This book explores the use of mathematical and computational approaches to optimize combination drug therapies for HIV. It delves into the dynamics of HIV infection and the challenges posed by drug resistance. The author develops a dynamic multidrug therapy strategy that tailors treatment to individual patients based on their viral load, CD4+ cell count, and the emergence of resistant strains. Through numerical simulations, the book demonstrates the potential of this approach to reduce viral load, increase CD4+ cell counts, and delay the onset of drug resistance. The work contributes to the ongoing effort to develop more effective and personalized treatment strategies for HIV.
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Stefanos Zenios is the Charles A. Holloway Professor at the Graduate School of Business, Stanford University. His pioneering work on maximizing the benefits of medical technology to patients when resources are limited has influenced policies in the US and Europe. He has quantified the ethical implications of technology allocation choices on patients and society as featured in the Financial Times and Times.com. At Stanford University, he was the first to introduce courses on the interface between medicine, engineering, and management in the MBA curriculum. Dr Zenios advises medical device and biopharmaceutical companies on health economics and outcomes studies for marketing and reimbursement strategies. He is also a co-founder of Culmini Inc., a company funded by the National Institutes of Health to develop web-tools that help patients and families with difficult choices.
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Seller: Forgotten Books, London, United Kingdom
Paperback. Condition: New. Print on Demand. This book explores the use of mathematical and computational approaches to optimize combination drug therapies for HIV. It delves into the dynamics of HIV infection and the challenges posed by drug resistance. The author develops a dynamic multidrug therapy strategy that tailors treatment to individual patients based on their viral load, CD4+ cell count, and the emergence of resistant strains. Through numerical simulations, the book demonstrates the potential of this approach to reduce viral load, increase CD4+ cell counts, and delay the onset of drug resistance. The work contributes to the ongoing effort to develop more effective and personalized treatment strategies for HIV. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781332258758_0
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781332258758
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781332258758
Quantity: 15 available