Prediction of treatment failure during infliximab induction therapy in inflammatory bowel disease patients based on pharmacokinetic and pharmacodynamic modeling

A prediction method for the individual serum concentration and therapeutic effect for optimizing adalimumab therapy in inflammatory bowel disease

OBJECTIVES

Adalimumab (ADM) therapy is effective for inflammatory bowel disease (IBD), but a significant number of IBD patients lose response to ADM. Thus, it is crucial to devise methods to enhance ADM's effectiveness. This study introduces a strategy to predict individual serum concentrations and therapeutic effects to optimize ADM therapy for IBD during the induction phase.

METHODS

We predicted the individual serum concentration and therapeutic effect of ADM during the induction phase based on pharmacokinetic and pharmacodynamic (PK/PD) parameters calculated using the empirical Bayesian method. We then examined whether the predicted therapeutic effect, defined as clinical remission or treatment failure, matched the observed effect.

RESULTS

Data were obtained from 11 IBD patients. The therapeutic effect during maintenance therapy was successfully predicted at 40 of 47 time points. Moreover, the predicted effects at each patient's final time point matched the observed effects in 9 of the 11 patients.

CONCLUSION

This is the inaugural report predicting the individual serum concentration and therapeutic effect of ADM using the Bayesian method and PK/PD modelling during the induction phase. This strategy may aid in optimizing ADM therapy for IBD.

Predictors and optimal management of tumor necrosis factor antagonist nonresponse in inflammatory bowel disease: A literature review

Tumor necrosis factor-α (TNF-α) antagonists, the first biologics approved for treating patients with inflammatory bowel disease (IBD), are effective for the induction and maintenance of remission and significantly improving prognosis. However, up to one-third of treated patients show primary nonresponse (PNR) to anti-TNF-α therapies, and 23%-50% of IBD patients experience loss of response (LOR) to these biologics during subsequent treatment. There is still no recognized predictor for evaluating the efficacy of anti-TNF drugs. This review summarizes the existing predictors of PNR and LOR to anti-TNF in IBD patients. Most predictors remain controversial, and only previous surgical history, disease manifestations, drug concentrations, antidrug antibodies, serum albumin, some biologic markers, and some genetic markers may be potentially predictive. In addition, we also discuss the next steps of treatment for patients with PNR or LOR to TNF antagonists. Therapeutic drug monitoring plays an important role in treatment selection. Dose escalation, combination therapy, switching to a different anti-TNF drug, or switching to a biologic with a different mechanism of action can be selected based on the concentration of the drug and/or antidrug antibodies.

Ulcerative Colitis and Acute Severe Ulcerative Colitis Patients Are Overlooked in Infliximab Population Pharmacokinetic Models: Results from a Comprehensive Review

Ulcerative colitis (UC) is part of the inflammatory bowels diseases, and moderate to severe UC patients can be treated with anti-tumour necrosis α monoclonal antibodies, including infliximab (IFX). Even though treatment of UC patients by IFX has been in place for over a decade, many gaps in modelling of IFX PK in this population remain. This is even more true for acute severe UC (ASUC) patients for which early prediction of IFX pharmacokinetic (PK) could highly improve treatment outcome. Thus, this review aims to compile and analyse published population PK models of IFX in UC and ASUC patients, and to assess the current knowledge on disease activity impact on IFX PK. For this, a semi-systematic literature search was conducted, from which 26 publications including a population PK model analysis of UC patients receiving IFX therapy were selected. Amongst those, only four developed a model specifically for UC patients, and only three populations included severe UC patients. Investigations of disease activity impact on PK were reported in only 4 of the 14 models selected. In addition, the lack of reported model codes and assessment of predictive performance make the use of published models in a clinical setting challenging. Thus, more comprehensive investigation of PK in UC and ASUC is needed as well as more adequate reports on developed models and their evaluation in order to apply them in a clinical setting.

Predictor of primary response to antitumor necrosis factor-α therapy for inflammatory bowel disease: a single-center observational study

BACKGROUND

It is necessary to find reliable and appropriate predictors of primary response to anti-TNFα therapy (infliximab and adalimumab) in inflammatory bowel disease (IBD) so as to avoid treatment failure and select optimal treatment. The aim of this study is to reveal useful predictors of the response to anti-TNFα treatment from baseline to 2 months after initial administration of anti-TNFα for individual IBD patients using our pharmacokinetic and pharmacodynamic (PK/PD) model at the time of second administration.

METHODS

We retrospectively analyzed 26 IBD patients who received anti-TNFα. In the PK/PD model, inflammation was assumed to be suppressed based on the action of anti-TNFα at the rate constant of Kanti-TNFα (day-1). Kanti-TNFα0 (day-1) is Kanti-TNFα in the absence of anti-TNFα. We expressed inflammation caused by factors not affected by the action of anti-TNFα using the rate constant Kelse (day-1). Using univariate and multivariate linear regressions, we statistically analyzed factors related to the improvement of disease activity index.

RESULTS

The significant correlation between Kanti-TNFα0/Kelse and the improvement of disease activity index was shown in Crohn's disease patients (univariate: estimated value 2.4; P = 0.003; and multivariate: 1.8; P = 0.012) and ulcerative colitis patients (univariate: 0.12; P = 0.011), and no other factors were significant.

CONCLUSION

This is the first study to present a useful predictor of primary response to anti-TNFα of individual IBD patients at second administration. The Kanti-TNFα0/Kelse ratio may help to select the optimal therapeutic drug and avoid the improper continuous administration of anti-TNFα in the induction phase.