Santa Clara University

Holding Up Production

Calculating Capacity When a Big Patent Expires

Businesses that hold lucrative patents face several tough decisions as those patents approach their expiration date. One consideration — particularly common in the pharmaceutical industry — is whether or not to try to “evergreen” the patent by applying for a new one or an improved version of the original product.

It’s a decision fraught with uncertainty on several fronts, including government regulation, market potential, and the need to ramp up production before the first two issues have been fully settled. Ram Bala, assistant professor of operations management and information systems (OMIS), and two colleagues have done a ground-breaking study of the production-capacity issues involved in such a decision.

“If you don’t have the production capacity, you can’t sell the product,” Bala says, “yet most of the research on evergreening has focused on marketing and economics. Up to now, no one has really studied the production-capacity question in this context.”

Production capacity is of immense importance to both the original patent holder and the generic manufacturers

Bala, who joined the Leavey faculty in January 2012, is lead author on the paper “Competition, Capacity and Evergreening,” which has been submitted to a major journal of management. Sumit Kunnumkal and Milind G. Sohoni of the Indian School of Business in Hyderabad, are co-authors.

Ram Bala Assistant Professor of OMIS

In the paper they look at several potential evergreening strategies and develop a model to help a business determine which is most likely to occur and what production capacity will be needed as a result. Bala says the underlying concepts can more easily be understood by considering the case of a pharmaceutical company that has a patent nearing expiration on a profitable prescription drug.

If a decision is made to evergreen the patent by developing a new and improved version of the drug, the path forward is obscured by a range of issues:

  • Will the patent office consider the new version sufficiently different from the original to issue a patent for it?
  • Will a new version pass clinical trials and win approval from federal regulators?
  • Will a generic manufacturer enter the market with a clone of the original drug?
  • If there is generic competition, should the drug company continue to sell the original as well as the improved version, or eliminate the original drug and sell only the new one?

“A company has to consider the tradeoffs involved in all these considerations as it tries to reach a decision,” Bala says. “What may seem like a straightforward decision really isn’t, and it’s complicated by the reality that firms often operate with separate departmental silos so that the research, marketing, and production people aren’t talking to each other as much as they should.”

Bala and his colleagues developed a model in their paper that can help businesses better weigh the factors involved in an evergreening decision and be better prepared with their production capacity. The model could help not only the company holding the original patent, but also a company planning to offer generic competition when the patent expires.

“We’ve talked with generic manufacturers, and they say production capacity is of immense importance to them,” Bala says. “They need to be able to decide when to invest in capacity and how much of it they’ll need to be ready on the day the patent expires.”

For both the original patent holder and the generic competitor, Bala says, the production-capacity gamble is a high-stakes affair. “If you don’t have enough capacity, you lose out on sales, on the ability to create market share, and on being able to lock in contracts with pharmacies and other distributors. With too much capacity you have waste and can’t sell your product at the price you want to get. Our model can help locate the point of tradeoff where a company can make a better decision.”


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Winter 2012 Contents

Watch My Eyes
Savannah Wei Shi used state-of-the-art eye-tracking technology to determine what works best on an Internet page layout.

Holding Up Production
Ram Bala and his colleagues have developed a model for helping companies calculate the production capacity they’ll need when a patent on a major product expires.

Good Mood, Good Decision
John Ifcher’s controlled experiment demonstrated a correlation between being in a good mood and making good financial decisions. The shelf of papers behind him shows the amount of raw data generated in a similar experiment.

Foiling the Data Snoopers
Haibing Lu did pioneering research on how to define “data cubes” so as to both share and protect information effectively.

Guided By Chatter
David Zimbra found that following the content of a Yahoo Finance chat room for a year led to an enhanced ability to predict stock price movements.

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