Queueing network modelling and lead time compression of pharmaceutical drug development

Designing an optimized pharmaceutical drug development process is an import ant problem in itself and is of significant practical and research interest . Drug development lead time is a critical performance metric for a pharmac eutical company. In this paper, we develop a multiclass queueing network mo del to capture the project dynamics in drug development organizations that involve multiple, concurrent projects with contention for human/technical r esources. We explore how drug development lead times can be reduced using e fficient scheduling and critical mass-based resource management. The model captures important facets of any typical drug development organization, suc h as concurrent execution of multiple projects, contention for resources, f eedback and reworking of project tasks, variability of new project initiati ons and task execution times, and certain scheduling issues. First, we show , using a class of fluctuation smoothing scheduling policies, that developm ent lead times can be compressed impressively, without having to commit add itional resources. Next, we show that critical mass-based project teams can compress lead times further. The model presented, though stylized, is suff iciently generic and conceptual, and will be of much value in new drug deve lopment project planning and management.