Phillip Minar

Background: With modest rates of endoscopic remission to anti-TNF biologics in children with moderate-to-severe Crohn’s disease (CD), there is a critical need to develop noninvasive biomarkers associated with anti-TNF response. We performed a comprehensive proteomic evaluation to identify peripheral-blood candidate biomarkers for anti-TNF response. Methods: The ENvISION study enrolled patients (2-19 years old) with CD prior to starting infliximab or adalimumab with outcomes prospectively monitored at Month 3 (M3) and Month 12 (M12). The SomaScan® (Somalogic, Boulder, CO, 7322 analytes) was performed prior to anti-TNF treatment (baseline) at M3 and M12. Endoscopic remission was assessed at M12 (simple endoscopic score-CD < 3). Results: Eighty patients with CD were enrolled with the CD Core Proteome developed from 61 prednisone-naive CD and 30 healthy controls. We identified 2999 differentially abundant proteins, 1403 with lower abundance and 1596 with higher abundance (FDR < 0.05). The CD Core Proteome was then compared across the three timepoints (baseline, M3 and M12) and we found that at both M3 and M12, the Core Proteome dysregulation retains strong identity with the baseline protein signal (β = .7, P < .001; β = .63, P < .001, respectively). Although the proteome exhibits change over time, it does not revert to a control-like state; rather, it transitions to a distinct “treated CD” proteome. In an exploratory investigation of the change in (delta) protein abundance from baseline to M3, we identified 132 proteins nominally associated with M12 endoscopic remission (P < .01). Using elastic net regression, we identified a three-protein panel (IRF1, NEUROG1, and APOA5) associated with M12 endoscopic remission (AUROC 0.94, 95% CI 0.88-1.0). Conclusions: In an exploratory investigation, we identified a CD Core Proteome and three-protein panel whose early changes were associated with M12 endoscopic remission, supporting their use as early pharmacodynamic response markers following external validation.

Background: Crohn’s disease (CD) patients achieving deep remission, defined as clinical remission with endoscopic healing (EH), have a lower rate of CD-related adverse events. EH can be achieved with anti-tumor necrosis factor (TNF) dose optimizations directed by pharmacokinetic (PK) and pharmacodynamic (PD) biomarkers. The primary aim was to identify PK metrics and PD biomarker cut-points associated with EH. Methods: In this multicenter, cross-sectional study, we enrolled CD patients (age 1-22 years) who received an anti-TNF biologic (infliximab or adalimumab) for >6 months and underwent ileocolonoscopy. EH was defined as a simple endoscopic score-CD (SES-CD) < 3. Results: Eighty-seven patients were enrolled with EH found in 55.2%. Lower levels of novel biomarkers neutrophil CD64, monocyte CD64, and soluble CD64 were associated with EH with cut-points of <4.5 ratio (AUROC 0.76), <44.6 ratio (AUROC 0.67), and <15.9 ng/mL (AUROC 0.67), respectively. There was no difference in the mean trough concentrations of infliximab or adalimumab between EH and non-EH, but the median infliximab clearance was higher in non-EH (0.26 L/day) compared to EH (0.21 L/day, P = .02). In our infliximab multivariable model, slower infliximab clearance, lower platelet count, and higher serum albumin were strong predictors for EH (AUC 0.90). Conclusions: We identified novel PK and PD cut-points for biomarkers associated with EH, including infliximab clearance and the novel CD64 biomarkers. Furthermore, we developed a multivariable PK and PD model for EH that, following validation, could guide dose escalation (PK failures) or prompt a switch to an alternate advanced therapeutic for PD failures.

Background and Aims: Children with Crohn’s Disease (CD) who develop internally penetrating complications (IPCs; abscesses and inflammatory masses) are at high risk for surgery and other adverse events. Early anti-tumor-necrosis-factor therapy (anti-TNF) improves outcomes among children with CD and anti-TNF initiation soon after IPC resolution decreases surgical risk. We aimed to evaluate the safety and effectiveness of early anti-TNF therapy among children hospitalized with active IPCs. Methods: We conducted a multicenter retrospective study of children (age ≥6 years) diagnosed with IPCs from 2007-2021. The exposure was anti-TNF within 30 days of IPC diagnosis. Outcomes included 1) infectious serious adverse events (iSAE) within 90 days, 2) non-infectious CD-related SAE (cdSAE), 3) CD-related surgery, and 4) combined clinical-biochemical-corticosteroid-free remission within 1 year. Outcomes were compared via inverse-probability-of-treatment-weighted Kaplan-Meier curves (log-rank test) and Cox proportional hazards models stratified by percutaneous drainage (PD) status. Results: Among 203 patients (median age 16 years, 50% female), 87 (43%) received early anti-TNF within 30 days of IPC diagnosis. In Cox analyses, early anti-TNF was not linked to iSAE, cdSAE, or surgeries, but was associated with increased combined clinical-biochemical-corticosteroid-free remission (HR 1.65, 95%CI 1.20, 2.27). However, surgical risk differed by PD status: patients receiving early anti-TNF and PD had lower risk versus PD alone (event-free survival 58% versus 15%, log-rank P=0.04). Conclusions: Early anti-TNF therapy in children with IPCs was not associated with iSAE or cdSAE. Notably, in those undergoing PD, early anti-TNF was associated with decreased surgeries. These findings support early anti-TNF initiation within a multidisciplinary treatment framework. Prospective studies with standardized treatment protocols are needed.

Model‐informed precision dosing (MIPD) utilizes pharmacokinetic/pharmacodynamic (PK/PD) models to optimize drug therapy. However, conventional MIPD often requires manual simulation and regimen selection, which are time‐consuming and demand specialized expertise. Reinforcement learning (RL), in which an agent learns optimal decisions through iterative interactions with an environment, offers a scalable and automated alternative. In this study, we developed a model‐informed Deep Q‐Network (DQN) to personalize infliximab dosing for patients with Crohn’s disease. The DQN was trained in a simulation environment incorporating a population PK model, inter‐individual variability, and assay error. Virtual patients with randomly and independently sampled covariates from log‐normal distributions were used to explore dosing strategies at Infusions 1, 3, and 4. Doses ranged from 1 to 10 mg/kg at Infusion 1 and from 1 to 20 mg/kg thereafter, with intervals of 4–12 weeks. The reward function prioritized achieving trough concentrations of 18–26 μg/mL before Infusion 3 and 5–10 μg/mL before Infusions 4 and 5, while penalizing overtreatment and additional infusions. The DQN policy converged after 80,000 episodes, yielding target attainment probabilities (PTAs) of 92.9% and 98.4% at Infusions 4 and 5, respectively, in 1000 virtual patients. High doses (11–20 mg/kg) were selected in only 0.2% of cases. At Infusion 4, 66.8% of patients received an 8‐week interval, and 57.3% at Infusion 5. Retrospective real‐world validation showed that patients whose actual doses matched DQN recommendations had trough levels significantly closer to target ranges. These findings support the feasibility of using DQN‐based agents to enhance and automate infliximab individualized dosing in pediatric populations.

The use of model‐informed precision dosing to personalize infliximab has been shown to improve both the acquisition of concentration targets and clinical outcomes during maintenance. Current iterations of infliximab pharmacokinetic models include time‐varying covariates of drug clearance, however, not accounting for the expected improvements in the covariates can lead to indiscriminate use of higher infliximab doses and imprecise drug exposure. The aim was to identify changes in the four biomarkers associated with infliximab clearance (Xiong et al. model) and determine if integration of these dynamic changes would improve model performance during induction and early maintenance. We analyzed two cohorts of children receiving infliximab for Crohn's Disease. The E_max method was used to assess time‐varying changes in covariates. Model performance (observed vs. predicted infliximab concentrations) was evaluated using median percentage error (bias) and median absolute percentage error (precision). The combined cohorts included 239 Crohn's disease patients. We found from baseline to dose 4, the maximum changes in weight, albumin, erythrocyte sedimentation rate, and neutrophil CD64 were 4.7%, +11.7%, −62.4%, and −26.5%, respectively. We also found the use of baseline covariates alone to forecast future trough concentration was inferior to the E_max time‐varying method with a significant improvement observed in bias (doses 2, 3, and 4) and precision (doses 2 and 4). The integration of the four time‐varying biomarkers of drug clearance with pharmacokinetic modeling improved the accuracy and precision of the predictions. This novel strategy may be key to improving drug exposure, minimizing indiscriminate dosing strategies, and reducing healthcare costs.

Background: We previously identified circulating and MRI biomarkers associated with the surgical management of Crohn’s disease (CD). Here we tested associations between these biomarkers and ileal resection inflammation and collagen content. Methods: Fifty CD patients undergoing ileal resection were prospectively enrolled at 4 centers. Circulating CD64, extracellular matrix protein 1 (ECM1), GM-CSF autoantibodies (GM-CSF Ab), and fecal calprotectin were measured by ELISA. Ileal 3-dimensional magnetization transfer ratio (3D MTR), modified Look-Locker inversion recovery (MOLLI) T1 relaxation, diffusion-weighted intravoxel incoherent motion (IVIM), and the simplified magnetic resonance index of activity (sMaRIA) were measured by MRI. Ileal resection specimen acute inflammation was graded, and collagen content was measured quantitatively using second harmonic imaging microscopy. Associations between biomarkers and ileal collagen content were tested. Results: Median (interquartile range [IQR]) age was 19.5 (16-33) years. We observed an inverse relationship between ileal acute inflammation and collagen content (r = −0.39 [95% confidence interval {CI}: −0.61, −0.10], P = .008). Most patients (33 [66%]) received biologics, with no variation in collagen content with treatment exposures. In the univariate analysis, CD64, GM-CSF Ab, fecal calprotectin, and sMaRIA were positively associated with acute inflammation and negatively associated with collagen content (P < .1). The multivariable model for ileal collagen content (R2 = 0.31 [95% CI: 0.11, 0.52]) included log CD64 (β = −.27; P = .19), log ECM1 (β = .47; P = .06), log GM-CSF Ab (β = −.15; P = .01), IVIM f (β = .29, P = .10), and IVIM D* (β = 1.69, P = .13). Conclusions: Clinically available and exploratory circulating and MRI biomarkers are associated with the degree of inflammation versus fibrosis in CD ileal resections. With further validation, these biomarkers may be used to guide medical and surgical decision-making for refractory CD.