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Hologic Acquires Gen-Probe: A View from the Plank

by Greg Emmerich, UW Madison M.S. Biotechnology Program. Business of Biotechnology: Frontiers and Strategies. Final Paper. April 23rd, 2013.  Privacy Disclaimer; Figure Templates.

Executive Summary

WalkingThePlankPirates

  • Hologic closed a $3.97 billion deal to acquire Gen-Probe in August 2012.  Hologic must be able to create significant value in order to justify such a large purchase as it moves forward.
  • Molecular diagnostics is the fastest-growing segment of the in vitro diagnostic market, which is expected to reach $67.2 billion by 2016.
  • The overall analysis of the acquisition is favorable.  However, the market is fiercely competitive and reliant upon decreasing reimbursement plans.
  • Hologic has strong capabilities with its sales force, but is too dependent on single suppliers and very large customers.
  • Success in the market is dependent on ability to innovate and adapt to change.  Hologic’s internal R&D needs to strengthen in that regard.
  • Four action steps are recommended to Hologic to overcome these challenges. Continue reading

Demystifying Big Data: Skytree Brings Machine Learning to the Masses

by Greg Emmerich, UW Madison M.S. Biotechnology Program. Advanced Biotechnology: Global Perspectives. Thesis Paper. April 16th, 2013.

Abstract

The Digital Revolution has created a knowledge-based society reliant upon a high-tech global economy.  The pace of innovation has been exponential, leaving some to wonder what possibilities the future may hold.

Big Data is the term given for collections of data sets that are too large and complex for traditional hands-on data management and processing.  The term comes from the realm of information technology, but across an increasing number of fields, scientists are encountering situations that fit the category of Big Data.  Astronomy, genetics, and proteomics are a few of the fields beginning to feel the pressure for managing their data effectively.

There are numerous technical challenges going into setting up a system to process Big Data in reasonable amounts of time.  Machine learning algorithms present great potential in their ability to tease out hidden relationships among data sets and make predictions, but these analyses require distributed computing clusters capable of communicating intermediate results between tasks.

Continue reading

Knome: A Model for Personal Genomics

by Greg Emmerich, UW Madison, M.S. Biotechnology Program, Early Drug Discovery Class.  December 7th, 2012.

Abstract


Predictive, preventative and personalized medicine is increasingly becoming a reality with recent advances to whole genome sequencing. Genome wide association studies wield impressive amounts of data, but due to differences in populations tested and analysis methodology, there are very few such studies that are reproducible. Great strides are being made in academia and industry, and the more research and data is shared, the more robust future studies will be. Knome Inc. has a unique method for annotating and interpreting genomic data that aims to tackle some of the challenges discussed. Continue reading

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