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Translational Therapeutics

Support to early clinical decisions in drug development and personalised medicine with checkpoint inhibitors using dynamic biomarker-overall survival models

British Journal of Cancer volume 129, pages 1383–1388 (2023)Cite this article

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Abstract

Longitudinal models of biomarkers such as tumour size dynamics capture treatment efficacy and predict treatment outcome (overall survival) of a variety of anticancer therapies, including chemotherapies, targeted therapies, immunotherapies and their combinations. These pharmacological endpoints like tumour dynamic (tumour growth inhibition) metrics have been proposed as alternative endpoints to complement the classical RECIST endpoints (objective response rate, progression-free survival) to support early decisions both at the study level in drug development as well as at the patients level in personalised therapy with checkpoint inhibitors. This perspective paper presents recent developments and future directions to enable wider and robust use of model-based decision frameworks based on pharmacological endpoints.

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Fig. 1: Tumour dynamic link functions (orange) and RECIST endpoints (blue) to support clinical early decisions.
Fig. 2: Illustration of SLD kinetics and survival probability predictions in 1 individual.

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Authors and Affiliations

  1. Clinical Pharmacology, Genentech-Roche, Marseille, France

    René Bruno

  2. Clinical Pharmacology, Genentech-Roche, Lyon, France

    Pascal Chanu

  3. Clinical Pharmacology, Genentech-Roche, Solna, Sweden

    Matts Kågedal

  4. Biostatistics, Roche, Basel, Switzerland

    Francois Mercier & Ulrich Beyer

  5. Clinical Pharmacology, Genentech, South San Francisco, CA, USA

    Kenta Yoshida, Chunze Li & Jin Y. Jin

  6. Université Paris Cité, IAME, INSERM, Paris, France

    Jérémie Guedj

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RB, PC, MK, FM and KY wrote the manuscript. All authors reviewed and edited the manuscript. All authors approved the version to be published.

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Bruno, R., Chanu, P., Kågedal, M. et al. Support to early clinical decisions in drug development and personalised medicine with checkpoint inhibitors using dynamic biomarker-overall survival models. Br J Cancer 129, 1383–1388 (2023). https://doi.org/10.1038/s41416-023-02190-5

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