Thaddeus H. Grasela

The Pharmacokinetic and Pharmacodynamic Profile of Tigecycline

Tigecycline, a first-in-class expanded-spectrum antimicrobial agent, has demonstrated efficacy in the treatment of complicated intra-abdominal and skin and skin-structure infections. This new antibiotic is available as an intravenous formulation and exhibits linear pharmacokinetics. It is rapidly distributed and has a large volume of distribution, indicating extensive tissue penetration. After a 100-milligram loading dose, followed by 50 milligrams every 12 h, the steady-state maximum concentration in serum after a 1-h infusion is approximately 0.6 microg/mL, the 24-h steady-state area under the concentration-time curve is approximately 5-6 microg.h/mL, and the terminal elimination half-life is approximately 40 h. The major route of elimination of tigecycline is through the feces, primarily as unchanged drug. The pharmacokinetic profile is not affected by severe or end-stage renal disease, nor is it significantly altered by hemodialysis. The pharmacokinetics of tigecycline are also not affected by food, although tolerability is increased if the drug is administered following a meal.

Symptomatic cardiotoxicity associated with 5-fluorouracil.

A prospective cohort study was conducted in 35 hospitals with oncology units to determine the incidence of symptomatic cardiotoxicity in patients receiving continuous infusions of 5‐fluorouracil (5‐FU), and to identify risk factors that could contribute to the development of 5‐FU‐associated cardiotoxicity. A sample of 483 patients [197 (41%) women, overall average age ± SD 60.9 ± 11.9 yrs] were followed for one cycle of 5‐FU infusion. Thirty‐eight (7.9%) patients had abrupt termination of the infusion. There were 9 (1.9%) cases of suspected or documented cardiotoxic events. Cardiotoxicity occurred in 7 (3.35%) of 209 patients receiving their first course of 5‐FU and in 2 (0.73%) other patients (p=0.044). Based on univariate analysis, the following patient groups were at elevated risk of cardiotoxicity: those with preexisting cardiac disease (RR=6.83, p=0.0023); patients receiving calcium channel blockers (RR=4.75, p=0.014); those receiving nitrates (RR=9.18, p=0.007); and patients receiving concomitant etoposide (RR=10.32, p=0.022). Patients with underlying cardiac disease require close monitoring while receiving continuous infusions of 5‐FU. They should be observed for signs and symptoms of cardiotoxicity, and vital signs should be measured frequently. Continued reporting of 5‐FU‐associated cardiotoxicity is necessary to identify other patients at risk.

Pretreatment Regimens for Adverse Events Related to Infusion of Amphotericin B

Infusion-related adverse events (IRAEs) such as nausea, vomiting, fever, chills, and thrombophlebitis that are associated with amphotericin B therapy often lead clinicians to prescribe a number of adjunctive pretreatment medications in an attempt to reduce the incidence and severity of these events. The purpose of this study was to determine the incidence of IRAEs during the first week of systemic amphotericin B therapy and to identify pretreatment regimens that are effective in preventing these IRAEs. Three hundred ninety-seven adult inpatients receiving amphotericin B therapy were prospectively monitored, and data regarding IRAEs and pretreatment regimens were collected. Of these patients, 282 (71%) developed at least one IRAE during the first 7 days of therapy. The IRAEs most commonly reported were fever (51% of patients) and chills (28%), followed by nausea (18%), headache (9%), and thrombophlebitis (5%). The most common regimens included diphenhydramine, a corticosteroid, acetaminophen, and heparin, administered alone or in combination with these or other drugs. Overall, common pretreatment regimens were similar in efficacy to no pretreatment in the prevention of IRAEs. Thus empirical premedication for IRAEs associated with amphotericin B cannot be routinely advocated; instead, patients should be treated when symptoms first arise and then premedicated for subsequent amphotericin B infusions.

Inhibition of enoxacin absorption by antacids or ranitidine.

Ten normal volunteers participated in a randomized, five-way crossover study to determine the effect of concurrent enoxacin and antacid or ranitidine administration on enoxacin absorption. The bioavailability of a single oral 400-mg enoxacin dose was significantly decreased, by 73 and 49%, when Maalox TC was administered 0.5 and 2 h before enoxacin, respectively. Enoxacin bioavailability was not significantly altered when the antacid was given 8 h before or 2 h after enoxacin administration. Ranitidine, administered intravenously 2 h before enoxacin, also significantly decreased enoxacin bioavailability, by 40%. The correlation between the proximity of antacid administration and the magnitude of the decrease in enoxacin bioavailability supports complexation as the mechanism of the antacid-enoxacin interaction. However, reduction of enoxacin bioavailability by ranitidine suggests that elevated gastric pH may also play a role in the antacid-enoxacin drug-drug interaction.

Eliminating Intensive Postoperative Care in Same-day Surgery Patients Using Short-acting Anesthetics

Background A multidisciplinary effort was undertaken to determine whether patients could safely bypass the postanesthesia care unit (PACU) after same-day surgery by moving to an earlier time point evaluation of recovery criteria. Methods A prospective, outcomes research study with a baseline month, an intervention month, and a follow-up month was designed. Five surgical centers (three community-based hospitals and two freestanding ambulatory surgical centers) were utilized. Two thousand five hundred eight patients were involved in the baseline period, and 2,354 were involved in the follow-up period. Outcome measures included PACU bypass rates and adverse events. Intervention consisted of a multidisciplinary educational program and routine feedback reports. Results The overall PACU bypass rate (58%) was significantly different from baseline (15.9%, P < 0.001), for patients to whom a general anesthetic was administered (0.4–31.8%, P < 0.001), and for those given other anesthetic techniques (monitored anesthesia care, regional or local anesthetics; 29.1–84.2%, P < 0.001). During the follow-up period, the average (SD) recovery duration for patients who bypassed the PACU was significantly shorter compared to that for patients who did not bypass, 84.6 (61.5) versus 175.1 (98.8) min, P < 0.001, with no change in patient outcome. Patients receiving only short-acting anesthetics were 78% more likely (P < 0.002) to bypass the PACU after adjusting for various surgical procedures. Conclusions This study represents a substantial change in clinical practice in the perioperative setting. Same-day surgical patients given short-acting anesthetic agents and who are awake, alert, and mobile requiring no parenteral pain medications and with no bleeding or nausea at the end of an operative procedure can safely bypass the PACU.

An introduction to mixed effect modeling: Concepts, definitions, and justification

In spite of the vast amount of data generated during the new drug development process, much remains to be learned about the pharmacokinetics of a drug once it is released on the market. The ethical and logistical problems which arise during an experimental pharmacokinetic study frequently prevent the study of elderly, pediatric, or critically ill patients. The recognition of these limitations by scientists and regulators have prompted a desire to extract the maximum amount of information from data available during Phase III and Phase IV clinical trials and, in addition, to use information generated during the routine clinical care of patients. Mixed effect model analysis allows one to overcome the problems of analyzing observational data to obtain accurate and precise estimates of population pharmacokinetic parameters. Use of this approach expands the methodologies available to the data analyst and opens up a number of data sources which can now be considered for analysis.SummaryIn spite of the vast amount of data generated during the new drug development process, much remains to be learned about the pharmacokinetics of a drug once it is released on the market. The ethical and logistical problems which arise during an experimental pharmacokinetic study frequently prevent the study of elderly, pediatric, or critically ill patients. The recognition of these limitations by scientists and regulators have prompted a desire to extract the maximum amount of information from data available during Phase III and Phase IV clinical trials and, in addition, to use information generated during the routine clinical care of patients. Mixed effect model analysis allows one to overcome the problems of analyzing observational data to obtain accurate and precise estimates of population pharmacokinetic parameters. Use of this approach expands the methodologies available to the data analyst and opens up a number of data sources which can now be considered for analysis.

Population Pharmacokinetic Analysis of Linezolid in Patients With Infectious Disease: Application to Lower Body Weight and Elderly Patients

Linezolid (Zyvox), belonging to oxazolidinone antibiotics, is commonly used for the treatment of patients infected with methicillin‐resistant Staphylococcus aureus and vancomycin‐resistant enterococci. Although linezolid has been approved worldwide, the Japanese pharmacokinetic (PK) profile has not been characterized in detail. The objective of this study is to develop a population PK model for linezolid that can be applied to a Japanese population. This population PK model was established based on the 1 Japanese phase III and 4 Caucasian phase II/III studies. A total of 2539 linezolid plasma concentration measurements from 455 patients, aged 18 to 98 years and body weight 30 to 190.5 kg, were used for the analysis. The data were analyzed using nonlinear mixed effects modeling. Body weight (BW), age, ethnicity, and gender were investigated as covariates. The final model was validated by the bootstrap technique. The PK profiles of linezolid were described with a 1‐compartment PK model with first‐order absorption and first‐order elimination. In the final population PK model, BW and age were influential covariates on clearance, and the distribution volume was affected by BW. The present population PK model of linezolid described well the PK profiles in Japanese patients who have lower BW and are relatively older compared with those in the United States/European Union.

The population pharmacokinetics of theophylline in neonates and young infants

The population pharmacokinetics of theophylline were evaluated using 391 theophylline serum concentration measurements from 108 neonates and young infants (postnatal age 0–26 weeks), who received theophylline for the treatment of neonatal apnea. A one-compartment pharmacokinetic model with first-order elimination was used, with intravenous aminophylline and oral theophylline administration modeled as zero-order infusions. The effect of a variety of developmental and demographic factors on clearance (CL) and volume (V) were investigated. Hypothesis testing to evaluate potentially significant factors produced a final model in which clearance was based on weight (kg) raised to an exponential power and postnatal age (weeks), with CL (ml/hr)=17.5 (weight)1.28 + 1.17 (postnatal age). Clearance was reduced by 12% for patients receiving parenteral nutrition. Volume of distribution in this population was adequately described using only weight, with V (L)=0.858 L/kg. Bioavailability of orally administered drug was not significantly less than unity. Interindividual variability in clearance was modest, with a coefficient of variation for clearance of 16%. An estimate of interindividual variability in volume could not be obtained. As a measure of residual variability in theophylline serum concentrations, the coefficients of variation for theophylline serum concentrations of 5.0, 10.0, and 13.0 mg/L were found to be approximately, 25, 12, and 9%, respectively. The identification of influential patient factors and the quantification of their influence on theophylline disposition allow for a priori estimates of theophylline pharmacokinetic parameters in these patients.

An evaluation of point and interval estimates in population pharmacokinetics using Nonmem analysis

In a simulation study of the estimation of population pharmacokinetic parameters, including fixed and random effects, the estimates and confidence intervals produced by NONMEM were evaluated. Data were simulated according to a monoexponential model with a wide range of design and statistical parameters, under both steady state (SS) and nonSS conditions. Within the range of values for population parameters commonly encountered in research and clinical settings, NONMEM produced parameter estimates for CL, V, σCL,and σewhich exhibit relatively small biases. As the range of variability increases, these biases became larger and more variable. An important exception was bias in the estimate for σvwhich was large even when the underlying variability was small. NONMEM standard error estimates are appropriate as estimates of standard deviation when the underlying variability is small. Except in the case of CL,standard error estimates tend to deteriorate as underlying variability increases. An examination of confidence interval coverage indicates that caution should be exercised when the usual 95% confidence intervals are used for hypothesis testing. Finally, simulationbased corrections of point and interval estimates are possible but corrections must be performed on a casebycase basis.

Evaluation of hypothesis testing for comparing two populations using NONMEM analysis

In a simulation study of inference on population pharmacokinetic parameters, two methods of performing tests of hypotheses comparing two populations using NONMEM were evaluated. These two methods are the test based upon 95% confidence intervals and the likelihood ratio test. Data were simulated according to a monoexponential model and, in that context, power curves for each test were generated for (i)the ratio of mean clearance and (ii)the ratio of the population standard deviations of clearance. To generate the power curves, a range of these parameters was employed; other pharmacokinetic parameters were selected to reflect the variability typically present in a Phase II clinical trial. For tests comparing the means, the confidence interval tests had approximately the same power as the likelihood ratio tests and were consistently more faithful to the nominal level of significance. For comparison of the standard deviations, and when the volume of information available was relatively small, however, the likelihood ratio test was more able to detect differences between the two groups. These results were then compared to results on parameter estimation in order to gain insight into the question of power. As an example, the nonnormality of estimates of the ratio of standard deviations plays an important role in explaining the low power for the confidence interval tests. We conclude that, except for the situation of modeling standard deviations with only sparse information, NONMEM produces tests of significance that are effective at detecting clinically significant differences between two populations.