Abstract
In this short research paper, we conceptually propose a valuation model that is suitable for assessing R&D projects and managing uncertainty in pharmaceutical laboratories. Taking this into consideration, this model would allow these organizations to take better strategic decisions that will affect the pipeline of clinical trials (per phase) and the portfolio of innovative drugs. More specifically, our valuation methodology would help decision makers to identify if and when to promote and abandon clinical trials and new drug developments. To this end, we adopt a real options valuation approach, which is combined with fuzzy techniques and simulation. Our proposal incorporates some additional features in relation to the previous literature that aim to make our model more adaptable to deal with real-world uncertainties in the development of new drugs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
E.F. Schmid, D.A. Smith, Managing innovation in the pharmaceutical industry. J. Commer. Biotechnol. 12(1), 50–57 (2005)
X. Zhong, G.B. Moseley, Mission possible: Managing innovation in drug discovery. Nat. Biotechnol. 25(8), 945–946 (2007)
G.L. Nigro, A. Morreale, G. Enea, Open innovation: A real option to restore value to the biopharmaceutical R&D. Int. J. Prod. Econ. 149, 183–193 (2014)
L.E. Brandão, G. Fernandes, J.S. Dyer, Valuing multistage investment projects in the pharmaceutical industry. Eur. J. Oper. Res. 271(2), 720–732 (2018)
F.A. Longstaff, E.S. Schwartz, Valuing American options by simulation: A simple least-squares approach. Rev. Financ. Stud. 14(1), 113–147 (2001)
J.C. Hsu, E.S. Schwartz, A model of R&D valuation and the design of research incentives. Insur. Math. Econ. 43(3), 350–367 (2008)
J. Puente, F. Gascon, B. Ponte, D. de la Fuente, On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions. Artif. Intell. Med. 100, 101703 (2019)
L.M. Friedman, C. Furberg, D.L. DeMets, D.M. Reboussin, C.B. Granger, Fundamentals of Clinical Trials, vol 4 (Springer, New York, 2010)
C.P. Adams, V.V. Brantner, Estimating the cost of new drug development: Is it really $802 million? Health Aff. 25(2), 420–428 (2006)
J. Holland, Fixing a broken drug development process. J. Commer. Biotechnol. 19(1), 238–263 (2013)
S. Dutta, B. Lanvin, S. Wunsch-Vincent, Global innovation index 2019 – Creating healthy lives–the future of medical innovation (2019). Available via https://www.wipo.int/edocs/pubdocs/en/wipo_pub_gii_2019.pdf. Accessed 31 May 2020
F. Gascón, J. Lozano, B. Ponte, D. de la Fuente, Measuring the efficiency of large pharmaceutical companies: An industry analysis. Eur. J. Health Econ. 18(5), 587–608 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Puente, J., Alonso, S., Gascon, F., Ponte, B., de la Fuente, D. (2021). A Model for the Strategic Management of Innovation and R&D Based on Real Options Valuation: Assessing the Options to Abandon and Expand Clinical Trials in Pharmaceutical Firms. In: Arabnia, H.R., Ferens, K., de la Fuente, D., Kozerenko, E.B., Olivas Varela, J.A., Tinetti, F.G. (eds) Advances in Artificial Intelligence and Applied Cognitive Computing. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70296-0_75
Download citation
DOI: https://doi.org/10.1007/978-3-030-70296-0_75
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-70295-3
Online ISBN: 978-3-030-70296-0
eBook Packages: Computer ScienceComputer Science (R0)