Queueing network modelling and lead time compression of pharmaceutical drug development

Abstract

Designing an optimized pharmaceutical drug development process is an important problem in itself and is of significant practical and research interest. Drug development lead time is a critical performance metric for a pharmaceutical company. In this paper, we develop a multiclass queueing network model to capture the project dynamics in drug development organizations that involve multiple, concurrent projects with contention for human/technical resources. We explore how drug development lead times can be reduced using efficient scheduling and critical mass-based resource management. The model captures important facets of any typical drug development organization, such as concurrent execution of multiple projects, contention for resources, feedback and reworking of project tasks, variability of new project initiations and task execution times, and certain scheduling issues. First, we show, using a class of fluctuation smoothing scheduling policies, that development lead times can be compressed impressively, without having to commit additional resources. Next, we show that critical mass-based project teams can compress lead times further. The model presented, though stylized, is sufficiently generic and conceptual, and will be of much value in new drug development project planning and management.