2026-09-20T02:31:13Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/330892022-01-31T14:14:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Fiona E. Murray and Anthony J. Sinskey.
Holland, Chad D. (Chad Darrel)
Sloan School of Management. Management of Technology Program.
Harvard University--MIT Division of Health Sciences and Technology.
Management of Technology Program.
Harvard University--MIT Division of Health Sciences and Technology
Sloan School of Management
2006-06-19T17:39:27Z
2006-06-19T17:39:27Z
2005
2005
http://hdl.handle.net/1721.1/33089
62172528
Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology; and, (S.M.M.O.T.)--Massachusetts Institute of Technology, Sloan School of Management, Management of Technology Program, 2005.
Includes bibliographical references.
The promise of personalized medicine lies in its potential to fundamentally change healthcare. In the past, pharmaceuticals were prescribed on a "one size fits all" basis-patients with certain disease phenotypes were given what were thought to be appropriate drugs. There is growing evidence however that the effectiveness of these drugs may differ by individual and by sub-group; presumably due to fundamental genetic differences in disease and metabolic pathways. Drugs like Herceptin, Gleevec and Iressa are part of an emerging trend in the biopharmaceutical arena of drugs that are accompanied by genetic diagnostic tests and prescribed only for patients with genotypes in which the agents are most effective.
by Chad D. Holland.
S.M.M.O.T.
S.M.
103 p.
7472164 bytes
7477842 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Harvard University--MIT Division of Health Sciences and Technology.
Management of Technology Program.
Personalized medicine, population genetics and privacy : an empirical study of international gene banks
Thesis
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Publication
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