External Model Performance Evaluation of Twelve Infliximab Population Pharmacokinetic Models in Patients with Inflammatory Bowel Disease

The Influence of Subclinical Active Inflammation on IFX Pharmacokinetic Modeling and Disease Progression Assessment: Findings from a Prospective Real-World Study in Inflammatory Bowel Disease Patients

BACKGROUND AND AIMS

Effective management of inflammatory bowel disease (IBD) relies on a comprehensive understanding of infliximab (IFX) pharmacokinetics (PK). This study's primary goal was to develop a robust PK model, identifying key covariates influencing IFX clearance (CL), while concurrently evaluating the risk of disease progression during the maintenance phase of IBD treatment.

METHODS

The multicenter, prospective, real-world DIRECT study was conducted in several care centers, which included 369 IBD patients in the maintenance phase of IFX therapy. A two-compartment population PK model was used to determine IFX CL and covariates. Logistic and Cox regressions were applied to elucidate the associations between disease progression and covariates embedded in the PK model.

RESULTS

The PK model included the contributions of weight, albumin, antidrug antibody (ADA), and fecal calprotectin (FC). On average, higher ADA, FC concentration and weight, and lower albumin concentration resulted in higher IFX CL. In the multivariate regression analyses, FC levels influenced the odds of disease progression in the majority of its definitions, when adjusted for several confounding factors. Additionally, alongside FC, both IFX and CL demonstrated a significant impact on the temporal aspect of disease progression.

CONCLUSION

In this 2-year real-world study, readily available clinical covariates, notably FC, significantly impacted IFX availability in IBD patients. We demonstrated that subclinical active inflammation, as mirrored by FC or CRP, substantially influenced IFX clearance. Importantly, FC emerged as a pivotal determinant, not only of IFX pharmacokinetics but also of disease progression. These findings underscore the need to integrate FC into forthcoming IFX pharmacokinetic models, amplifying its clinical significance.

Best Practice for Therapeutic Drug Monitoring of Infliximab: Position Statement from the International Association of Therapeutic Drug Monitoring and Clinical Toxicology

BACKGROUND

Infliximab, an anti-tumor necrosis factor monoclonal antibody, has revolutionized the pharmacological management of immune-mediated inflammatory diseases (IMIDs). This position statement critically reviews and examines existing data on therapeutic drug monitoring (TDM) of infliximab in patients with IMIDs. It provides a practical guide on implementing TDM in current clinical practices and outlines priority areas for future research.

METHODS

The endorsing TDM of Biologics and Pharmacometrics Committees of the International Association of TDM and Clinical Toxicology collaborated to create this position statement.

RESULTS

Accumulating data support the evidence for TDM of infliximab in the treatment of inflammatory bowel diseases, with limited investigation in other IMIDs. A universal approach to TDM may not fully realize the benefits of improving therapeutic outcomes. Patients at risk for increased infliximab clearance, particularly with a proactive strategy, stand to gain the most from TDM. Personalized exposure targets based on therapeutic goals, patient phenotype, and infliximab administration route are recommended. Rapid assays and home sampling strategies offer flexibility for point-of-care TDM. Ongoing studies on model-informed precision dosing in inflammatory bowel disease will help assess the additional value of precision dosing software tools. Patient education and empowerment, and electronic health record-integrated TDM solutions will facilitate routine TDM implementation. Although optimization of therapeutic effectiveness is a primary focus, the cost-reducing potential of TDM also merits consideration.

CONCLUSIONS

Successful implementation of TDM for infliximab necessitates interdisciplinary collaboration among clinicians, hospital pharmacists, and (quantitative) clinical pharmacologists to ensure an efficient research trajectory.

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.

The Effect of Polymorphisms and Other Biomarkers on Infliximab Exposure in Paediatric Inflammatory Bowel Disease: Development of a Population Pharmacokinetic Model

BACKGROUND

Therapeutic drug monitoring (TDM) of infliximab has been shown to be a effective strategy for inflammatory bowel disease (IBD). Population pharmacokinetic (PopPK) modeling can predict trough concentrations for individualized dosing.

OBJECTIVE

The aim of this study was to develop a PopPK model of infliximab in a paediatric population with IBD, assessing the effect of single nucleotide polymorphisms (SNPs) and other biomarkers on infliximab clearance.

METHODS

This observational and ambispective single-centre study was conducted in paediatric patients with IBD treated with infliximab between July 2016 and July 2022 in the Paediatric Gastroenterology Service of the Hospital Universitari Vall d'Hebron (HUVH) (Spain). Demographic, clinical, and analytical variables were collected. Twenty SNPs potentially associated with variations in the response to infliximab plasma concentrations were analysed. infliximab serum concentrations and antibodies to infliximab (ATI) were determined by ELISA. PopPK modelling was performed using nonlinear mixed-effects analysis (NONMEM).

RESULTS

Thirty patients (21 males) were included. The median age (range) at the start of infliximab treatment was 13 years (16 months to 16 years). A total of 190 samples were obtained for model development (49 [25.8%] during the induction phase). The pharmacokinetics (PK) of infliximab were described using a two-compartment model. Weight, erythrocyte sedimentation rate (ESR), faecal calprotectin (FC), and the SNP rs1048610 (ADAM17) showed statistical significance for clearance (CL), and albumin for inter-compartmental clearance (Q). Estimates of CL1 (genotype 1-AA), CL2 (genotype 2-AG), CL3 (genotype 3-GG), Q, Vc, and Vp (central and peripheral distribution volumes) were 0.0066 L/h/46.4 kg, 0.0055 L/h/46.4 kg, 0.0081 L/h/46.4 kg, 0.0029 L/h/46.4 kg, 0.6750 L/46.4 kg, and 1.19 L/46.4 kg, respectively. The interindividual variability (IIV) estimates for clearance, Vc, and Vp were 19.33, 16.42, and 36.02%, respectively.

CONCLUSIONS

A popPK model utilising weight, albumin, FC, ESR, and the SNP rs1048610 accurately predicted infliximab trough concentrations in children with IBD.

A systematic evaluation of population pharmacokinetic models for polymyxin B in patients with liver and/or kidney dysfunction

Polymyxin B (PMB) is considered a last-line treatment for multidrug-resistant (MDR) gram-negative bacterial infections. Model-informed precision dosing with population pharmacokinetics (PopPK) models could help to individualize PMB dosing regimens and improve therapy. However, the external prediction ability of the established PopPK models has not been fully elaborated. This study aimed to systemically evaluate eleven PMB PopPK models from ten published literature based on a new independent population, which was divided into four different populations, patients with liver dysfunction, kidney dysfunction, liver and kidney dysfunction, and normal liver and kidney function. The whole data set consisted of 146 patients with 391 PMB concentrations. The prediction- and simulation-based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. In the overall evaluation process, none of the models exhibited satisfactory predictive ability in both prediction- and simulation-based diagnostic simultaneously. However, the evaluation of the models in the subgroup of patients with normal liver and kidney function revealed improved predictive performance compared to those with liver and/or kidney dysfunction. Bayesian forecasting demonstrated enhanced predictability with the incorporation of two to three prior observations. The external evaluation highlighted a lack of consistency between the prediction results of published models and the external validation dataset. Nonetheless, Bayesian forecasting holds promise in improving the predictive performance of the models, and feedback from therapeutic drug monitoring is crucial in optimizing individual dosing regimens.

Antibody Drug Clearance: An Underexplored Marker of Outcomes with Checkpoint Inhibitors

Immune-checkpoint inhibitor (ICI) therapy has dramatically changed the clinical landscape for several cancers, and ICI use continues to expand across many cancer types. Low baseline clearance (CL) and/or a large reduction of CL during treatment correlates with better clinical response and longer survival. Similar phenomena have also been reported with other monoclonal antibodies (mAb) in cancer and other diseases, highlighting a characteristic of mAb clinical pharmacology that is potentially shared among various mAbs and diseases. Though tempting to attribute poor outcomes to low drug exposure and arguably low target engagement due to high CL, such speculation is not supported by the relatively flat exposure-response relationship of most ICIs, where a higher dose or exposure is not likely to provide additional benefit. Instead, an elevated and/or increasing CL could be a surrogate marker of the inherent resistant phenotype that cannot be reversed by maximizing drug exposure. The mechanisms connecting ICI clearance, therapeutic efficacy, and resistance are unclear and likely to be multifactorial. Therefore, to explore the potential of ICI CL as an early marker for efficacy, this review highlights the similarities and differences of CL characteristics and CL-response relationships for all FDA-approved ICIs, and we compare and contrast these to selected non-ICI mAbs. We also discuss underlying mechanisms that potentially link mAb CL with efficacy and highlight existing knowledge gaps and future directions where more clinical and preclinical investigations are warranted to clearly understand the value of baseline and/or time-varying CL in predicting response to ICI-based therapeutics.

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.

External validation of population pharmacokinetic models of gentamicin in paediatric population from preterm newborns to adolescents

The aim of this study was to externally validate the predictive performance of published population pharmacokinetic models of gentamicin in all paediatric age groups, from preterm newborns to adolescents. We first selected published population pharmacokinetic models of gentamicin developed in the paediatric population with a wide age range. The parameters of the literature models were then re-estimated using the PRIOR subroutine in NONMEM^®. The predictive ability of the literature and the tweaked models was evaluated. Retrospectively collected data from a routine clinical practice (512 concentrations from 308 patients) were used for validation. The models with covariates characterising developmental changes in clearance and volume of distribution had better predictive performance, which improved further after re-estimation. The tweaked model by Wang 2019 performed best, with suitable accuracy and precision across the complete paediatric population. For patients treated in the intensive care unit, a lower proportion of patients would be expected to reach the target trough concentration at standard dosing. The selected model could be used for model-informed precision dosing in clinical settings where the entire paediatric population is treated. However, for use in clinical practice, the next step should include additional analysis of the impact of intensive care treatment on gentamicin pharmacokinetics, followed by prospective validation.

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 [...].

Saudi Arabia consensus guidance for the diagnosis and management of adults with inflammatory bowel disease

Optimal management of inflammatory bowel disease (IBD) relies on a clear understanding and tailoring evidence-based interventions by clinicians in partnership with patients. This article provides concise guidelines for the management of IBD in adults, based on the most up-to-date information at the time of writing and will be regularly updated. These guidelines were developed by the Saudi Ministry of Health in collaboration with the Saudi Gastroenterology Association and the Saudi Society of Clinical Pharmacy. After an extensive literature review, 78 evidence-and expert opinion-based recommendations for diagnosing and treating ulcerative colitis and Crohn's disease in adults were proposed and further refined by a voting process. The consensus guidelines include the finally agreed on statements with their level of evidence covering different aspects of IBD diagnosis and treatment.

Ulcerative Colitis and Acute Severe Ulcerative Colitis Patients Are Overlooked in Infliximab Population Pharmacokinetic Models: Results from a Comprehensive Review

Ulcerative colitis (UC) is part of the inflammatory bowels diseases, and moderate to severe UC patients can be treated with anti-tumour necrosis α monoclonal antibodies, including infliximab (IFX). Even though treatment of UC patients by IFX has been in place for over a decade, many gaps in modelling of IFX PK in this population remain. This is even more true for acute severe UC (ASUC) patients for which early prediction of IFX pharmacokinetic (PK) could highly improve treatment outcome. Thus, this review aims to compile and analyse published population PK models of IFX in UC and ASUC patients, and to assess the current knowledge on disease activity impact on IFX PK. For this, a semi-systematic literature search was conducted, from which 26 publications including a population PK model analysis of UC patients receiving IFX therapy were selected. Amongst those, only four developed a model specifically for UC patients, and only three populations included severe UC patients. Investigations of disease activity impact on PK were reported in only 4 of the 14 models selected. In addition, the lack of reported model codes and assessment of predictive performance make the use of published models in a clinical setting challenging. Thus, more comprehensive investigation of PK in UC and ASUC is needed as well as more adequate reports on developed models and their evaluation in order to apply them in a clinical setting.

Multi‐model averaging improves the performance of model‐guided infliximab dosing in patients with inflammatory bowel diseases

Infliximab dosage de‐escalation without prior knowledge of drug concentrations may put patients at risk for underexposure and trigger the loss of response. A single‐model approach for model‐informed precision dosing during infliximab maintenance therapy has proven its clinical benefit in patients with inflammatory bowel diseases. We evaluated the predictive performances of two multi‐model approaches, a model selection algorithm and a model averaging algorithm, using 18 published population pharmacokinetic models of infliximab for guiding dosage de‐escalation. Data of 54 patients with Crohn’s disease and ulcerative colitis who underwent infliximab dosage de‐escalation after an earlier escalation were used. A priori prediction (based solely on covariate data) and maximum a posteriori prediction (based on covariate data and trough concentrations) were compared using accuracy and precision metrics and the classification accuracy at the trough concentration target of 5.0 mg/L. A priori prediction was inaccurate and imprecise, with the lowest classification accuracies irrespective of the approach (median 59%, interquartile range 59%–63%). Using the maximum a posteriori prediction, the model averaging algorithm had systematically better predictive performance than the model selection algorithm or the single‐model approach with any model, regardless of the number of concentration data. Only a single trough concentration (preferably at the point of care) sufficed for accurate and precise prediction. Predictive performance of both single‐ and multi‐model approaches was robust to the lack of covariate data. Model averaging using four models demonstrated similar predictive performance with a five‐fold shorter computation time. This model averaging algorithm was implemented in the TDMx software tool to guide infliximab dosage de‐escalation in the forthcoming prospective MODIFI study (NCT04982172).