Evaluation of the Predictive Performance of Population Pharmacokinetic Models of Adalimumab in Patients with Inflammatory Bowel Disease

External Evaluation of Population Pharmacokinetic Models of Ustekinumab in Patients with Inflammatory Bowel Disease

BACKGROUND

Population pharmacokinetic (popPK) models are essential tools for optimizing ustekinumab (UST) dosing for the treatment of inflammatory bowel disease (IBD) through therapeutic drug monitoring. The external validation of these models is necessary to ensure their predictive performance and clinical utility. The aim of the study was to externally validate 4 published popPK models of UST in a real-world cohort of patients with IBD using prediction-based and simulation-based diagnostics, as well as Bayesian forecasting.

METHODS

Four popPK models of UST, identified through a systematic literature review, were evaluated using data from 99 patients with IBD and 374 serum UST concentrations. Predictive performance and Bayesian forecasting were assessed using statistical metrics, including mean prediction error, median prediction error (MDPE), and median absolute prediction error (MADPE). The acceptability criteria (MDPE ±20%, MADPE ≤30%, F20 ≥35%, and F30 ≥50%) were applied.

RESULTS

None of the models satisfied the predefined acceptability criteria. The Xu et al model demonstrated the best performance, achieving an MDPE of 19.55% and the lowest RMSPE (2.88 mcg/mL), but F20 (20.1%) and F30 (32.4%) values fell below thresholds. The model proposed by Adedokun et al showed strong results in simulation-based diagnostics, with only 5.6% of the observed concentrations outside the prediction interval.

CONCLUSIONS

The models developed by Xu et al and Adedokun et al exhibited the most promising predictive performance and potential clinical applicability for model-informed precision dosing. Refinements to these models and further research are required to enhance their use in personalized UST therapies for IBD.

A prediction method for the individual serum concentration and therapeutic effect for optimizing adalimumab therapy in inflammatory bowel disease

OBJECTIVES

Adalimumab (ADM) therapy is effective for inflammatory bowel disease (IBD), but a significant number of IBD patients lose response to ADM. Thus, it is crucial to devise methods to enhance ADM's effectiveness. This study introduces a strategy to predict individual serum concentrations and therapeutic effects to optimize ADM therapy for IBD during the induction phase.

METHODS

We predicted the individual serum concentration and therapeutic effect of ADM during the induction phase based on pharmacokinetic and pharmacodynamic (PK/PD) parameters calculated using the empirical Bayesian method. We then examined whether the predicted therapeutic effect, defined as clinical remission or treatment failure, matched the observed effect.

RESULTS

Data were obtained from 11 IBD patients. The therapeutic effect during maintenance therapy was successfully predicted at 40 of 47 time points. Moreover, the predicted effects at each patient's final time point matched the observed effects in 9 of the 11 patients.

CONCLUSION

This is the inaugural report predicting the individual serum concentration and therapeutic effect of ADM using the Bayesian method and PK/PD modelling during the induction phase. This strategy may aid in optimizing ADM therapy for IBD.

Therapeutic drug monitoring in inflammatory bowel diseases. Position statement of the Spanish Working Group on Crohn's Disease and Ulcerative Colitis

The treatment of inflammatory bowel disease has undergone a significant transformation following the introduction of biologic drugs. Thanks to these drugs, treatment goals have evolved from clinical response and remission to more ambitious objectives, such as endoscopic or radiologic remission. However, even though biologics are highly effective, a significant percentage of patients will not achieve an initial response or may lose it over time. We know that there is a direct relationship between the trough concentrations of the biologic and its therapeutic efficacy, with more demanding therapeutic goals requiring higher drug levels, and inadequate exposure being common. Therapeutic drug monitoring of biologic medications, along with pharmacokinetic models, provides us with the possibility of offering a personalized approach to treatment for patients with IBD. Over the past few years, relevant information has accumulated regarding its utility during or after induction, as well as in the maintenance of biologic treatment, in reactive or proactive strategies, and prior to withdrawal or treatment de-escalation. The aim of this document is to establish recommendations regarding the utility of therapeutic drug monitoring of biologics in patients with inflammatory bowel disease, in different clinical practice scenarios, and to identify areas where its utility is evident, promising, or controversial.

Population Pharmacokinetic Model of Adalimumab Based on Prior Information Using Real World Data

Adalimumab is a fully human monoclonal antibody used for the treatment of inflammatory bowel disease (IBD). Due to its considerably variable pharmacokinetics and the risk of developing antibodies against adalimumab, it is highly recommended to use a model-informed precision dosing approach. The aim of this study is to develop a population pharmacokinetic (PopPK) model of adalimumab for patients with IBD based on a literature model (reference model) to be used in the clinical setting. A retrospective observational study with 54 IBD patients was used to develop two different PopPK models based on the reference model. One of the developed models estimated the pharmacokinetic population parameters (estimated model), and the other model incorporated informative priors (prior model). The models were evaluated with bias and imprecision. Clinical impact was also assessed, evaluating the differences in dose interventions. The developed models included the albumin as a continuous covariate on apparent clearance. The prior model was superior to the estimated model in terms of bias, imprecision and clinical impact on the target population. In conclusion, the prior model adequately characterized adalimumab PK in the studied population and was better than the reference model in terms of predictive performance and clinical impact.

Assessing the Impact of Immunogenicity and Improving Prediction of Trough Concentrations: Population Pharmacokinetic Modeling of Adalimumab in Patients with Crohn's Disease and Ulcerative Colitis

BACKGROUND AND OBJECTIVE

Predicting adalimumab pharmacokinetics (PK) for patients impacted by anti-drug antibodies (ADA) has been challenging. The present study assessed the performance of the adalimumab immunogenicity assays in predicting which patients with Crohn's disease (CD) and ulcerative colitis (UC) have low adalimumab trough concentrations; and aimed to improve predictive performance of adalimumab population PK (popPK) model in CD and UC patients whose PK was impacted by ADA.

METHODS

Adalimumab PK and immunogenicity data obtained from 1459 patients in SERENE CD (NCT02065570) and SERENE UC (NCT02065622) were analyzed. Adalimumab immunogenicity was assessed using electrochemiluminescence (ECL) and enzyme-linked immunosorbent (ELISA) assays. From these assays, three analytical approaches (ELISA concentrations, titer, and signal-to-noise [S/N] measurements) were tested as predictors for classifying patients with/without low concentrations potentially affected by immunogenicity. The performance of different thresholds for these analytical procedures was assessed using receiver operating characteristic curves and precision-recall curves. Based on the results from the most sensitive immunogenicity analytical procedure, patients were classified into PK-not-ADA-impacted and PK-ADA-impacted subpopulations. Stepwise popPK modeling was implemented to fit the PK data to an empirical adalimumab two-compartment model with linear elimination and ADA delay compartments to account for the time delay to generate ADA. Model performance was assessed by visual predictive checks and goodness-of-fit plots.

RESULTS

The classical ELISA-based classification (with 20 ng/mL ADA as lower threshold) showed a good balance of precision and recall, to determine which patients had at least 30% adalimumab concentrations below 1 µg/mL. Titer-based classification with the lower limit of quantitation (LLOQ) as threshold showed higher sensitivity to classify these patients compared to the ELISA-based approach. Therefore, patients were classified as PK-ADA-impacted or PK-not-ADA impacted using the LLOQ titer threshold. In the stepwise modeling approach ADA-independent parameters were first fit using PK data from titer-PK-not-ADA-impacted population. The identified ADA-independent covariates included the effect of indication, weight, baseline fecal calprotectin, baseline C-reactive protein, baseline albumin on clearance; and sex and weight on volume of distribution of the central compartment. Pharmacokinetic-ADA-driven dynamics were characterized using PK data for the PK-ADA-impacted population. The categorical covariate based on the ELISA classification was the best at describing the additional effect of immunogenicity analytical approaches on ADA synthesis rate. The model was able to adequately describe the central tendency and variability for PK-ADA-impacted CD/UC patients.

CONCLUSIONS

The ELISA assay was found to be optimal for capturing impact of ADA on PK. The developed adalimumab popPK model is robust in predicting PK profiles for CD and UC patients whose PK was impacted by ADA.

Model-Informed Precision Dosing (MIPD)

Model-informed precision dosing (MIPD) is an advanced quantitative approach focusing on individualized dosage optimization, integrating complex mathematical and statistical models of drugs and disease combined with individual demographic and clinical patient characteristics [...].

Cost-Effectiveness of Therapeutic Drug Monitoring of Anti-TNF Therapy in Inflammatory Bowel Disease: A Systematic Review

Infliximab and adalimumab are monoclonal antibodies against tumor necrosis factor (anti-TNF) used to manage inflammatory bowel disease (IBD). Therapeutic Drug Monitoring (TDM) has been proven to prevent immunogenicity, to achieve better long-term clinical results and to save costs in IBD treatment. The aim of this study was to conduct a systematic review on cost-effectiveness analyses of studies that apply TDM of anti-TNF in IBD and to provide a critical analysis of the best scientific knowledge available in the literature. The quality of the included studies was assessed using Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Cost-effectiveness of the TDM strategies was presented as total costs, cost savings, quality-adjusted life-years (QALY) and incremental cost-effectiveness ratio (ICER). Thirteen studies that examined the health economics of TDM of anti-TNF in IBD from 2013 to 2021 were included. Eight of them (61.5%) achieved a score between 17 and 23 on the CHEERS checklist. The comparison between the TDM strategy and an empirical strategy was cost saving. The ICER between reactive TDM and an empirical strategy was dominated (favorable) by reactive TDM, whereas the ICER value for proactive TDM compared to an empirical strategy ranged from EUR 56,845 to 3,901,554. This systematic review demonstrated that a TDM strategy is cost-effective or cost-saving in IBD.