Elizabeth Ludwig

Population Pharmacokinetics of Tigecycline in Patients with Complicated Intra-Abdominal or Skin and Skin Structure Infections

ABSTRACT Tigecycline, a first-in-class expanded glycylcycline antimicrobial agent, has demonstrated efficacy in the treatment of complicated skin and skin structure infections (cSSSI) and complicated intra-abdominal (cIAI) infections. A population pharmacokinetic (PK) model for tigecycline was developed for patients with cSSSI or cIAI enrolled in two phase 2 clinical trials, and the influence of selected demographic factors and clinical laboratory measures was investigated. Tigecycline was administered as an intravenous loading dose followed by a 0.5- or 1-h infusion every 12 h for up to 14 days. Blood samples were collected the day before or the day of hospital discharge for the determination of serum tigecycline concentrations. Patient covariates were evaluated using stepwise forward (α = 0.05) and backward (α = 0.001) procedures. The predictive performance of the model was assessed separately using pooled data from either two phase 3 studies for patients with cSSSI or two phase 3 studies for patients with cIAI. A two-compartment model with zero-order input and first-order elimination adequately described the steady-state tigecycline concentration-time data. Tigecycline clearance was shown to increase with increasing weight, increasing creatinine clearance, and male gender (P < 0.001). The final model provided a relatively unbiased fit to each data set. Individual predicted values of the area under the concentration-time curve from 0 to 12 h (AUC0-12) were generally unbiased (median prediction error, −1.60% to −3.78%) and were similarly precise (median absolute prediction error, <4%) when compared across data sets. The population PK model provided the basis to obtain individual estimates of steady-state AUC0-12 in later exposure-response analyses of tigecycline safety and efficacy in patients with cSSSI or cIAI.

Population Pharmacokinetics and Pharmacodynamics of Garenoxacin in Patients with Community-Acquired Respiratory Tract Infections

ABSTRACT Garenoxacin (T-3811ME, BMS-284756) is a novel, broad-spectrum des-F(6) quinolone currently under study for the treatment of community-acquired respiratory tract infections. This analysis assessed garenoxacin population pharmacokinetics and exposure-response relationships for safety (adverse effects [AE]) and antimicrobial activity (clinical cure and bacteriologic eradication of Streptococcus pneumoniae and the grouping of Haemophilus influenzae, Haemophilus parainfluenzae, and Moraxella catarrhalis). Data were obtained from three phase II clinical trials of garenoxacin administered orally as 400 mg once daily for 5 to 10 days for the treatment of community-acquired pneumonia, acute exacerbation of chronic bronchitis, and sinusitis. Samples were taken from each patient before drug administration, 2 h following administration of the first dose, and on the day 3 to 5 visit. Individual Bayesian estimates of the fu (fraction unbound), the Cmax, and the fu for the area under the concentration-time curve from 0 to 24 h (fu AUC0-24) were calculated as measurements of drug exposure by using an ex vivo assessment of average protein binding. Regression analysis was performed to examine the following relationships: treatment-emergent AE incidence and AUC0-24, Cmax, or patient factors; clinical response or bacterial eradication and drug exposure (fu Cmax/MIC, fu AUC0-24/MIC, and other exposure covariates); or disease and patient factors. Garenoxacin pharmacokinetics were described by a one-compartment model with first-order absorption and elimination. Clearance was dependent on creatinine clearance, ideal body weight, age, obesity, and concomitant use of pseudoephedrine. The volume of distribution was dependent on weight and gender. Patients with mild or moderate renal dysfunction had, on average, approximately a 16 or 26% decrease in clearance, respectively, compared to patients of the same gender and obesity classification with normal renal function. AE occurrence was not related to garenoxacin exposure. Overall, clinical cure and bacterial eradication rates were 91 and 90%, respectively, for S. pneumoniae and 93 and 92%, respectively, for the grouping of H. influenzae, H. parainfluenzae, and M. catarrhalis. The fu AUC0-24/MIC ratios were high (>90% were >200), and none of the pharmacokinetic-pharmacodynamic exposure measurements indexed to the MIC or other factors were significant predictors of clinical or bacteriologic response. Garenoxacin clearance was primarily related to creatinine clearance and ideal body weight. Although garenoxacin exposure was approximately 25% higher for patients with moderate renal dysfunction, this increase does not appear to be clinically significant as exposures in this patient population were not significant predictors of AE occurrence. Garenoxacin exposures were at the upper end of the exposure-response curves for measurements of antimicrobial activity, suggesting that 400 mg of garenoxacin once daily is a safe and adequate dose for the treatment of the specified community-acquired respiratory tract infections.

Population pharmacokinetics of tigecycline in healthy volunteers.

Tigecycline, a novel glycylcycline, possesses broad‐spectrum antimicrobial activity. A structural population pharmacokinetic model for tigecycline was developed based on data pooled from 5 phase I studies. Intravenous tigecycline was administered as single (12.5–300 mg) or multiple (25–100 mg) doses every 12 hours for up to 10 days. Three‐compartment models with zero‐order input and first‐order elimination separately described the single‐ or multiple‐dose full‐profile data. Additional models were evaluated using a subset of the phase I data mimicking the phase II/III trial sparse‐sampling scheme and dosage. A 2‐compartment model best described the reduced phase I data following single or multiple doses and provided reliably accurate estimates of tigecycline AUC0–12. This modeling supported phase II/III population pharmacokinetic model development to further determine individual patient tigecycline exposures for safety and efficacy analyses.

A population pharmacokinetic-pharmacodynamic analysis and model validation of azimilide.

Pharmacokinetic (PK) and pharmacodynamic (PD) models for azimilide were developed and validated with sparse blood sampling and QTc interval data obtained during three clinical trials of azimilide for prevention of supraventricular arrhythmia recurrence.

Challenges in the Transition to Model-Based Development

Practitioners of the art and science of pharmacometrics are well aware of the considerable effort required to successfully complete modeling and simulation activities for drug development programs. This is particularly true because of the current, ad hoc implementation wherein modeling and simulation activities are piggybacked onto traditional development programs. This effort, coupled with the failure to explicitly design development programs around modeling and simulation, will continue to be an important obstacle, to the successful transition to model-based drug development. Challenges with timely data availability, high data discard rates, delays in completing modeling and simulation activities, and resistance of development teams to the use of modeling and simulation in decision making are all symptoms of an immature process capability for performing modeling and simulation.A process that will fulfill the promise of model-based development will require the development and deployment of three critical elements. The first is the infrastructure—the data definitions and assembly processes that will allow efficient pooling of data across trials and development programs. The second is the process itself—developing guidelines for deciding when and where modeling and simulation should be applied and the criteria for assessing performance and impact. The third element concerns the organization and culture—the establishment of truly integrated, multidisciplinary, and multiorganizational development teams trained in the use of modeling and simulation in decision-making. Creating these capabilities, infrastructure, and incentivizations are critical to realizing the full value of modeling and simulation in drug development.

Exposure–response analyses of tigecycline tolerability in healthy subjects☆

Tigecycline exposure (area under the concentration-time curve [AUC((0-infinity))] and maximum serum concentration [C(max)]) and first occurrence of nausea and vomiting were evaluated in 136 healthy subjects after 12.5- to 300-mg single doses. Nausea was more frequent in females (46%, 10/22) compared with males (31%, 11/36) after 100-mg doses. Most nausea (vomiting) events occurred < or =4 h (<6 h) after tigecycline. For doses < or =100 mg, the median duration of nausea and vomiting was approximately 5 h. Based on logistic regression, increased exposure (AUC((0-infinity)) >C(max)) to tigecycline results in an increased rate of nausea (P < or = .0001; = .0022) and vomiting (P < or = .0001; = .0006). At the median AUC((0-infinity)) (C(max)) for the 50-mg dose group, the probability of nausea and vomiting was 0.26 (0.29) and 0.07 (0.11), respectively. Model-predicted rates of nausea and vomiting were comparable with those observed for the tetracycline class of antibiotics, with tolerable rates predicted after 50-mg doses of tigecycline.

OI‐A‐1

TOL is a oral vasopressin (V2) receptor antagonist under development for treatment of CHF and/or HYP. Direct and indirect effect PK/PD models were evaluated to characterize the effect of TOL concentration (Cp) on urine flow rate (UFR) and the influence of water intake rate (WIR), loop diuretic use, and patient covariates.