GLP-1 based therapies: differential effects on fasting and postprandial glucose.

Glucagon-like peptide-1 (GLP-1), a gut-derived hormone secreted in response to nutrients, has several glucose and weight regulating actions including enhancement of glucose-stimulated insulin secretion, suppression of glucagon secretion, slowing of gastric emptying and reduction in food intake. Because of these multiple effects, the GLP-1 receptor system has become an attractive target for type 2 diabetes therapies. However, GLP-1 has significant limitations as a therapeutic due to its rapid degradation (plasma half-life of 1-2 min) by dipeptidyl peptidase-4 (DPP-4). Two main classes of GLP-1-mediated therapies are now in use: DPP-4 inhibitors that reduce the degradation of GLP-1 and DPP-4-resistant GLP-1 receptor (GLP-1R) agonists. The GLP-1R agonists can be further divided into short- and long-acting formulations which have differential effects on their mechanisms of action, ultimately resulting in differential effects on their fasting and postprandial glucose lowering potential. This review summarizes the similarities and differences among DPP-4 inhibitors, short-acting GLP-1R agonists and long-acting GLP-1R agonists. We propose that these different GLP-1-mediated therapies are all necessary tools for the treatment of type 2 diabetes and that the choice of which one to use should depend on the specific needs of the patient. This is analogous to the current use of modern insulins, as short-, intermediate- and long-acting versions are all used to optimize the 24-h plasma glucose profile as needed. Given that GLP-1-mediated therapies have advantages over insulins in terms of hypoglycaemic risk and weight gain, optimized use of these compounds could represent a significant paradigm shift for the treatment of type 2 diabetes.

Clinical relevance of anti-exenatide antibodies: safety, efficacy and cross-reactivity with long-term treatment.

AIMS: Antibody formation to therapeutic peptides is common. This analysis characterizes the time-course and cross-reactivity of anti-exenatide antibodies and potential effects on efficacy and safety. METHODS: Data from intent-to-treat patients in 12 controlled (n = 2225,12-52 weeks) and 5 uncontrolled (n = 1538, up to 3 years) exenatide twice-daily (BID) trials and 4 controlled (n = 653,24-30 weeks) exenatide once weekly (QW) trials with 1 uncontrolled period (n = 128,52 weeks) were analysed. RESULTS: Mean titres peaked early (6-22 weeks) and subsequently declined. At 30 weeks, 36.7% of exenatide BID patients were antibody-positive; 31.7% exhibited low titres (≤125) and 5.0% had higher titres (≥625). Antibody incidence declined to 16.9% (1.4% higher titre) at 3 years. Similarly, 56.8% of exenatide QW patients were antibody-positive (45.0% low/11.8% higher titre) at 24-30 weeks, declining to 45.4% positive (9.2% higher titre) at 52 weeks. Treatment-emergent anti-exenatide antibodies from a subset of patients tested did not cross-react with human GLP-1 or glucagon. Other than injection-site reactions, adverse event rates in antibody-positive and antibody-negative patients were similar. Efficacy was robust in both antibody-negative and antibody-positive patients (mean HbA1c change: -1.0 and -0.9%, respectively, exenatide BID; -1.6% and -1.3% exenatide QW). No correlation between change in HbA1c and titre was observed for exenatide BID, although mean reductions were attenuated in the small subset of patients (5%) with higher titres. A significant correlation was observed for exenatide QW with no difference between antibody-negative and low-titre patients, but an attenuated mean reduction in the subset of patients (12%) with higher titres. CONCLUSIONS: Low-titre anti-exenatide antibodies were common with exenatide treatment (32% exenatide BID, 45% exenatide QW patients), but had no apparent effect on efficacy. Higher-titre antibodies were less common (5% exenatide BID, 12% exenatide QW) and within that titre group, increasing antibody titre was associated with reduced average efficacy that was statistically significant for exenatide QW. Other than injection-site reactions, anti-exenatide antibodies did not impact the safety of exenatide.

Prophylactic use of anti-emetic medications reduced nausea and vomiting associated with exenatide treatment: a retrospective analysis of an open-label, parallel-group, single-dose study in healthy subjects.

AIMS: Transient nausea and, to a lesser extent, vomiting are common adverse effects of exenatide that can be mitigated by dose titration and usually do not result in treatment discontinuation. This retrospective analysis of data from a phase 1, open-label, parallel-group, single-dose study in healthy subjects evaluated the effect of oral anti-emetics on exenatide-associated nausea and vomiting and on the pharmacokinetics of exenatide. METHODS: A single subcutaneous dose (10 µg) of exenatide was administered to 120 healthy subjects (19-65 years, BMI 23-35 kg/m(2) ). Incidences of nausea and vomiting were compared between 60 subjects premedicated with two oral anti-emetics 30 min before the exenatide dose and 60 non-premedicated subjects. Similarly, the area under the concentration-time curve (AUC) and the maximum observed concentration (C(max) ) of plasma exenatide concentrations over 8 h post-dose were compared. RESULTS: Among all subjects [61% male, 32 ± 12 years, body mass index (BMI) 29.1 ± 3.4 kg/m(2) (mean ± sd)], mild to moderate nausea was the most frequent adverse event after exenatide dosing. Vomiting was also observed. Subjects premedicated with anti-emetics experienced significantly less nausea and vomiting (16.7 and 6.7%, respectively) vs. non-premedicated subjects (61.7 and 38.3%, respectively; P-value <0.0001 for both nausea and vomiting). The mean area under the concentration-time curve and the maximum observed concentration AUC and C(max) of plasma exenatide concentrations during 8 h post-dose were not significantly different between groups. CONCLUSION: Administration of oral anti-emetics before a single 10-µg exenatide dose was associated with significant reductions in treatment-emergent nausea and vomiting, with no discernible effect on the pharmacokinetics of exenatide. Use of anti-emetic therapy may provide a short-term strategy to minimize the nausea and vomiting associated with exenatide treatment.

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 AUC(0-12). This modeling supported phase II/III population pharmacokinetic model development to further determine individual patient tigecycline exposures for safety and efficacy analyses.

Exposure-response analyses of tigecycline efficacy in patients with complicated intra-abdominal infections.

Exposure-response analyses were performed to test the microbiological and clinical efficacies of tigecycline in complicated intra-abdominal infections where Escherichia coli and Bacteroides fragilis are the predominant pathogens. Data from evaluable patients enrolled in three clinical trials were pooled. Patients received intravenous tigecycline (100-mg loading dose followed by 50 mg every 12 h or 50-mg loading dose followed by 25 mg every 12 h). At the test-of-cure visit, microbiological and clinical responses were evaluated. Patients were prospectively classified into cohorts based on infection with a baseline pathogen(s): E. coli only (cohort 1), other mono- or polymicrobial Enterobacteriaceae (cohort 2), at least one Enterobacteriaceae pathogen plus an anaerobe(s) (cohort 3), at least one Enterobacteriaceae pathogen plus a gram-positive pathogen(s) (cohort 4), and all other pathogens (cohort 5). The cohorts were prospectively combined to increase sample size. Logistic regression was used to evaluate ratio of steady-state 24-hour area under the concentration-time curve (AUC) to MIC as a response predictor, and classification-and-regression-tree (CART) analyses were utilized to determine AUC/MIC breakpoints. Analysis began with cohorts 1, 2, and 3 pooled, which included 71 patients, with 106 pathogens. The small sample size precluded evaluation of cohorts 1 (34 patients, 35 E. coli pathogens) and 2 (16 patients, 24 Enterobacteriaceae). CART analyses identified a significant AUC/MIC breakpoint of 6.96 for microbiological and clinical responses (P values of 0.0004 and 0.399, respectively). The continuous AUC/MIC ratio was also borderline predictive of microbiological response (P = 0.0568). Cohort 4 (21 patients, 50 pathogens) was evaluated separately; however, an exposure-response relationship was not detected; cohort 5 (31 patients, 60 pathogens) was not evaluated. The prospective approach of creating homogenous populations of pathogens was critical for identifying exposure-response relationships in complicated intra-abdominal infections.

Exposure-response analyses of tigecycline efficacy in patients with complicated skin and skin-structure infections.

Exposure-response analyses were performed for the microbiological and clinical efficacy of tigecycline in the treatment of complicated skin and skin-structure infections, where Staphylococcus aureus and streptococci are the predominant pathogens. A prospective method was developed to create homogeneous patient populations for PK-PD analyses. Evaluable patients from three clinical trials were pooled for analysis. Patients received a tigecycline 100-mg loading dose/50 mg every 12 h or a 50-mg loading dose/25 mg every 12 h. At the test-of-cure visit, microbiologic and clinical responses were evaluated. Patients were prospectively evaluated and classified into cohorts based on baseline pathogens: S. aureus only (cohort 1), monomicrobial S. aureus or streptococci (cohort 2), two gram-positive pathogens (cohort 3), polymicrobial (cohort 4), or other monomicrobial infections (cohort 5). A prospective procedure for combining cohorts was used to increase the sample size. Logistic regression evaluated steady-state 24-h area under the concentration-time curve (AUC(24))/MIC ratio as a predictor of response, and classification and regression tree (CART) analyses were utilized to determine AUC/MIC breakpoints. Analysis began with pooled cohorts 2 and 3, the focus of these analyses, and included 35 patients with 40 S. aureus and/or streptococcal pathogens. CART analyses identified a significant AUC/MIC breakpoint of 17.9 (P = 0.0001 for microbiological response and P = 0.0376 for clinical response). The continuous AUC/MIC ratio was predictive of microbiological response based on sample size (P = 0.0563). Analysis of all pathogens combined decreased the ability to detect exposure-response relationships. The prospective approach of creating homogeneous populations based on S. aureus and streptococci pathogens was critical for identifying exposure-response relationships.

Population pharmacokinetics of tigecycline in patients with complicated intra-abdominal or skin and skin structure infections.

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 (alpha = 0.05) and backward (alpha = 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 (AUC(0-12)) 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 AUC(0-12) in later exposure-response analyses of tigecycline safety and efficacy in patients with cSSSI or cIAI.