Optimal Embeddedness and Governance in Biotech Venture Capital Syndicates

Yuxin Hu and Nektarios Oraiopoulos

Papers from arXiv.org

Abstract: The biotech venture market faces intense capital demands and regulatory scrutiny, yet academic research on VC networks remains rooted in software and consumer-tech contexts. This dissertation investigates how repeated co-investment ties and domain-expertise homophily influence a venture's exit likelihood, timing, and route amid the sector's pronounced technological and market uncertainty. Using a novel panel of 11,680 biotechnology start-ups from the United States, Canada, and Europe (2010-2024), we apply pooled logit, Cox proportional-hazards, multinomial logit, and Fine-Gray competing-risk models. Our findings show that both average prior co-investment and investor homophily exhibit robust inverted-U relationships with exit outcomes. Moderate familiarity and scientific overlap maximize exit probability, while either sparse or excessive embedding reduces success. Governance mechanisms also play a crucial role: participation of a pharmaceutical corporate VC or a highly independent board flattens the negative effects of over-embedding, enabling syndicates to sustain exit momentum at higher levels of familiarity or homogeneity. Furthermore, the optimal degree of embeddedness is route-specific: IPOs require deeper coordination than trade sales, while acquisitions peak earlier and are less sensitive to homophily. These findings refine network-embeddedness theory in the life-science context, identify governance contingencies, and offer practitioners quantitative metrics to balance trust, expertise, and oversight in biotech financing.

Date: 2025-12
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