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Biotechnology industry is at the heart of the fast-growing knowledge-based economy. One of the distinguishing characteristics of biotech industry is clustering. A cluster, like an organism, will experience origin, growth, and decline/reorientation. Our study constructs a framework to analyze biotech clusters with different origins,“spontaneous and policy-driven”, through their life cycles. We use Bay Area in the United States and Shanghai Zhangjiang Hi-Tech Park in China as two cases to represent spontaneous and policy-driven biotech clusters. This study fills the gap of previous literature by providing a side-by-side comparison between two types of biotech clusters in the evolutionary process. Drawing from two cases, the success factors both biotech clusters own are human capital and financial capital, but the underlying forces for formatting and providing these factors are different. The fundamental difference between two cases lays on entrepreneurship, social capital and network patterns. Moreover, social capital and the accompanying networks are main factors shape a cluster’s configuration. It is essential to know the dynamics and essence of different types of clusters for both policy makers and academic researchers.