Assessing decision inputs in drug development between small, early stage companies and big pharma : is there is a difference?

Abstract

The pipeline productivity challenge facing large, publicly traded pharmaceutical companies, collectively referred to as "Big Pharma," is well known. The unprecedented success Big Pharma achieved over the past few decades in commercializing blockbuster products means that it is now faced with near-term patent expirations on such products, representing billions of dollars in lost sales and profits. In order to maintain its economic momentum, Big Pharma is increasingly relying on the universe of smaller, early stage biotechnology and pharmaceutical companies as a source of new products. Early stage companies may offer Big Pharma something beyond simply more product bets. Several recent consulting studies have shown that economic returns to Big Pharma of products sourced externally are greater than those developed internally, which raises the question: What, if anything, are early stage companies doing differently from Big Pharma in their product development programs? The goal of this thesis is to evaluate product development programs ("projects") and compare qualitatively and quantitatively the decisions for projects at key decision points between early stage pharmaceutical and biotechnology companies and Big Pharma. Given that much of the critical discovery and R&D work on pharmaceutical products happens both before and during a product's entry into human clinical trials, this thesis focuses on those areas of the development continuum where R&D plays a central role. The key decision points are therefore: lead candidate selection/optimization, moving a project from pre-clinical trials into Phase I human clinical trials, and moving a project from Phase I to Phase II clinical trials in humans.

(cont.) The thesis tests the hypothesis that small, early stage, publicly traded U.S. & Canadian biotech and pharma firms (Small Pharma) focused on 1-2 therapeutic areas who high levels of homogeneity in their decision making process, number of decision inputs, prioritization processes, and metrics for all three key decision points in the product development process irrespective of whether a product originates inside or outside the company. In comparison, Big Pharma companies will show heterogeneity in these variables for their projects. I have obtained data from primary interviews of industry executives within Big Pharma and Small Pharma firms. The therapeutic areas selected for the early stage company data set are: (1) cancer and autoimmune disease, (2) cardiovascular disease, and (3) infectious disease. The rationale for these therapeutic areas is that there is significant drug development activity taking place in these fields, and there are significant unmet medical needs within them. Additionally, both Big Pharma and Small Pharma companies are developing products in these fields. I compare these data sets statistically using Fisher's exact test and Yates' chi-square test.