Ensuring Quality Science From “R” to “D”: An Optimal Adoption Strategy for In-Licensing of Pharmaceutical Innovation

In today's competitive business environment, pharmaceutical companies intensively explore contract R&D opportunities with small biotechnology companies and in-license externally discovered compounds to replenish their product pipelines. In order to maintain and increase external collaboration productivity, pharmaceutical companies must find the most promising outside compounds generated in the research stage as the inputs for later in-house development stages. Thus, the “R”-to-“D” transition is significant in ensuring the scientific quality of in-licensed compounds. In this paper, an optimal adoption strategy is proposed to evaluate the in-licensing opportunities for a pharmaceutical company as it finances several biotech partners who focus on the same therapeutic area. This strategy is fundamentally an outsourcing decision process for the pharmaceutical company, and it is modeled as a Poisson process during which small biotechs submit their outcomes to the pharmaceutical company. We give the formulation for the process, whose simulation results, here, indicate that under the high uncertainty of both time value and market payoff, the pharmaceutical company should make its decision by trading off research time for gradually emerging information on the compound's quality. Specific characteristics that emerged in this process are discussed. We also carried out interviews with pharmaceutical R&D managers to explore the “practical applicability” of the model.

[1]  P. Danzon,et al.  Productivity in Pharmaceutical Biotechnology R&D: The Role of Experience and Alliances , 2003, Journal of health economics.

[2]  James Kalamas,et al.  The optimum time for drug licensing , 2003, Nature Reviews Drug Discovery.

[3]  Rolf F. Tiggemann,et al.  Project Portfolio Management: A Powerful Strategic Weapon in Pharmaceutical Drug Development , 1998 .

[4]  Alexander Kamb,et al.  What's wrong with our cancer models? , 2005, Nature Reviews Drug Discovery.

[5]  Sheldon M. Ross,et al.  Introduction to probability models , 1975 .

[6]  Andrew A. Signore,et al.  Pharmaceutical Industry Profile , 2005 .

[7]  J. Michael Pearson,et al.  Riding the Pharma Roller Coaster: In an Industry in Which Many Mergers Have Failed to Create Value, Fred Hassan Has Used Them to Take Pharmacia into the Pharmaceutical Big Leagues. Here He Explains How , 2002 .

[8]  Anthony Coia,et al.  Value drivers in licensing deals , 2002, Nature Biotechnology.

[9]  K. McCardle Information Acquisition and the Adoption of New Technology , 1985 .

[10]  Nafees N. Malik Biotech acquisitions by big pharma: why and what is next. , 2009, Drug discovery today.

[11]  Khaleel Malik,et al.  The Growth and Management of R&D Outsourcing: Evidence from UK Pharmaceuticals , 2008 .

[12]  Emeric Henry,et al.  The timing of licensing: theory and empirics , 2008 .

[13]  Dean Paxson,et al.  A gene to drug venture: Poisson options analysis , 2001 .

[14]  C. Lengauer,et al.  Cancer drug discovery through collaboration , 2005, Nature Reviews Drug Discovery.

[15]  Andrew Jones,et al.  Drug discovery alliances , 2005, Nature Reviews Drug Discovery.

[16]  Arvids A. Ziedonis Real Options in Technology Licensing , 2007, Manag. Sci..

[17]  Emily Marden Open Source Drug Development: A Path to More Accessible Drugs and Diagnostics? , 2010 .

[18]  Brian C. Cunningham Biotech and pharma: State of the relationship in the new millennium , 2002 .

[19]  David Cavalla,et al.  The extended pharmaceutical enterprise. , 2003, Drug discovery today.

[20]  Bruce Rasmussen Alliance Opportunities for Aus Biotech , 2004 .

[21]  Fiona E. Murray Innovation as co-evolution of scientific and technological networks: exploring tissue engineering , 2002 .

[22]  Min Ding,et al.  Valuation and Design of Pharmaceutical R&D Licensing Deals , 2005 .

[23]  Oliver Gassmann,et al.  Leading Pharmaceutical Innovation: Trends and Drivers for Growth in the Pharmaceutical Industry , 2004 .

[24]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[25]  Gerrit Reepmeyer Risk-sharing in the Pharmaceutical Industry: The Case of Out-licensing , 2006 .

[26]  T. Cymet,et al.  The Truth about Drug Companies: How They Deceive Us and What to Do about It , 2006 .

[27]  Gary P. Pisano,et al.  R&D Performance, Collaborative Arrangements and the Market for Know-How: A Test of the "Lemons" Hypothesis in Biotechnology , 1997 .

[28]  Boris Bogdan,et al.  Getting real about valuations in biotech , 2005, Nature Biotechnology.

[29]  Jennifer F. Reinganum On the diffusion of new technology: A game theoretic approach , 1981 .

[30]  James L. Gilbert,et al.  Rebuilding Big Pharma ’ s Business Model , 2022 .

[31]  Guozhen Zhao,et al.  Enhancing R&D in science-based industry: An optimal stopping model for drug discovery , 2009 .

[32]  Karl A Thiel Goodbye Columbus! New NRDOs forego discovery , 2004, Nature Biotechnology.

[33]  K. Kimura,et al.  Are research and development processes independent in the pharmaceutical R&D? , 2007 .

[34]  W. Marsden I and J , 2012 .

[35]  Walter van Dyck Predictive performance of front-loaded experimentation strategies in pharmaceutical discovery: a Bayesian perspective , 2004 .

[36]  K. Thiel A very firm handshake: biotech's growing negotiating power , 2005, Nature Biotechnology.

[37]  A. Jones Minimizing leakage of value from R&D alliances , 2007, Nature Reviews Drug Discovery.

[38]  R. Jensen,et al.  Adoption and diffusion of an innovation of uncertain profitability , 1982 .

[39]  F. Sams-Dodd,et al.  Optimizing the discovery organization for innovation. , 2005, Drug discovery today.

[40]  Lefkos Middleton,et al.  Disease-specific target selection: a critical first step down the right road. , 2005, Drug discovery today.

[41]  Bruce L. Booth Valuation with cash multiples , 2005, Nature Reviews Drug Discovery.

[42]  Dennis A Smith,et al.  Pharmaceutical R&D in the spotlight: why is there still unmet medical need? , 2007, Drug discovery today.