Therapeutic drug monitoring to improve outcome of anti-TNF drugs in pediatric inflammatory bowel disease. (3rd July 2019)

• Record Type: Journal Article
• Authors: Franca, Raffaella; Curci, Debora; Lucafò, Marianna; Decorti, Giuliana; Stocco, Gabriele
• Is Part Of: Expert opinion on drug metabolism and toxicology. Volume 15:Number 7(2019)
• Page Start: 527
• Page End: 539
• Publication Date: 2019-07-03
• Subjects: Anti-TNF drugs -- biologics -- children -- Crohn's disease -- inflammatory bowel disease -- therapeutic drug monitoring -- ulcerative colitis; Drugs -- Toxicology -- Periodicals; Drugs -- Metabolism -- Periodicals; 615.7
• DOI: 10.1080/17425255.2019.1630378
• Languages: English
• ISSNs: 1742-5255

Abstract

ABSTRACT: Introduction : Medical treatment of pediatric inflammatory bowel diseases (IBD) has been greatly changed by the introduction of a number of biologic agents that are able to target various players of the immune response. In particular, monoclonal antibodies against the pro-inflammatory cytokine TNF-alpha (TNF) such as infliximab, adalimumab, and golimumab are now in the clinics both in induction and maintenance therapy, and several efforts are currently ongoing to optimize the use of these drugs in children. Areas covered : This review focuses on therapeutic drug monitoring (TDM) of anti-TNF levels and antidrug antibodies (ADAs), in IBD children. A revision of the analytical assays used for assessing anti-TNF plasma levels is also provided. Expert opinion : Although there is a consensus across studies that higher anti-TNF trough levels are associated with a better clinical outcome, and that early anti-TNF serum measurements could be predictive of long-term response, it is still not clear what the best predictive time of sampling is and what the ideal target drug plasma concentration to achieve. Indeed, there are a number of published studies, particularly in pediatric cohorts, limited by the population size analyzed and more prospective large studies are needed to examine the value of these predictive markers.