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Predicting efficacy assessment of combined treatment of radiotherapy and nivolumab for NSCLC patients through virtual clinical trials using QSP modeling

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Abstract

Non-Small Cell Lung Cancer (NSCLC) remains one of the main causes of cancer death worldwide. In the urge of finding an effective approach to treat cancer, enormous therapeutic targets and treatment combinations are explored in clinical studies, which are not only costly, suffer from a shortage of participants, but also unable to explore all prospective therapeutic solutions. Within the evolving therapeutic landscape, the combined use of radiotherapy (RT) and checkpoint inhibitors (ICIs) emerged as a promising avenue. Exploiting the power of quantitative system pharmacology (QSP), we undertook a study to anticipate the therapeutic outcomes of these interventions, aiming to address the limitations of clinical trials. After enhancing a pre-existing QSP platform and accurately replicating clinical data outcomes, we conducted an in-depth study, examining different treatment protocols with nivolumab and RT, both as monotherapy and in combination, by assessing their efficacy through clinical endpoints, namely time to progression (TTP) and duration of response (DOR). As result, the synergy of combined protocols showcased enhanced TTP and extended DOR, suggesting dual advantages of extended response and slowed disease progression with certain combined regimens. Through the lens of QSP modeling, our findings highlight the potential to fine-tune combination therapies for NSCLC, thereby providing pivotal insights for tailoring patient-centric therapeutic interventions.

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Acknowledgements

M.S. received the Bourse du centenaire from the Faculté de Pharmacie, Université de Montréal. Support was also provided by NSERC (Collaborative Research and Development Grants), in partnership with Syneos Health and Pfizer; FRQNT-Projet d’équipe, and from Prompt.

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Authors and Affiliations

  1. Laboratoire de recherche en pharmacométrie, Faculté de pharmacie, Université de Montréal, Montreal, Canada

    Miriam Schirru, Hamza Charef, Khalil-Elmehdi Ismaili, Frédérique Fenneteau & Fahima Nekka

  2. Clinical Pharmacology, Syneos Health, Quebec, Quebec G1P 0A2, Canada

    Didier Zugaj & Pierre-Olivier Tremblay

  3. Centre de recherches mathématiques (CRM), Université de Montréal, Montreal, Canada

    Fahima Nekka

  4. Centre for Applied Mathematics in Bioscience and Medicine (CAMBAM), McGill University, Montreal, Canada

    Fahima Nekka

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  1. Miriam Schirru
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Contributions

Conceptualization: M.S., D.Z., P.-O.T., F.N.; Methodology: M.S., H.C., D.Z., F.F., F.N.; Code development and simulations: M.S., D.Z.; Investigation: M.S., H.C., D.Z.; Data acquisition: M.S., K.-E.I., H.C.; Funding acquisition: F.N., P.-O.T.; Writing—original draft: M.S.; Writing—review & editing: M.S., F.F., D.Z., F,N.; Supervision: F.N., F.F., D.Z.. All authors reviewed and authorized the manuscript.

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Correspondence to Miriam Schirru.

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Schirru, M., Charef, H., Ismaili, KE. et al. Predicting efficacy assessment of combined treatment of radiotherapy and nivolumab for NSCLC patients through virtual clinical trials using QSP modeling. J Pharmacokinet Pharmacodyn (2024). https://doi.org/10.1007/s10928-024-09903-0

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