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. 2025 Oct;64(10):1507-1515.
doi: 10.1007/s40262-025-01555-8. Epub 2025 Jul 25.

TDM-Based Tailored Dosing of Durvalumab in Lung Cancer Patients: A Comprehensive Population Pharmacokinetic-Pharmacoeconomic Evaluation

Fenna de Vries  1   2 , Eric J F Franssen  3 , Arthur A J Smit  4 , Dirk Jan A R Moes  5 , Anthonie J van der Wekken  6 , Thijs Oude Munnink  7 , Jeroen J M A Hendrikx  8 , Daphne W Dumoulin  9 , Stijn L W Koolen  10   11 , Wietske Kievit  12 , Michel M van den Heuvel  13   14 , Rob Ter Heine  15
Affiliations

TDM-Based Tailored Dosing of Durvalumab in Lung Cancer Patients: A Comprehensive Population Pharmacokinetic-Pharmacoeconomic Evaluation

Fenna de Vries et al. Clin Pharmacokinet. 2025 Oct.

Abstract

Background: The increasing use of immune checkpoint inhibitors, such as durvalumab, places a significant financial burden on healthcare systems, strains hospital capacities, and contributes to environmental concerns.

Objective: We aimed to develop alternative dosing strategies to optimize durvalumab administration, reduce unnecessary drug use, and ensure sustainable cancer care without sacrificing efficacy.

Methods: Using the population pharmacokinetic model developed by the licensing holder, we designed two alternative dosing strategies for non-small cell lung cancer based on therapeutic drug monitoring. Adjustments were made to the dose or administration interval, following regulatory standards for in silico dose optimization. A pharmacoeconomic evaluation was conducted to estimate potential cost savings from a medical perspective.

Results: Both alternative strategies achieved high exposure levels, with 98.1-99.0% of patients exceeding a predefined efficacy target, surpassing the 95.4% predicted by the license holder for the approved 10 mg/kg 2-weekly regimen. They also reduced overall drug exposure by 7-24% and eliminated drug wastage, resulting in an average annual cost reduction of €25,163 (22.9%) per patient.

Conclusion: Therapeutic drug monitoring-guided adjustments for durvalumab offer a potentially cost-saving way to optimize drug use, reduce healthcare burdens, and lessen environmental impact while ensuring adequate patient exposure. Our proposal's evidence provides a solid basis for a non-inferiority study.

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Conflict of interest statement

Declarations. Conflict of interest: Financial interest: A.v.d.W. has relationships with AstraZeneca, Boehringer Ingelheim GmbH, Pfizer Inc, F. Hoffmann-La Roche Ltd, Takeda Oncology, Bristol Myers Squibb Co., and Eli Lilly and Company, involving consulting, advisory roles, funding grants, and speaking fees. D.D. has consulting and speaking engagements with Bristol Myers Squibb Co., Merck & Co. Inc., AstraZeneca, Roche, and Pfizer. M.v.d.H. received financial support from the Radboudumc Department of Respiratory Diseases. The parties of interest had no role in the study’s design, data collection, analysis, interpretation, manuscript writing, or the decision to publish. Non-financial interest: A.v.d.W. holds a fiduciary role on the board of the ROS1ders advocacy group. R.t.H. is affiliated with Radboud University Medical Center. The parties of interest had no role in the study’s design, data collection, analysis, interpretation, manuscript writing, or the decision to publish. Editorial Board membership: D.M. is an editorial board member of Clinical Pharmacokinetics. D.M. was not involved in the selection of peer reviewers for the manuscript nor any of the subsequent editorial decisions. No interest: The remaining authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Code availability: The population pharmacokinetic model code is included as Supplementary Information. Funding: No funds, grants, or other support was received. Data availability: Data is included as Supplementary Information. Author contributions: F. de Vries: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Validation, Writing—original draft. E.J.F. Franssen: Conceptualization, Supervision, Resources, Writing—review and editing. A.A.J. Smit: Conceptualization, Writing—review and editing. D.J.A.R. Moes: Writing—review and editing. A.J. van der Wekken: Writing—review and editing. T. Oude Munnink: Writing—review and editing. J.J.M.A. Hendrix: Writing—review and editing. D.W. Dumoulin: Writing—review and editing. S.L.W. Koolen: Writing—review and editing. W. Kievit: Methodology, Writing—review and editing. M.M. van den Heuvel: Conceptualization, Writing—review and editing. R. ter Heine: Conceptualization, Methodology, Supervision, Resources, Writing—original draft. All authors have provided their formal approval for this submission.

Figures

Fig. 1
Fig. 1
Levels of durvalumab per dosing strategy. (A) The evolution of durvalumab trough levels over a full year of treatment for each dosing strategy. (B) The distribution of steady-state trough levels for each dosing strategy. The solid line represents the median level, while the shaded areas indicate the interquartile range (A). The horizontal line at 53.3 µg/mL indicates the threshold level for efficacy (A and B). TDM therapeutic drug monitoring
Fig. 2
Fig. 2
Cost trajectory per dosing strategy. The solid lines represent the mean treatment costs over time, the shaded area represents the 95% confidence interval, and the vertical dashed lines represent the mean and maximum treatment duration. TDM therapeutic drug monitoring
Fig. 3
Fig. 3
Cost differences per treatment component per patient between TDM-based dosing strategies and licensed dosing regimens. Comparison of costs between TDM-based strategies and the 10-mg/kg every 2 weeks regimen at (A) 8 months and (B) 12 months, as well as between TDM-based strategies and the 1500-mg every 4 weeks regimen at (C) 8 months and (D) 12 months. TDM therapeutic drug monitoring
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