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• W3171849144 abstract "The research and development (R&D) management in any major research pharmaceutical company is constantly faced with the need to make complicated activity scheduling and resource allocation decisions, as they carry out scientific work to develop new therapeutic products. This paper describes how we develop a decision support tool that allows practitioners to determine portfolio-wide optimal schedules in a systematic, quantitative, and largely automated fashion. Our tool is based on a novel mixed-integer linear optimization model that extends archetypal multimode resource-constrained project scheduling models in order to accommodate multiple rich features that are pertinent to the Chemistry, Manufacturing, and Controls (CMC) activities carried out within the pharmaceutical R&D setting. The tool addresses this problem at the operational level, determining schedules that are optimal in light of chosen business objectives under activity sequencing, resource availability, and deadline constraints. Applying the tool on current workload data demonstrates its tractability for practical adoption. We further illustrate how, by utilizing the tool under different input instances, one may conduct various tactical analyses to assess the system’s ability to cope with sudden changes or react to shifting management priorities." @default.
• W3171849144 created "2021-06-22" @default.
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• W3171849144 date "2021-07-01" @default.
• W3171849144 modified "2023-10-09" @default.
• W3171849144 title "Portfolio-Wide Optimization of Pharmaceutical R&D Activities Using Mathematical Programming" @default.
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• W3171849144 doi "https://doi.org/10.1287/inte.2021.1074" @default.
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