Population pharmacokinetic analysis of etrolizumab in patients with moderately‐to‐severely active ulcerative colitis

Meta-analysis of etrolizumab versus placebo in ulcerative colitis: safety and efficacy outcomes

Background

The existing body of scientific literature offers inconclusive findings on the safety and therapeutic effectiveness of etrolizumab (ETR) for the treatment of ulcerative colitis (UC).

Objectives

The goal of this meta-analysis is to furnish a comprehensive synthesis of evidence that evaluates the safety and therapeutic effects of ETR in the management of UC.

Design

Meta-analysis.

Data sources and methods

PubMed, Embase, and Web of science were searched to collect relevant English studies, and the reference lists of eligible studies were manually searched to avoid missing any eligible studies. Outcome measures encompassed clinical response, incidence of adverse events, histological remission, endoscopic remission, endoscopic improvement, and antidrug antibodies. Relevant data were extracted by two independent investigators.

Results

The meta-analysis incorporated five eligible studies, involving a total of 1528 patients, with 1015 treated with ETR and 513 with placebo. The pooled analysis indicates that ETR is both effective and safe. The adverse event rates, endoscopic and histological response, as well as overall remission were comparable between the two groups. The monoclonal antibody group had a lower incidence rate of adverse reactions than the placebo group [odds ratio (OR): 0.81; 95% confidence interval (CI): 0.63-1.03; p = 0.09)]. Clinical response was higher in the ETR group than in the placebo group (OR: 1.56; 95% CI: 1.20-2.02; p = 0.0009), and endoscopic improvement was more favorable in the ETR group (OR: 1.88; 95% CI: 1.45-2,45; p < 0.00001). A higher rate of endoscopic remission was found in the ETR group than in the placebo group (OR: 2.48; 95% CI: 1.75-3.50; p < 0.00001); histological remission was significantly higher in the ETR group than in the placebo group (OR: 2.11; 95% CI: 1.55-2.86; p < 0.00001). The placebo group had a lower rate of positive antidrug antibodies (OR: 1.31; 95% CI: 0.79-2.17; p < 0.29), and the incidence of complications was significantly higher in the ETR group compared with the placebo group (OR: 2.05; 95% CI: 1.48-2.83; p < 0.0001).

Conclusion

Given the heterogeneity and potential biases in the included studies, gastroenterologists should cautiously tailor drug delivery strategies based on their clinical experience and the unique needs of individual patients.

PROSPERO registration

CRD42023396100.

Time-dependent clearance can confound exposure-response analysis of therapeutic antibodies: A comprehensive review of the current literature

Exposure-response (ER) analysis is used to optimize dose and dose regimens during clinical development. Characterization of relationships between drug exposure and efficacy or safety outcomes can be utilized to make dose adjustments that improve patient response. Therapeutic antibodies typically show predictable pharmacokinetics (PK) but can exhibit clearance that decreases over time due to treatment. Moreover, time-dependent changes in clearance are frequently associated with drug response, with larger decreases in clearance and increased exposure seen in patients who respond to treatment. This often confounds traditional ER analysis, as drug response influences exposure rather than the reverse. In this review, we survey published population PK analyses for reported time-dependent drug clearance effects across 158 therapeutic antibodies approved or in regulatory review. We describe the mechanisms by which time-dependent clearance can arise, and evaluate trends in frequency, magnitude, and time scale of changes in clearance with respect to indication, mechanistic interpretation of time-dependence, and PK modeling techniques employed. We discuss the modeling and simulation strategies commonly used to characterize time-dependent clearance, and examples where time-dependent clearance has impeded ER analysis. A case study using population model simulation was explored to interrogate the impact of time-dependent clearance on ER analysis and how it can lead to spurious conclusions. Overall, time-dependent clearance arises frequently among therapeutic antibodies and has spurred erroneous conclusions in ER analysis. Appropriate PK modeling techniques aid in identifying and characterizing temporal shifts in exposure that may impede accurate ER assessment and successful dose optimization.

A disease model predicting placebo response and remission status of patients with ulcerative colitis using modified Mayo score

The Mayo Clinical Score is used in clinical trials to describe the clinical status of patients with ulcerative colitis (UC). It comprises four subscores: rectal bleeding (RB), stool frequency (SF), physician's global assessment, and endoscopy (ENDO). According to recent US Food and Drug Administration guidelines (Ulcerative colitis: developing drugs for treatment, Guidance Document, https://www.fda.gov/regulatory-information/s. 2022), clinical response and remission should be based on modified Mayo Score (mMS) relying on RB, SF, and ENDO. Typically, ENDO is performed at the beginning and end of each phase, whereas RB and SF are more frequently available. Item response theory (IRT) models allow the shared information to be used for prediction of all subscores at each observation time; therefore, it leverages information from RB and SF to predict ENDO. A UC disease IRT model was developed based on four etrolizumab phase III studies to describe the longitudinal mMS subscores, placebo response, and remission at the end of induction and maintenance. For each subscore, a bounded integer model was developed. The placebo response was characterized by a mono-exponential function acting on all mMS subscores similarly. The final model reliably predicted longitudinal mMS data. In addition, remission was well-predicted by the model, with only 5% overprediction at the end of induction and 3% underprediction at the end of maintenance. External evaluation of the final model using placebo arms from five different studies indicated adequate performance for both longitudinal mMS subscores and remission status. These results suggest utility of the current disease model for informed decision making in UC clinical development, such as assisting future clinical trial designs and evaluations.

Exposure‐response relationships of etrolizumab in patients with moderately‐to‐severely active ulcerative colitis

Etrolizumab is an IgG1‐humanized monoclonal anti‐β7 integrin antibody. Phase III trials with induction and/or maintenance phases were conducted in patients with moderately‐to‐severely active ulcerative colitis (UC) who were either previously treated with tumor necrosis factor (TNF) inhibitors (HICKORY) or were TNF inhibitor naïve (HIBISCUS I/II, LAUREL, and GARDENIA). A total of eight exposure‐response analyses were conducted for two clinical outcomes (remission and endoscopic improvement) at the end of induction for studies HIBISCUS I/II (combined) and HICKORY and at the end of maintenance for studies HICKORY and LAUREL. Trough concentration at week 4 (C_trough,wk4) of induction was selected as the exposure metric. Exposure‐response (ER) modeling was conducted using logistic regression. A full covariate model was used to examine the impact of covariates on clinical outcomes. Linear models with a single intercept for placebo and active treatments adequately described the data for all eight analyses. The etrolizumab exposure‐response slope was significant (p < 0.05) for seven of the eight analyses. Baseline Mayo Clinic Score (MCS) was the only statistically significant covariate that impacted induction remission and endoscopic improvement. No statistically significant covariate was identified to impact maintenance outcomes except for baseline fecal calprotectin on endoscopic improvement for LAUREL study. A statistically significant positive ER relationship was identified for most of the clinical outcomes tested, reflecting a better treatment effect in patients with UC with higher etrolizumab C_trough,wk4 of induction. Baseline MCS was the only other significant covariate impacting induction efficacy. Besides C_trough,wk4 of induction, no consistent covariate was identified to impact maintenance efficacy.