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Systems theory for pharmaceutical dr...

Aswani, Anil Jayanti.

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Systems theory for pharmaceutical drug discovery.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Systems theory for pharmaceutical drug discovery./
Author:	Aswani, Anil Jayanti.
Description:	152 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-09, Section: B, page: .
Contained By:	Dissertation Abstracts International71-09B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3413307
ISBN:	9781124140025

Systems theory for pharmaceutical drug discovery.
Aswani, Anil Jayanti.

Systems theory for pharmaceutical drug discovery. - 152 p.

Source: Dissertation Abstracts International, Volume: 71-09, Section: B, page: .

Thesis (Ph.D.)--University of California, Berkeley, 2010.

Biological networks are comprised of thousands of interacting components, and these networks have complicated patterns of feedback and feed-forward motifs. It is practically impossible to use intuition to determine whether simultaneously modifying multiple pharmaceutical targets has a good therapeutic response. Even when a drug is discovered which is safe in humans and highly-effective against its target, the medical effect on the disease may be underwhelming. This provides a strong impetus for developing a systems theory for pharmaceutical drug discovery. This thesis discusses system theoretic tools which are useful for doing drug discovery. The first class of tools discussed is system identification tools, and case studies of parametric modeling are given. A new statistical system identification procedure which exploits the geometric and hierarchical structure of many biological (and engineering) systems is presented, and this new procedure is applied to engineering and biological systems. The second class of tools discussed is a new set of target selection tools. Given mathematical models of biological networks, these tools select a set of targets for pharmaceutical drugs. The targets are selected to achieve good medical outcomes for patients by reducing the effect of diseases on pathways and ensuring that the targets do not too adversely affect healthy cells. The ultimate goal of the work presented in this thesis is to create a framework which can be used to rationally select new drug targets and also be able to create personalized medicine treatments which are tailored to the particular phenotypic behavior of an individual's disease.

ISBN: 9781124140025Subjects--Topical Terms:

517247
Statistics.

Systems theory for pharmaceutical drug discovery.
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100 1 $a Aswani, Anil Jayanti. $3 1671056
245 1 0 $a Systems theory for pharmaceutical drug discovery.
300 $a 152 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-09, Section: B, page: .
500 $a Adviser: Claire Tomlin.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2010.
520 $a Biological networks are comprised of thousands of interacting components, and these networks have complicated patterns of feedback and feed-forward motifs. It is practically impossible to use intuition to determine whether simultaneously modifying multiple pharmaceutical targets has a good therapeutic response. Even when a drug is discovered which is safe in humans and highly-effective against its target, the medical effect on the disease may be underwhelming. This provides a strong impetus for developing a systems theory for pharmaceutical drug discovery. This thesis discusses system theoretic tools which are useful for doing drug discovery. The first class of tools discussed is system identification tools, and case studies of parametric modeling are given. A new statistical system identification procedure which exploits the geometric and hierarchical structure of many biological (and engineering) systems is presented, and this new procedure is applied to engineering and biological systems. The second class of tools discussed is a new set of target selection tools. Given mathematical models of biological networks, these tools select a set of targets for pharmaceutical drugs. The targets are selected to achieve good medical outcomes for patients by reducing the effect of diseases on pathways and ensuring that the targets do not too adversely affect healthy cells. The ultimate goal of the work presented in this thesis is to create a framework which can be used to rationally select new drug targets and also be able to create personalized medicine treatments which are tailored to the particular phenotypic behavior of an individual's disease.
590 $a School code: 0028.
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650 4 $a Engineering, Electronics and Electrical. $3 626636
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710 2 $a University of California, Berkeley. $b Electrical Engineering & Computer Sciences. $3 1671057
773 0 $t Dissertation Abstracts International $g 71-09B.
790 1 0 $a Tomlin, Claire, $e advisor
790 1 0 $a El Ghaoui, Laurent $e committee member
790 1 0 $a Bickel, Peter $e committee member
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