Society: AGA

Background: Our team (Xiong et al. 2021) recently developed an infliximab population pharmacokinetic (popPK) model in children and young adults with Crohn’s disease (CD). We found that prediction accuracy improved when all five covariates of drug clearance were included. Given the dynamic changes in the four covariates (weight, albumin, sedimentation rate, neutrophil CD64 expression) that occur during induction, we hypothesized that model-informed precision dosing to predict early trough concentrations (cTrough) from baseline covariates alone would be imprecise. Therefore, our aims were to: 1. Test the precision of the model predicted (a priori) cTrough compared to the observed cTrough at dose3 and dose4 and 2. Test whether disease progression modeling would provide more precise predictions.
Methods: REFINE is a prospective cohort of 78 children and young adults receiving infliximab at four medical centers from 2014-2019. The DSH retrospective cohort includes 161 children and young adults with CD who started infliximab at a single center from 2019-2021. REFINE cTroughs were obtained at every infusion while the DSH cohort had cTroughs obtained either at dose3, dose4 or both. Model imprecision was calculated by the root mean square error (RMSE%) and percent bias by the mean prediction error (MPE%). The Pearson r and R²were used to calculate the correlation between the observed and the model predicted cTrough.
Results: The median (IQR) age at the start of infliximab was 14.3 (11-16) years with 32% female, and 85% white race. The median starting dose was 7.1 (5.5-10) mg/kg. Using the combined cohorts, we first calculated the observed percent improvement of all four covariates from dose1-dose3 and from dose1-dose4 (Table1). We then assessed the a priori predicted cTrough at dose3 and dose4 for both cohorts using the Xiong et al. popPK model and Bayesian estimation under three conditions. Condition1: cTrough were predicted using only the four baseline (pre-treatment) covariates of clearance. Condition2: cTrough were calculated using a combination of the baseline covariates and the calculated improvement (from baseline as shown in Table1) in all four covariates at either dose3 or dose4. Condition3: combination of Condition2 and one observed cTrough (week2 for dose3 and week6 for dose4 predictions). As shown, the MPE% improved when the simulated dose3 covariates were included in the prediction (Table2, A2). Furthermore, the correlations between the predicted and observed dose3 cTrough also improved for ConditionA3. For dose4, incorporating the week6 level improved the RMSE% and Pearson correlation (ConditionB3).
Conclusions: Disease progression modeling improves the precision of predicting the targeted dose3 (week6) cTrough. Disease progression modeling will be incorporated in our PK dashboard to perform more accurate model-informed precision dosing.

<b>Table1</b>. Observed improvement in the four covariates of drug clearance from dose1-dose3 or dose1-dose4.

Table1. Observed improvement in the four covariates of drug clearance from dose1-dose3 or dose1-dose4.

<b>Table2: </b>Model performance without and with disease progression pharmacokinetic modeling.

Table2: Model performance without and with disease progression pharmacokinetic modeling.

Introduction: Both the Crohn’s Disease Exclusion Diet combined with Partial enteral nutrition (CDED+PEN) and exclusive enteral nutrition (EEN) induce remission in mild-to-moderate pediatric Crohn’s Disease (CD) and are associated with a marked decrease in fecal kynurenine (Kyn) levels. This suggests a link between the clinical outcome of dietary therapy and changes in tryptophan (TRP) metabolism. TRP is necessary for the formation of serotonin and melatonin. Alterations in serotonin-melatonin pathway were observed in colitis. Dietary TRP is also metabolized through the KYN pathway. KYN pathway metabolites such as KYN and quinolinic acid (QUIN) have been suggested to play a vital role in modulating the intestinal immune response. Here, we characterize the changes in fecal TRP metabolites induced by CDED+PEN or EEN and their association with remission.

Methods: We investigated the changes in 21 TRP metabolites (belonging to serotonin, KYN or indole pathways) in fecal samples from previously performed a 12-week prospective trial (Ghiboub et al, 2022) comparing two different nutritional therapies (CDED+PEN vs EEN) for remission induction in mild to moderate pediatric CD. After 6 weeks, the EEN group could return to a free diet with 25% of calories from PEN. The primary outcome was the tolerability to the dietary therapy. Secondary endpoints were intention-to-treat (ITT) remission at week (W)6 (defined by Pediatric CD Activity Index (PCDAI) ≤ 10) and corticosteroid-free ITT sustained remission at W12. TRP metabolites at week (W)0, W6 and W12 of 73 samples were measured by liquid chromatography coupled with high-resolution mass spectrometry. The data were analyzed according to clinical outcome groups of baselines (W0), induced remission (W06_rem), no-remission (W06_nr), sustained remission (W12_sr) and non-sustained remission (W12_nsr).

Results: In CDED+PEN, the drops in some components of KYN pathway such as KYN (P= 9.67E-4) and QUIN (P= 0.04) were associated with W06_rem, which were maintained in W12_sr (P= 0.003 and 0.02, respectively). In EEN, a significant decrease in QUIN was also associated with W06_rem (P= 0.02) and W12_sr (P= 0.03). Remarkably, serotonin pathway metabolites such as melatonin, N-acetyl-serotonin and 5-OH-tryptophan, were increased in samples from patients maintaining remission at W12 with both CDED+PEN and EEN. Importantly, in samples from patients failing to sustain remission, no significant changes were observed. The ratios of KYN/melatonin and QUIN/melatonin performed well as markers for remission.

Conclusion: The reduction in KYN pathway compounds and the increase in serotonin pathway compounds are associated with diet-induced and sustained remission. Further studies are warranted to assess causality and the association of these metabolites with specific diet and lifestyle factors, affecting sustained clinical remission.

Johan Van Limbergen

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