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

René BrunoPascal ChanuMatts KågedalFrancois MercierKenta YoshidaJérémie GuedjChunze LiUlrich BeyerJin Y Jin
Published in: British journal of cancer (2023)
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.
Keyphrases
  • free survival
  • dna damage
  • cell cycle
  • ejection fraction
  • newly diagnosed
  • bone marrow
  • current status
  • decision making
  • combination therapy