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

Schräpel, Christina; Kovar, Lukas; Selzer, Dominik; Hofmann, Ute; Tran, Florian; Reinisch, Walter; Schwab, Matthias; Lehr, Thorsten

doi:10.3390/pharmaceutics13091368

Cited by 17 publications

(13 citation statements)

References 69 publications

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“…Currently, there is no well‐established target of classification accuracy for MIPD approach. To the best of our knowledge, classification accuracy has only been included for model predictive performance evaluation for infliximab in Schräpel et al 32 Therefore, defining clinical relevance of these additional analysis tools still requires further investigation to facilitate the translation and appropriate use of the MIPD approaches in clinical care. Third, we also scrutinized the importance of utilizing point‐of‐care testing and the availability of covariate data on the predictive performances.…”

Section: Discussionmentioning

confidence: 99%

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

Kantasiripitak

Outtier

Wicha

et al. 2022

CPT Pharmacom & Syst Pharma

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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 multimodel 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).

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Section: Discussionmentioning

confidence: 99%

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

Kantasiripitak

Outtier

Wicha

et al. 2022

CPT Pharmacom & Syst Pharma

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“…The sparse concentration measurements in our study precluded the development of an original PK model. Therefore, we evaluated the usefulness of published population PK models for cisplatin in SCLC, by adopting the approach that was recently shown beneficial in informing treatment with other drugs, such as anti-infectives (vancomycin, meropenem, polymyxin B), monoclonal antibodies (infliximab, adalimumab), and imatinib, among others [25,27,28,[34][35][36][37]. In addition, we used informative priors and $PRIOR subroutine in NONMEM, which was demonstrated to produce improved predictive performance of the PK models on sparse datasets, on the population (a priori) and individual (a posteriori) level [29].…”

Section: Discussionmentioning

confidence: 99%

“…Possible errors in the sampling and infusion time documentation in the early phase could further contribute to higher bias and imprecision, since a recent study demonstrated that even 5 min inaccuracies affect the estimation of volume of distribution in central and peripheral compartment, as well as the intercompartmental clearance [42]. However, the choice of the robust predictive performance parameters (SSPB and ζ) to assess the bias and precision mitigated the outlying error values and possible data inaccuracies in the early phase [33,34].…”

Section: Discussionmentioning

confidence: 99%

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Population pharmacokinetics of cisplatin in small cell lung cancer patients guided with informative priors

Zdovc

Vaupotič

Marolt

et al. 2022

Cancer Chemother Pharmacol

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Purpose Cisplatin-etoposide treatment is recommended as a first line in small cell lung cancer patients (SCLC). However, the prognosis is poor and the dosing is not tailored beyond the body surface area, which is related with indeterminate cisplatin exposure-response relationship. We aimed to evaluate cisplatin pharmacokinetics (PK) and the exposure to unbound cisplatin in SCLC patients using the informative priors, and assess the relationship between the cisplatin exposure and probability of neutropenia. Methods Observational clinical study was performed including 17 cisplatin-treated SCLC patients. External population cisplatin PK models were identified and NONMEM ® software and $PRIOR subroutine were used for the model evaluation. The bias and precision of the model-predicted cisplatin concentrations were evaluated. The best models were combined in a final model including several sets of informative priors, which was used to estimate individual cisplatin exposure, analyze the relationship between the exposure and neutropenia and simulate several cisplatin dosing regimens in a virtual patient cohort. ResultsThe models by Urien with the informative priors best fitted the data. The individual cisplatin exposure ranged between 2430 and 4560 μg*h/L. There was a trend of increasing probability of neutropenia and febrile neutropenia with increasing cisplatin exposure. Approximately 50%, 75% and 90% of patients receiving 60 mg/m 2 , 70 mg/m 2 and 80 mg/m 2 , respectively, achieved the previously identified exposure threshold of 2860 μg*h/L. Conclusion We developed a tool to individualize cisplatin dosing based on the estimated probability of neutropenia. The benefit of more intense dosing regimens in SCLC patients should be further assessed.

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“…In the selected articles, only two models took ADA into account in a more mechanistic way, seeking to implement immunogenicity impact on clearance and improving model predictions [ 38 , 52 ]. In general, as shown by Schräpel et al, poor predictions are observed for ADA-positive patients compared to ADA-negative in most developed models [ 61 ]. Thus, implementation of more mechanistic models, accounting for the impact of ADA development on PK, as well as on pharmacodynamics, could improve the therapeutic management of ADA-positive patients.…”

Section: Discussion and Perspectivesmentioning

confidence: 99%

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

et al. 2022

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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.

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

Cited by 17 publications

References 69 publications

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

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

Population pharmacokinetics of cisplatin in small cell lung cancer patients guided with informative priors

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

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