MBA Coursework
MBA 586
Legal, Regulatory and Ethical Issues in Life Science Industries
This course consists of topics relating to:
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The U.S. Regulatory System
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Regulation of Life Science Industries
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Ethics in Marketing and Promotion
- Inspection and Enforcement of Regulations
- Patents and IP Law
- Tort Law
This course covered these topics in relation to pharmaceutical companies to agricultural biotechnology. With a bit of freedom granted by this course, I focused many of my assignments and research on ethics and regulations within agricultural biotechnology.
Two systematic literature reviews were developed during this course: one focusing on the ability for companies to patent seeds and how this impacts farmers, and one focusing on the recent supreme court decision in Natural Grocers v. Rollins and how it impacts the agricultural biotechnology industry.
MBA 585
Current Topics in BioSciences Management
MBA 545
Decision Making Under Uncertainty
This course consists of topics relating to:
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Research and development
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IP and regulations
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Production and logistics
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Marketing and customer service
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Business strategy
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Financing, M&As, strategic partnerships
The mid-semester project was a case study assessment of Novo Nordisk that resulted in giving a presentation recommending a strategy for navigating the production, marketing, and general future of GLP-1 drugs.
The final project was a report and presentation diving into the role of external innovation and Big Pharma business development teams. Within this report, we hypothesized that external innovation was beginning to yield negative returns and suggest a strategy for pharmaceutical companies moving forward.
This course consists of topics relating to:
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Identifying and framing issues surrounding decisions
- Obtaining decision-relevant information in an unbiased manner
- Defining values and tradeoffs
- Analysis and evaluation of alternatives
- Supporting decisions through statistical analysis
Work in this class involved developing decision trees, cumulative distribution functions using probability encoding, and influence diagrams given decision-making scenarios. Additionally, we learned how to determine expected value given perfect and imperfect information and how to find the expected utility and certain equivalent for a decision given a utility function.
Projects in this class involved developing spreadsheet-based decision models in Microsoft Excel and conducting sensitivity analyses of uncertain variables in a decision-making scenario. Syncopation DPL software was used to produce models used in these analyses and to support decisions.