to levels equivalent to those observed before enoxacin coadministration. In general, the changes in plasma theophylline concentrations observed after the addition of discontinuation of enoxacin were complete within 3 days.

Pharmacokinetics of ceftriaxone in patients with renal and liver insufficiency and correlations with a physiologic nonlinear protein binding model.

In patients with normal hepatic and renal function, between 30 and 60 percent of administered ceftriaxone is eliminated by nonrenal (biliary) mechanisms. Substantial nonrenal elimination reduces the need for dose adjustments in mild and moderate renal impairment. Minor increases in the biologic half-life (12 hours versus normal of 8 hours) of ceftriaxone have been seen in (functionally) anephric patients with normal extrarenal clearance mechanisms. Anephric patients with decreased nonrenal elimination (additional liver damage) showed a greater increase in biologic half-lives (greater than 15 hours). In patients with various degrees of liver insufficiency (alcoholic fatty liver and cirrhosis with and without ascites), only those with ascites showed significant changes in total drug clearance and volume of distribution. However, these changes in patients with ascites were such that they did not demonstrate significantly different biologic half-lives (9.7 hours versus normal of 8 hours). Simulations of observed concentration versus time data support a physiologic disposition model whereby ceftriaxone, like other cephalosporins, distributes only in plasma and in the extravascular-extracellular (interstitial) fluid and ceftriaxone is saturably bound to albumin in both spaces. All observations in normal subjects and patients were in good agreement with the physiologic disposition model predictions. The consequences of the nonlinear binding behavior of ceftriaxone are such that they favor the administration of ceftriaxone in a large single dose rather than in divided doses. No major drug accumulation is expected in patients with renal or hepatic insufficiency, but anephric patients with a decrease of more than 80 percent in nonrenal elimination will require dose adjustments.

Chloramphenicol pharmacokinetics in infants and young children.

We measured serum chloramphenicol concentrations in 17 hospitalized pediatric patients (aged 1 month to 6 years) after intravenous infusion of chloramphenicol succinate. The serum T1/2 ranged from 2.1 to 8.3 hours with a mean of 3.98 (SD 1.75) hours, while the apparent volume of distribution ranged from 0.78 to 2.09 liters/kg with a mean of 1.39 (SD 0.34) liters/kg. The total body clearance ranged 0.122 to 0.429 liters/kg/hour with a mean of 0.281 (SD 0.117) liters/kg/hour. Two patients were restudied, and had increased clearance during their hospitalization. Because of the wide variability in pharmacokinetics, we conclude that serum chloramphenicol concentrations should be monitored in infants and children.

Individualization of theophylline dosage using a single serum sample following a test dose.

Because formulas for theophylline requirement based on weight alone carry the risk of overdosing and toxicity, this study was designed to test a clearance nomogram for determining daily theophylline requirement after a known initial dose of theophylline. Twenty asthmatic children who had not taken theophylline for at least 36 hours fasted and were given one dose of anhydrous theophylline (5 mg/kg). Six hours later the serum level was measured and the appropriate dosage of sustained-release theophylline to achieve a serum level of 10 micrograms/ml was selected from the clearance nomogram. Three to seven days later a six-hour theophylline level was obtained. Of 20 patients, therapeutic levels of 10 to 30 micrograms/ml were achieved in 15, and the remaining five patients had levels close to this (range 6.2 to 16.0 micrograms/ml). The dosage requirement per 24 hours ranged from 10 to 32 mg/kg/24 hr. This method of determining theophylline requirements for children required measurement of the serum theophylline level only once for the determination of a safe and effective daily dose. It is especially valuable when follow-up is difficult and is a safe way to avoid serious overdosing while being certain of effective dosing.

Altered theophylline clearance during an influenza B outbreak.

During the 1980 influenza B outbreak in King County, Washington, 11 children whose asthma had previously been controlled with a stable theophylline dose, developed theophylline toxicity on this same dose. Two had seizures, eight had nausea and vomiting, and three had headaches. All had clinical evidence of a febrile viral illness. The toxicity appeared to be related to decreased theophylline clearance, which gradually returned to preillness levels over a period of one to three months. Six of ten children had serologic evidence of influenza B, which is presumed to be the cause of the altered clearance. In children receiving chronic theophylline therapy, symptoms of vomiting, headaches, or seizures during a viral illness may be due to theophylline toxicity rather than the virus. Such patients should have an immediate serum theophylline determination, even if previous levels have been in the therapeutic range.

Haemoperfusion in the management of digoxin toxicity: is it warranted?

Several recent publications have encouraged the use of hemoperfusion to remove digoxin from the body of overdosed patients. The usefulness of haemoperfusion in removing digoxin from the body has therefore been examined using pharmacokinetic simulation techniques and published data. Haemoperfusion for a period of 4 hours with a clearance of 100 ml/min removes less than 7% of the amount of digoxin in the body (including that in the gastrointestinal tract at the beginning of haemoperfusion), regardless of the time after the dose that haemoperfusion is started. Dramatic therapeutic benefit in digoxin intoxication is unlikely to be a consequence of the amount of digoxin removed from the body by haemoperfusion. If therapeutic benefit is derived from a transient decline of digoxin concentration in plasma, it may be expected to be negated as the drug redistributes from tissues.

Multiple-dose non-linear regression analysis program. Aminoglycoside dose prediction.

The ability of a new multiple-dose non-linear regression analysis program to predict steady-state aminoglycoside peak and trough serum concentrations was evaluated. 30 patients receiving either amikacin (7), gentamicin (10) or tobramycin (13) were studied. A standard method of prediction which requires the collection of 3 or 4 serum samples during a dosing interval and a predictive method which relies upon population-based estimates of pharmacokinetic parameters were compared with the new approach which requires the collection of 2 serum samples. There were no significant differences between the methods which utilised serum concentration data with regard to predictive precision (mean prediction error of about 10%). These methods were more precise than the population-based method (p less than 0.01, mean prediction error 29.1%). None of the methods produced biased estimates. These results indicate that when the regression program is employed, valid estimates of pharmacokinetic parameters and prediction of steady-state serum concentrations can be obtained with fewer serum samples than have been recommended.

Population pharmacokinetics of clinafloxacin in healthy volunteers and patients with infections: experience with heterogeneous pharmacokinetic data.

OBJECTIVE: Clinafloxacin is a new fluoroquinolone antibacterial with inhibitory activity against aerobic, anaerobic and atypical bacterial pathogens. The objectives of this study are to evaluate the pharmacokinetics of clinafloxacin in healthy volunteers and patients with infections and to describe our experience with mixed-effects modelling using heterogeneous pharmacokinetic data. DESIGN AND SETTING: Retrospective analysis of data from phase I to III trials. PATIENTS AND PARTICIPANTS: 204 healthy volunteers and 221 patients with infections. METHODS: Nonlinear mixed-effects modelling (MEM) was used to evaluate 3437 clinafloxacin plasma concentrations collected in 15 phase I to III trials. Models were developed separately for the healthy volunteers and patients, and then for the combined study population. RESULTS: The phase I data were best described with a 2-compartment linear model with first-order absorption. The absorption lag-time and absorption rate constant were 0.24h and 1.17h(-1), respectively. The volumes of distribution were found to be nonlinear functions of body surface area. Estimated creatinine clearance was the most important covariate for systemic clearance (CL). Interoccasion variability (IOV) in CL was observed in the patients in the phase II trial. In the combined study population, the variability in CL was best described by a model including IOV and distinct variabilities for healthy volunteers and patients. CONCLUSION: MEM was useful for evaluating data collected during different phases of drug development for this new fluoroquinolone agent.

Prediction of maintenance dose required to attain a desired drug concentration at steady-state from a single determination of concentration after an initial dose.

Strong correlations have been reported between drug concentrations at steady-state and a single drug concentration determined sometime after an initial dose for lithium, nortriptyline, imipramine, desipramine, choramphenicol and theophylline. The mathematical basis of these relationships suggests that a one point method for predicting steady-state drug concentrations and individual dosing requirements should be widely applicable to most drugs and should be valid for patients having a wide range of drug half-lives. A method is presented for evaluating the optimum time of blood sampling to determine a drug concentration in serum of plasma that best correlates with steady-state levels and for defining the range of drug half-lives beyond which the predictive approach is likely to give poor results.

Hypothesis for the individualisation of drug dosage.

Computer simulations based on the pharmacokinetics of chloramphenicol and theophylline in patients, indicate a very strong correlation (r = 0.988 for chloramphenicol and r = 0.971 for theophylline) between log maintenance dose required to achieve a desired average drug concentration in serum at steady-state, and the drug concentration in serum 6 hours after an initial test dose administered by constant rate intravenous infusion over 0.5h. Accordingly, we have developed a nomogram to predict individual daily dosing requirements for these drugs in uncomplicated patients from a single serum assay following an initial dose. Within defined limits, predictions made with the nomogram are essentially equivalent to those made by iraditional pharmacokinetic methods which require substantially more drug concentration-time data following a test dose. Predictions based on the nomogram are relatively unaffected by small but typical errors in magnitude of the test dose, infusion time, sampling time and assay. Protocols for the administration of the test dose other than described, e.g. administration of an oral theophylline solution, may be equally useful for dosage predictions. In principle, this approach should apply to other drugs.

Rapid estimation of chloramphenicol clearance in infants and children.

A method is presented by which chloramphenicol clearance (CL) can be estimated from a single serum sample obtained 6 hours after the initial intravenous dose. The method was evaluated prospectively in 20 infants and children who received intravenous chloramphenicol sodium succinate. Agreement between predicted and observed clearance was excellent (r = 0.914, p less than 0.001). The equation of the observed regression line was: observed 0.886x predicted + 0.019. The method appears to provide reasonably accurate estimates of clearance which can be used for rapid clinical adjustment of dose.

Clinical pharmacokinetics of troglitazone.

Troglitazone is a new thiazolidinedione oral antidiabetic agent approved for use to improve glycaemic control in patients with type 2 diabetes. It is rapidly absorbed with an absolute bioavailability of between 40 and 50%. Food increases the absorption by 30 to 80%. The pharmacokinetics of troglitazone are linear over the clinical dosage range of 200 to 600 mg once daily. The mean elimination half-life ranges from 7.6 to 24 hours, which facilitates a once daily administration regimen. The pharmacokinetics of troglitazone are similar between patients with type 2 diabetes and healthy individuals. In humans, troglitazone undergoes metabolism by sulfation, glucuronidation and oxidation to form a sulfate conjugate (M1), glucuronide conjugate (M2) and quinone metabolite (M3), respectively. M1 and M3 are the major metabolites in plasma, and M2 is a minor metabolite. Age, gender, type 2 diabetes, renal impairment, smoking and race do not appear to influence the pharmacokinetics of troglitazone and its 2 major metabolites. In patients with hepatic impairment the plasma concentrations of troglitazone, M1 and M3 increase by 30%, 4-fold, and 2-fold, respectively. Cholestyramine decreases the absorption of troglitazone by 70%. Troglitazone may enhance the activities of cytochrome P450 (CYP) 3A and/or transporter(s) thereby reducing the plasma concentrations of terfenadine, cyclosporin, atorvastatin and fexofenadine. It also reduces the plasma concentrations of the oral contraceptive hormones ethinylestradiol, norethindrone and levonorgestrel. Troglitazone does not alter the pharmacokinetics of digoxin, glibenclamide (glyburide) or paracetamol (acetaminophen). There is no pharmacodynamic interaction between troglitazone and warfarin or alcohol (ethanol). Pharmacodynamic modelling showed that improvement in fasting glucose and triglyceride levels increased with dose from 200 to 600 mg. Knowledge of systemic troglitazone exposure within a dose group does not improve the prediction of glucose lowering response or adverse effects beyond those based on the administered dose.

Impact of population pharmacokinetic-pharmacodynamic analyses on the drug development process: experience at Parke-Davis.

BACKGROUND: Continued scepticism about the benefits of population pharmacokinetics and/or population pharmacodynamics, here referred to collectively as the population approach, hampers its widespread application in drug development. At the same time the sources of this scepticism have not been clearly defined. In an attempt to capture and clearly define these concerns and to help communicate the value of the population approach in drug development at Parke-Davis we conducted a survey of customers within the company. The results of this survey are presented here. METHODS: All drug development programmes conducted over the past 10 years that included a population approach in data analysis and interpretation were identified. A brief description of the population analysis was prepared together with a brief description of how the resulting information was used in each drug development programme. These synopses were forwarded to relevant members of each drug development team together with a survey designed to solicit opinions as to the relevance and impact of these analyses. RESULTS: The most frequent use of information derived from population-based analysis was in labelling. In all cases of drugs making to New Drug Application (NDA) submission the analyses resulted in information that was included in approved or proposed labelling. In almost half of the cases summarised here (5 of 12), population-based analysis was perceived to have resulted in information that influenced the direction of individual development programmes. In many of these cases the information was serendipitous. It is also noted that most of these analyses were not the result of clearly defined objectives and prospective analysis plans. CONCLUSIONS: Use of the population approach, even when applied retrospectively, may have value in complementing or supporting interpretation of other data collected during the course of a trial. Atypical systemic exposure is quickly and easily assessed for correlation with adverse events or exceptional efficacy in retrospective or ad hoc evaluation. Although we know of no direct evidence, it is possible that such use of population pharmacokinetic data has facilitated NDA review and approval by providing insight into the role of atypical systemic drug exposure in otherwise spurious events.

Effect of troglitazone on urinary excretion of 6beta-hydroxycortisol.

Coadministration of troglitazone reduces the plasma concentrations of terfenadine and ethinyl estradiol. Because these drugs are metabolized at least in part by cytochrome P450 3A (CYP3A), it is possible that troglitazone induces CYP3A activity, thereby reducing plasma concentrations of these agents. Known inducers of CYP3A, such as rifampin, phenytoin, carbamazepine, and phenobarbital, increase the urinary excretion of 6beta-hydroxycortisol and the ratio of 6beta-hydroxycortisol to cortisol. This evaluation examined the effect of troglitazone on urinary excretion of 6beta-hydroxycortisol and the ratio of 6beta-hydroxycortisol to cortisol as a marker for CYP3A induction. Urine samples were collected from 11 subjects who completed a study evaluating the effect of multiple-dose administration of troglitazone 400 mg once daily (days 11-20) on the steady-state pharmacokinetics of digoxin (0.25 mg daily on days 1-20). A single urine sample was collected at baseline on day 1, and 24-hour urine samples were collected on days 10 and 20. Mean +/- standard deviation 24-hour excretion rate of cortisol was unchanged, whereas that of 6beta-hydroxycortisol increased during troglitazone administration. The ratio of 24-hour urinary 6beta-hydroxycortisol to cortisol excretion increased from 7.4 +/- 2.7 on day 10 to 16.1 +/- 6.2 on day 20. The ratio observed on day 10 was similar to that obtained at baseline. These results are consistent with the hypothesis that troglitazone induces CYP3A activity.

Effect of troglitazone on the pharmacokinetics of an oral contraceptive agent.

Fifteen healthy women participated in a study to determine the effect of multiple doses of troglitazone on the pharmacokinetics of Ortho-Novum 1/35 (35 micrograms ethinyl estradiol [EE] and 1 mg norethindrone [NE]). Participants received three cycles (21 days each of active drug followed by 7 days without medication) of Ortho-Novum. During the third cycle, participants also received troglitazone 600 mg qd for 22 days. Pharmacokinetic profiles of EE and NE were determined on day 21 of the second and third cycles. Progesterone and sex hormone binding globulin (SHBG) levels were also measured. Troglitazone decreased EE Cmax and AUC(0-24) by 32% and 29%, respectively. Likewise, troglitazone decreased NE Cmax and AUC(0-24) by 31% and 30%, respectively. Plasma SHBG concentrations increased from 113 nmol/L during cycle 2 to 220 nmol/L during cycle 3. Troglitazone reduced plasma unbound AUC for NE by 49%. Serum progesterone levels were lower than 1.5 ng/mL on all occasions. Thus, coadministration of troglitazone and Ortho-Novum decreases the systemic exposure to EE and NE. A higher dose of oral contraceptive or an alternate method of contraception should be considered for patients treated with troglitazone.

Meta-analysis of steady-state pharmacokinetics of troglitazone and its metabolites.

The object of this study is to evaluate the effects of age, gender, age-by-gender interaction, Type II diabetes, body weight, race, smoking, and formulation on steady-state pharmacokinetics of troglitazone, Metabolite 1 (sulfate conjugate), and Metabolite 3 (quinone metabolite) following multiple-dose oral administration of troglitazone. Pharmacokinetic parameter estimates [Cl/F (apparent oral clearance), AUC0-24 (area under plasma concentration-time curve), and ratio of AUC for troglitazone to Metabolite 1 and to Metabolite 3] obtained from 84 healthy volunteers and 171 patients with Type II diabetes in 8 studies were analyzed using a graphical method (for race and smoking) or a weighted ANCOVA model incorporating gender, health status (healthy vs Type II diabetes), and formulation as main effects; age, age-by-gender interaction, and body weight as continuous covariates. Ratio of AUC for troglitazone to metabolites was also examined by inspection of log-probit plots. Age, gender, age-by-gender, Type II diabetes, and formulation had negligible effects on troglitazone Cl/F, AUC0-24 (all analytes), and AUC ratio of troglitazone to metabolites. Race and smoking did not appear to influence steady-state pharmacokinetics of troglitazone and its metabolites. Although body weight was a significant covariate for AUC0-24 and Cl/F, the explanatory power of the overall model was weak (R2 < 0.2). Log-probit plots did not reveal a polymorphic distribution in AUC ratio of troglitazone to Metabolite 1 or Metabolite 3. Based on pharmacokinetics, dose adjustment for troglitazone in relation to the demographic factors examined is not required due to their poor predictive ability on steady-state pharmacokinetics of troglitazone and its metabolites.