P0643 Development of a personalized infliximab dosing algorithm for Acute Severe Ulcerative Colitis: results of a multi-center pharmacometrics analysis

Abstract Background Acute severe ulcerative colitis (ASUC) is a medical emergency with a potential need for emergency colectomy. Infliximab (IFX) is a safe and effective rescue therapy for patients with steroid-refractory ASUC. Despite being increasingly practiced, there is no evidence that intensified/accelerated IFX regimens are superior to standard induction dosing [1]. However, insight into the IFX pharmacokinetics (PK) and personalized dosing in ASUC are lacking. Methods We performed a multicenter, retrospective population PK (popPK) and exposure–response modeling study using pooled individual data from ASUC patients diagnosed via Truelove and Witts score. Data on IFX dosing, exposure, patient demographics, and treatment outcomes were collected. A popPK model was developed to predict the relationship between IFX dosing and exposure. Parametric time-to-event analysis was used to predict colectomy within 3 months, considering patient characteristics and PK projections. An algorithm for personalized, risk-stratified IFX rescue dosing was developed. Modeling and simulation tasks were performed in NONMEM. Results Eight medical centers contributed data from 74 patients with ASUC (18 female; median [interquartile range] age 33 [22–47] years; body weight 63 [56–75] kg), including 157 IFX concentrations (Table 1). Baseline C-reactive protein (CRP) and serum albumin were 30 [7–87] mg/L and 31 [27–38] g/L, respectively. Eleven patients (15%) underwent colectomy within 90 days after start of IFX therapy. The one-compartmental popPK model with typical IFX clearance (CL) 0.48 L/day (14% relative standard error) and volume of distribution (V) 12.9 L (21%) described the IFX concentration–time data well. IFX CL and V increased with higher body weight. CL increased with higher CRP. The ratio of the Bayesian forecasted (hence simulated) area under the IFX concentration–time curve between weeks 2 and 4 (AUCw2–w4) over the estimated CL (AUCw2–w4/CL), was the best predictor of colectomy (area under the receiver operating characteristic curve, 0.80 [95%CI 0.54–1.00]). The higher the Ln(AUCw2–w4/CL), which we defined as the colectomy index (C-index), the lower the hazard risk for colectomy. A C-index of 5.84 discriminated best between patients with and without colectomy (sensitivity 83%, specificity 84%) (Figure 1). The classification accuracy was 82% [95%CI 71%–91%]. Conclusion We performed the first model-based dose–exposure–response analysis of IFX in patients with ASUC. We developed the C-index as a predictor for colectomy, which combines AUCw2–w4 (modifiable risk factor) and IFX CL (unmodifiable risk factor). Personalized dosing for IFX rescue therapy using individuals’ AUCw2–w4 target is feasible using an early TDM sample and a precision dosing software tool. References [1] Choy et al. Lancet Gastroenterol Hepatol. 2024;9(11):981–996

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.