Pharmacokinetics of sematilide in renal failure

Pharmacokinetics and Safety of the Ketolide Telithromycin in Patients with Renal Impairment

The pharmacokinetics and safety of the ketolide telithromycin were evaluated in two separate studies after single and repeat oral dosing in patients with varying degrees of renal impairment and in subjects with normal renal function. The single-dose study was an open-label, nonrandomized, parallel-group design in which all 40 patients received a single oral dose of telithromycin 800 mg. The repeat-dose study was an open-label study with a randomized, balanced, incomplete three-block treatment crossover design. In this study, each of the 36 patients received two of three telithromycin regimens (400, 600, or 800 mg once daily for 5 days), with a washout period of >/= 7 days between treatments. Telithromycin was well tolerated. Adverse events were generally mild in severity, and no serious drug-related adverse events were reported. Plasma exposure to telithromycin (C(max), AUC) showed a tendency to increase with increasing severity of renal impairment in both studies. In patients with severe renal impairment (CL(CR) < 30 mL/min) receiving telithromycin 800 mg in the repeat-dose study, C(max,ss) and AUC((0-24 h)ss) increased 1.5-fold (p < 0.05) to 2.0-fold (p = 0.0005), respectively, compared with healthy subjects. The percentage of dose excreted in urine and renal clearance (CL(R)) of telithromycin was found to decrease significantly with increasing severity of renal impairment in both studies, and CL(R) was found to be independent of telithromycin dose in the repeat-dose study. In conclusion, telithromycin dosage adjustment is not necessary in patients with mild to moderate renal impairment (CL(CR) >/= 30 mL/min). In patients with severe renal impairment (CL(CR) < 30 mL/min), dosage adjustment could be considered.

Evaluation of a novel method to estimate absolute bioavailability of drugs from oral data

The goal of this investigation was to evaluate the performance of a novel method allowing estimation of absolute bioavailability from oral data only. In contrast to the traditional method, which compares areas under the drug concentration time curves after oral and intravenous administration in subjects with normal renal function, the novel method uses total and renal clearance values following oral administration from subjects with varying renal functions to estimate bioavailability. The novel method can also provide estimates for nonrenal clearance.Published data on total clearance and renal clearance of drugs obtained from subjects with variable renal functions were collected, the novel method applied, estimates of bioavailability and nonrenal clearance obtained and compared with reported estimates by the traditional methods. In addition computations were performed to assess various factors that could possibly affect the reliability of the novel method. The results indicated that the novel method provides accurate estimates for bioavailability of drugs meeting the prerequisites: linear kinetics, predominant renal excretion in normals, absence of metabolic polymorphism and independence of bioavailability and nonrenal clearance from renal function. The average (standard deviation) of the prediction error and bias of the bioavailability estimates by the novel method was 7.8 (6.0) and -1.4 (9.8)%, respectively. The estimates for nonrenal clearance by the novel method were less accurate. The computations confirmed that the estimates by the novel method are sensitive to renal-function dependent changes in nonrenal clearance and bioavailability and also depend on the extent of renal excretion of a drug. In conclusion, the novel method's main use is to diagnose absence or presence of changes in bioavailability and non-renal clearance of drugs in populations with varying renal function.

Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution

In drug discovery and nonclinical development the volume of distribution at steady state (V(ss)) of each novel drug candidate is commonly determined under in vivo conditions. Therefore, it is of interest to predict V(ss) without conducting in vivo studies. The traditional description of V(ss) corresponds to the sum of the products of each tissue:plasma partition coefficient (P(t:p)) and the respective tissue volume in addition to the plasma volume. Because data on volumes of tissues and plasma are available in the literature for mammals, the other input parameters needed to estimate V(ss) are the P(t:p)'s, which can potentially be predicted with established tissue composition-based equations. In vitro data on drug lipophilicity and plasma protein binding are the input parameters used in these equations. Such a mechanism-based approach would be particularly useful to provide first-cut estimates of V(ss) prior to any in vivo studies and to explore potential unexpected deviations between sets of predicted and in vivo V(ss) data, when the in vivo data become available during the drug development process. The objective of the present study was to use tissue composition-based equations to predict rat and human V(ss) prior to in vivo studies for 123 structurally unrelated compounds (acids, bases, and neutrals). The predicted data were compared with in vivo data obtained from the literature or at Roche. Overall, the average ratio of predicted-to-experimental rat and human V(ss) values was 1.06 (SD = 0.817, r = 0.78, n = 147). In fact, 80% of all predicted values were within a factor of two of the corresponding experimental values. The drugs can therefore be separated into two groups. The first group contains 98 drugs for which the predicted V(ss) were within a factor of two of those experimentally determined (average ratio of 1.01, SD = 0.39, r = 0.93, n = 118), and the second group includes 25 other drugs for which the predicted and experimental V(ss) differ by a factor larger than two (average ratio of 1.32, SD = 1.74, r = 0.42, n = 29). Thus, additional relevant distribution processes were neglected in predicting V(ss) of drugs of the second group. This was true especially in the case of some cationic-amphiphilic bases. The present study is the first attempt to develop and validate a mechanistic distribution model for predicting rat and human V(ss) of drugs prior to in vivo studies.