Alliances between big pharmaceutical firms (BPF) and smaller biotechnology firms (BIOF) are increasing. The 20 largest BPF firms formed nearly 1,500 alliances with BIOFs between 1977 and 2002 (Lam 2004). Over half of the current 20 best-selling BPF prescription drugs were co-developed, co-marketed, or in-license with BIOF firms, accounting for 40 percent of BPF revenues (Lam 2004). However, sixty percent of drug discovery alliances fail to achieve expected results—half for non-technical reasons (Laroia and Krishnan 2005). Nonetheless, alliances are becoming more important for BPF firms because alliances help them to meet or exceed competitive growth rate projections.

This dissertation explores the effect of BPF firm management policies on creating and fostering alliances with partner firms. The study had main objectives. (1) Analyze the Patterns and Trends in BPF/BIOF Alliances. (2) Develop a Framework for Modeling the Alliances. (3) Test the Validity of the System Dynamics Model.

Study #1 was conducted based on 18 years of historical data on alliances for 3 large BPF firms: Johnson & Johnson, Pfizer, and Eli Lilly, ranked 1st, 2nd, and 10th in reported 2009 revenues. Analysis of alliance management data collected in Study #1 for the period 1993 through 2008 showed great similarity among the large BPF firms in their alliance selection practices. Of the 16 alliance deal attributes defining the alliances, the BIOF firm characteristics and BPF firm characteristics, 13 were similar. Study #1 showed that dynamic relationships exist among revenue growth, exploration alliances, exploitation alliance, R&D investments, and licensing royalties.

In Study #2, a framework for studying alliances was developed based on the results of Study #1. The framework was used to create the System Dynamics model. Furthermore, it is shown that the alliance agreements depend on the strength of the ties between the BPF and BIOF firms. The sensitivity analyses tested nine assertions (from Study #1) that involve revenue, exploration, exploitation, and strength of ties. The results validate the model.