P885 Pharmacokinetics, pharmacodynamics, and immunogenicity of biosimilar infliximab in pediatric patients with inflammatory bowel disease

Abstract

Abstract Background The pharmacokinetics and pharmacodynamics of biosimilar infliximab (IFX-BioS) in pediatric inflammatory bowel disease (IBD) are poorly understood. We examined some factors predicting IFX-BioS trough levels (TLs) in children. Methods Children with Crohn's disease (CD) and ulcerative colitis (UC) with an indication to start IFX-BioS in our center were prospectively included (January 2021-June 2022). TLs were measured with an in vitro lateral flow immunoassay (therapeutic range:3-7 microg/mL) at the 4th and 6th infusions and correlated with several covariates. Results A total of 110 TLs in 55 children (34 UC and 21 CD) were included. The mean TLs were 8.8±7.6 microg/mL and 9.8±6.7 microg/mL at the 4th and 6th infusions, respectively. The multivariate linear regression model at the 4th infusion found a positive correlation between TLs and age at diagnosis (B: 1.950, 95% CI: [0.019, 3.882], p=0.048) and IFX-BioS dose/kg (B: 1.962, 95% CI: [0.238, 3.687], p=0.029), and a negative correlation with clinical scores (B: -0.401, 95% CI: [-0.738, -0.064], p=0.023). At the 6th infusion, female gender (B: 6.887, 95 CI: [0.861, 12.913], p=0.029), hemoglobin (B: 1.853, 95% CI: [0.501, 3.204], p=0.011), and IFX-BioS dose/kg (B: 1.792, 95% CI: [0.979, 2.605], p<0.001) were found to be positively correlated to TLs. Clinical remission was achieved in 71% (4th infusion) and 67.2% (6th infusion) of patients. Logistic regression analysis revealed no significant association between combined clinical and biochemical remission and TLs at the 4th (OR: 0.010, 95% CI: [0.928; 11.099], p=0.819) or 6th (OR: 0.017, 95% CI: [0.924; 1.119], p=0.732) infusion, corrected for IFX-BioS dose/kg and interval between infusions. Conclusion We discovered some predictors IFX-BioS TLs in IBD children. Understanding the IFX-BioS pharmacokinetics and pharmacodynamics could allow physicians to identify which patients are at higher risk of poor outcomes and adjust treatment accordingly.