Adding to the complexity, mechanisms for drug production are typically not standardized even within firms, technologies continue
to change, and generic drugs are poised to dramatically impact the industry (2). In recent years, this changing dynamic has
been a key focus of research at the University of California, Berkeley, culminating with the recent establishment of the CELDi
Biopharmaceutical Operations Initiative (BOI), focusing on the development of cutting-edge tools, techniques, and approaches
to improve production systems, logistics systems, supply chain, inventory, and distribution within biopharmaceutical firms—essentially,
biopharmaceutical operations. The research initiative is jointly sponsored by member firms and the National Science Foundation
(NSF) under the Industry/University Cooperative Research Program.
Figure 2: Respondents, as a percentage, indidcate how they make decisions regarding inventory level and/or the number of suppliers
used (multiple selections were allowed).
Key to the development of this initiative was a series of industry–academia workshops held at Berkeley (one sponsored by the
NSF) in which the challenges and opportunities in biopharmaceutical operations management were explored. Across the industry,
managers have an overlapping set of concerns, and are eager for better approaches, tools, and techniques that account for
the unique characteristics of biopharmaceutical operations and help deal with these concerns. A common theme emerged from
these workshops: the need for more effective risk-management tools and approaches. Many firms are specifically focusing on
identifying and hedging risks associated with their operations, and are eager to collaborate to improve tools, techniques,
and approaches to do so. As a precursor to a concerted research effort in this area, the BOI surveyed nearly 300 industry
members to explore attitudes about risk related to suppliers, raw materials, contamination, outsourcing, disposable technology,
demand forecasting, inventory, and distribution, with a particular focusing on understanding which concerns are most significant,
how firms measure these risks, and what mitigation strategies they currently have in place (see sidebar, "Survey Respondents").
Below is a summary of the survey's key observations.
Figure 3: Respondents indicate their level of concern about certain manufacturing-related risks, where the scale ranges from
1 to 5, with 1 meaning not concerned, 3 meaning concerned, 5 meaning extremely concerned.
Overall, firms are most concerned with quality risks, contamination risks, and risks associated with lack of visibility into
contract manufacturing operations. More broadly, firms are concerned with a broad spectrum of risk-related issues, including
supplier risk, manufacturing reliability, inventory risks, cold-chain issues, and forecasting-related risks. In preliminary
interviews that accompanied the survey, several respondents even highlighted their concern that firms in the industry lack
a "global" or "system" view of risks faced, and rather than developing a cohesive strategy to minimize risk, consider risks
one at a time, thereby ignoring their interactions.
Surprisingly given these concerns, however, there is relatively little focus in the industry on detailed analysis of relevant
data, relatively little formal quantification of risk, little formal modeling and simulation of risk or risk mitigation strategies,
little focus on inventory optimization, and little measurement of uncertainty.
In contrast, in many industries risk mitigation involves spending considerable resources collecting and analyzing data, assessing
the types of variability in the data, optimizing resource utilization to mitigate risk, and developing rigorous models to
understand where inventory and other buffers can most effectively be utilized to hedge against risk. Surprisingly, for such
a sophisticated industry in so many ways (e.g., compared with basic consumer products or industrial equipment manufacturers),
this industry has a qualitative view of risk management. This finding is particularly surprising given the vast amount of
data that is collected in the industry.