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dc.contributor.advisorBryan R . Moser.en_US
dc.contributor.authorBadwe, Ravi.en_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering and Management Program.en_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2019-10-04T21:34:51Z
dc.date.available2019-10-04T21:34:51Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122442
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2019en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 89-92).en_US
dc.description.abstractPharmaceutical R&D involves significant uncertainty, including high attrition rate and long time for a project to progress from a target identification phase to commercial launch. Despite this uncertainty, senior leaders must make decisions about R&D portfolio, the impact of which may not be observable for many years. Hence the purpose of this thesis is to understand the current state of Pharmaceutical R&D portfolio management and identify the gaps in R&D portfolio management research. The literature survey revealed that though there are many qualitative and quantitative approaches for the portfolio management of projects in the development phase (i.e. from pre-clinical to phase 3.), the topic of portfolio management in the drug discovery phase (i.e. target validation to lead optimization) have not been well covered in the literature. Hence the problem statement of this thesis is to develop a portfolio management approach for drug discovery.en_US
dc.description.abstractPortfolio management in pharmaceutical drug discovery space is not only a mathematics problem but also a representation problem in terms of activities, resources, decisions, dependencies, and uncertainties. There is something about the nature of the scope of early research in pharma which makes it different from downstream phases and respective parallels in other sectors. Improved representation can lead to improved prediction in drug discovery phase. Hence as the first step, structured survey was conducted to listen to insights from an experienced professional in the drug discovery domain at NIBR (Novartis Institute of Biomedical Research) to build the required understanding about discovery phase. The survey results helped in identification of the biology, chemistry, medical, marketing, and strategy factors generally taken into consideration during drug discovery project prioritization.en_US
dc.description.abstractResource allocation is not considered during project prioritization - even though resource allocation determines the cycle-time that in turn influences the probability of project to reach pre-clinical phase. Proposed semi-quantitative portfolio management approach, which is based on the survey results, incorporates three key aspects of drug discovery project - scope feasibility (science), desirability (market and strategy), and time feasibility (resource allocation and cycle time). Proposed criterion based model for computing scope feasibility and desirability can be uniformly and transparently applied to all the projects across different disease areas and requires discussion between concerned teams to generate required scores. Also, proposed resource allocation model will enable portfolio management teams to generate multiple scenarios (trade spaces) on scope feasibility, time feasibility, and desirability dimensions.en_US
dc.description.abstractBased on the thresholds, which can be calculated from past data, portfolio team and management in conjunction with other teams such as disease area representatives, chemistry team, marketing etc. can decide the best scenario. The future work needs to focus on validating the proposed portfolio management approaches and models with the real data from past projects in the drug discovery phase in order to enable to organization-wide implementation.en_US
dc.description.statementofresponsibilityby Ravi Badwe.en_US
dc.format.extent99 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering and Management Program.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titlePortfolio optimization in early drug R&D : a deeper dive into underlying dynamics of early research in pharmaceutical/biotech sectoren_US
dc.title.alternativePortfolio optimization in early drug research and development : a deeper dive into underlying dynamics of early research in pharmaceutical/biotech sectoren_US
dc.title.alternativeDeeper dive into underlying dynamics of early research in pharmaceutical/biotech sectoren_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering and Management Programen_US
dc.contributor.departmentSystem Design and Management Programen_US
dc.identifier.oclc1120725745en_US
dc.description.collectionS.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Programen_US
dspace.imported2019-10-04T21:34:50Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSysDesen_US


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