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Simulating Market Entry Rewards for Antibiotics Development
Christopher Okhravi1, Simone Callegari1, Steve McKeever1
1Christopher Okhravi, M.S.Sc., is a Ph.D. student of Information Systems. His research concerns simulating the effects of policy intervention on research & development. Simone Callegari, Ph.D., is a Postdoctoral Investigator at Uppsala University in Sweden. His research concerns simulating the effects of policy intervention on antimicrobial agents' research & development. Steve McKeever, D.Phil., is an Associate Professor of Information Systems at Uppsala University in Sweden. He holds a D.Phil. in Mathematics from the University of Oxford. A recent focus has been supporting simulations at the life science interface. Carl Kronlid, M.Sc., is a Ph.D. student of Industrial Engineering & Management at Uppsala University in Sweden. His research is focused on innovation and organizing, with a focus on collaborative high-tech innovation projects. Enrico Baraldi, Ph.D., is a Professor of Industrial Engineering & Management at Uppsala University in Sweden. His research concerns strategies in business networks, innovation, product development and the commercialization of science. Olof Lindahl, Ph.D., is an Assistant Professor of International Business at Uppsala University in Sweden. His research interests lie in the management of multinational firms, particularly in the mechanical engineering and pharmaceutical industries. Francesco Ciabuschi, Ph.D., is a Professor of International Business at Uppsala University in Sweden. His research concerns management of multinationals, corporate strategy, state enterprises, innovation management and entrepreneurship.
Abstract:
We design an agent based Monte Carlo model of antibiotics research and development (R&D) to explore the effects of the policy intervention known as Market Entry Reward (MER) on the likelihood that an antibiotic entering pre-clinical development reaches the market. By means of sensitivity analysis we explore the interaction between the MER and four key parameters: projected net revenues, R&D costs, venture capitalists discount rates, and large pharmaceutical organizations' financial thresholds. We show that improving revenues may be more efficient than reducing costs, and thus confirm that this pull-based policy intervention effectively stimulates antibiotics R&D.
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