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Realize hidden value through timely portfolio decisions: dynamic portfolio simulation with aligned management processes can improve pharmaceutical research productivity.

Article Excerpt
The development and launch of an innovative new drug may take 10 to 15 years, and cost estimates vary from around $500 million to more than $2,000 million, depending on the therapy and the developing firm (1). R&D budgets of international pharmaceutical companies trended around 15 percent of sales in 2006 (2). Additionally, the pharmaceutical R&D process is burdened with extremely high attrition rates, resulting in ever-fewer innovative drugs coming to the market. Despite scientific breakthroughs and rapid technological advances in miniaturization and automation, potential drug candidates face a high degree of project termination during the rigorous testing and selection process. Faced with a dire need to close the innovation gap, a reorientation toward value maximization has transformed the R&D departments of the large, multinational pharmaceutical companies (3).

There have been any number of reports on value-driven portfolio management. However, current approaches (4) show an intriguing gap in addressing the specific aspect of early drug discovery, e.g., management of portfolios with projects exhibiting high uncertainty and a high number and frequency of decision points. This paper presents for the first time a dynamic model of an integrated portfolio management process for the research phase. We specifically discuss the minimum necessary decision bodies involved, key processes, number and temporary validity of the decisions, and address the general issue of portfolio-wide resource allocation.

Organization of Pharmaceutical R&D

The pharmaceutical industry provides innovative therapies to patients through new proprietary products. Each company defines its therapeutic areas of interest in the context of formulating the respective enterprise strategy. For simplicity, Figure 1 divides the complex R&D process into three different segments based on common definitions in the industry and characteristic project and risk profiles. Based on the chosen therapeutic areas, specific disease knowledge for various indications is created internally, a mandatory prerequisite for successful partnering through in- or out-licensing. We believe that an open enterprise structure is needed in all phases without any discrimination between internal and external project ideas. The pharmaceutical industry has made significant progress toward this goal, particularly in the early and late development phases. Because these final stages of the pharmaceutical development process (clinical development) are highly regulated, information for a project in the clinical stage is extensive and standardized and can be readily transferred between companies. The large number of licensing deals is proof of this (5). However, for the research stage this still seems an elusive goal. In particular, unresolved intellectual property issues make companies reluctant to share data openly. Even in long-established successful strategic partnerships, data created by one partner do not always fit the information needs of the other, thereby resulting in additional experiments and difficult project evaluation.

One way to address these issues is with the model of Innocentive, Inc., which Eli Lilly founded. Companies wishing to solve a particular problem (seekers) are anonymously connected with thousands of scientists around the world (solvers); all intellectual rights reside with the company whereas the solver receives a cash award for an accepted solution. This approach has yielded...