Prediction of infliximab and anti-drug antibody concentrations in patients with inflammatory bowel disease using machine learning models with real-world data from a prospective cohort study

Key Points

• Machine learning models predict infliximab and anti-drug antibody concentrations effectively, enhancing clinical decisions.
• Random forest and XGBoost performed best for infliximab and anti-drug antibodies, respectively, showing high accuracy.
• The anti-drug antibody model demonstrates stable multi-step forecasting capability for better dosing strategies.
• Individualized dosing may reduce the need for frequent therapeutic drug monitoring in clinical practice.