Cancer Biology
Overall Survival (OS) is regarded as the most trustworthy and preferred endpoint in oncology trials to evaluate drug treatment benefits. In order to speed up and streamline the development of clinical oncology drugs, it is critical to identify the dynamic effects and connections between the various variables collected from patients for a given drug and its indication. Due to temporal differences, drug-induced effects and causal relationships can be difficult to interpret. Parametric time-to-event models and population pharmacokinetic– pharmacodynamic modeling are increasingly being used to address this issue.
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