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A comparison of stochastic programming methods for portfolio level decision-making

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A comparison of stochastic programming methods for portfolio level decision-making. / Graham, E.; Jaki, T.; Harbron, C.
In: Journal of Biopharmaceutical Statistics, Vol. 30, No. 3, 01.05.2020, p. 405-429.

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Graham E, Jaki T, Harbron C. A comparison of stochastic programming methods for portfolio level decision-making. Journal of Biopharmaceutical Statistics. 2020 May 1;30(3):405-429. Epub 2019 Dec 11. doi: 10.1080/10543406.2019.1684307

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Graham, E. ; Jaki, T. ; Harbron, C. / A comparison of stochastic programming methods for portfolio level decision-making. In: Journal of Biopharmaceutical Statistics. 2020 ; Vol. 30, No. 3. pp. 405-429.

Bibtex

@article{0d405bb94f0445c186425801b683b12d,
title = "A comparison of stochastic programming methods for portfolio level decision-making",
abstract = "Several methods have been presented in the literature for the management of a pharmaceutical portfolio, i.e. selecting which clinical studies should be conducted. We compare two existing approaches that use stochastic programming techniques and formulate the problem as a mixed integer linear programme (MILP). The first approach will be referred to as the ROV (real option valuation) approach since values are assigned to drug development programmes using methods for real option valuation. The second approach will be referred to as the PS (project scheduling) approach as this approach focusses on the scheduling of clinical studies and is formulated similarly to the resource constrained project scheduling problem. The ROV approach treats the value of a drug development programme as stochastic whereas the PS approach treats the trial outcomes as the stochastic component of the programme. As a consequence, the two approaches may select different portfolios. An advantage of the PS approach is that a schedule for when trials are to be conducted is provided as part of the optimal solution. This advantage comes at a much increased computational burden, however.",
keywords = "Portfolio management, stochastic programming, real option valuation, project scheduling, portfolio level decision making, research and development pipeline",
author = "E. Graham and T. Jaki and C. Harbron",
year = "2020",
month = may,
day = "1",
doi = "10.1080/10543406.2019.1684307",
language = "English",
volume = "30",
pages = "405--429",
journal = "Journal of Biopharmaceutical Statistics",
issn = "1054-3406",
publisher = "Taylor and Francis Ltd.",
number = "3",

}

RIS

TY - JOUR

T1 - A comparison of stochastic programming methods for portfolio level decision-making

AU - Graham, E.

AU - Jaki, T.

AU - Harbron, C.

PY - 2020/5/1

Y1 - 2020/5/1

N2 - Several methods have been presented in the literature for the management of a pharmaceutical portfolio, i.e. selecting which clinical studies should be conducted. We compare two existing approaches that use stochastic programming techniques and formulate the problem as a mixed integer linear programme (MILP). The first approach will be referred to as the ROV (real option valuation) approach since values are assigned to drug development programmes using methods for real option valuation. The second approach will be referred to as the PS (project scheduling) approach as this approach focusses on the scheduling of clinical studies and is formulated similarly to the resource constrained project scheduling problem. The ROV approach treats the value of a drug development programme as stochastic whereas the PS approach treats the trial outcomes as the stochastic component of the programme. As a consequence, the two approaches may select different portfolios. An advantage of the PS approach is that a schedule for when trials are to be conducted is provided as part of the optimal solution. This advantage comes at a much increased computational burden, however.

AB - Several methods have been presented in the literature for the management of a pharmaceutical portfolio, i.e. selecting which clinical studies should be conducted. We compare two existing approaches that use stochastic programming techniques and formulate the problem as a mixed integer linear programme (MILP). The first approach will be referred to as the ROV (real option valuation) approach since values are assigned to drug development programmes using methods for real option valuation. The second approach will be referred to as the PS (project scheduling) approach as this approach focusses on the scheduling of clinical studies and is formulated similarly to the resource constrained project scheduling problem. The ROV approach treats the value of a drug development programme as stochastic whereas the PS approach treats the trial outcomes as the stochastic component of the programme. As a consequence, the two approaches may select different portfolios. An advantage of the PS approach is that a schedule for when trials are to be conducted is provided as part of the optimal solution. This advantage comes at a much increased computational burden, however.

KW - Portfolio management

KW - stochastic programming

KW - real option valuation

KW - project scheduling

KW - portfolio level decision making

KW - research and development pipeline

U2 - 10.1080/10543406.2019.1684307

DO - 10.1080/10543406.2019.1684307

M3 - Journal article

VL - 30

SP - 405

EP - 429

JO - Journal of Biopharmaceutical Statistics

JF - Journal of Biopharmaceutical Statistics

SN - 1054-3406

IS - 3

ER -