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Statistical Methods in Pre- and Clinical Drug Development: Tumour Growth-Inhibition Model Example

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Modelling of tumour-related outcomes to assess treatment efficacy applies in both pre- and clinical drug development. Stein et al. [2008] proposed a new paradigm to evaluate cancer therapy effectiveness in an early clinical drug development. The model decomposes the observed individual tumour measurements over time into two independent component processes of a constant exponential tumour growth/regrowth and regression (inhibition). The model was also found relevant in modelling pre-clinical in-vivo experimental data, establishing a novel approach in describing the observed tumour volume dynamics beyond a current practice. During the talk, the model pros and cons will be addressed with an example efficacy assessment of the Antibody Drug Conjugate (ADC) cancer therapies on a single study and database meta-analysis level.

This talk is part of the Cambridge Statistics Discussion Group (CSDG) series.

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