國立虎尾科技大學 |

Monte Carlo simulation for the pharmaceutical industry = concepts, algorithms, and case studies /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Monte Carlo simulation for the pharmaceutical industry/ Mark Chang.
Reminder of title:	concepts, algorithms, and case studies /
Author:	Chang, Mark.
Published:	Boca Raton :CRC Press, : c2010.,
Description:	1 online resource (539 p.)
Subject:	Drug Industry - methods. -
Online resource:	http://www.crcnetbase.com/isbn/978-1-4398-3592-0
ISBN:	9781439835937 (electronic bk.)

Monte Carlo simulation for the pharmaceutical industry = concepts, algorithms, and case studies /
Chang, Mark.

Monte Carlo simulation for the pharmaceutical industryconcepts, algorithms, and case studies /[electronic resource] :Mark Chang. - Boca Raton :CRC Press,c2010. - 1 online resource (539 p.) - Chapman & Hall/CRC biostatistics series ;36. - Chapman & Hall/CRC biostatistics series ;38..

Includes bibliographical references and index.

"Preface Drug development, aiming at improving people's health, becomes more costly every year. The pharmaceutical industry must join its efforts with government and health professions to seek new, innovative, and cost- effective approaches in the development process. During this evolutionary process in the next decades, computer simulations will no doubt play a critical role. Computer simulation or Monte Carlo is the technique of simulating a dynamic system or process using a computer program. Computer simulations, as an efficient and effective research tool, have been used virtually in every concern of engineering, science, mathematics, etc. In this book, I am going to present the concept, theory, algorithm, and cases studies of Monte Carlo simulation in the pharmaceutical and health industries. The concepts refer not only to simulation in general, but also to various types of simulations in drug development. The theory will include virtual data sampling, game theory, deterministic and stochastic decision theories, adaptive design methods, Petrinet, genetic programming, resampling methods, and other strategies. These theories and methods either are necessary to carry out the simulations or make the simulations more efficient, even though there are many practical problems that can be simulated directly in ad hoc fashion without any theory of their efficiency or convergence considerations. The algorithms, which can be descriptive, computer pseudocode, or a combination of both, provide the basis for implementation of simulation methods. The case studies or applications are the simplified versions of the real world problems. These simplifications are necessary because a single case could otherwise occupy the whole book, preventing readers from exploring broad issues"--Provided by publisher.

ISBN: 9781439835937 (electronic bk.)Subjects--Topical Terms:

583209
Drug Industry
--methods.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: RM301.25 / .C46 2010eb

Dewey Class. No.: 615/.190113

Monte Carlo simulation for the pharmaceutical industry = concepts, algorithms, and case studies /
LDR:02754cam a2200241Ka 4500 001 778851
006 m o d
007 cr cnu---unuuu
008 140304s2010 flu ob 001 0 eng d
020 $a 9781439835937 (electronic bk.)
020 $a 1439835934 (electronic bk.)
020 $z 9781439835920
035 $a ocn668400779
040 $a N $b eng $c N $d YDXCP $d EBLCP $d E7B $d CDX $d OCLCQ $d MHW $d OCLCQ $d OHS $d OCLCQ
050 4 $a RM301.25 $b .C46 2010eb
082 0 4 $a 615/.190113 $2 22
100 1 $a Chang, Mark. $3 786667
245 1 0 $a Monte Carlo simulation for the pharmaceutical industry $h [electronic resource] : $b concepts, algorithms, and case studies / $c Mark Chang.
260 $a Boca Raton : $b CRC Press, $c c2010.
300 $a 1 online resource (539 p.)
490 1 $a Chapman & Hall/CRC biostatistics series ; $v 36
504 $a Includes bibliographical references and index.
520 $a "Preface Drug development, aiming at improving people's health, becomes more costly every year. The pharmaceutical industry must join its efforts with government and health professions to seek new, innovative, and cost- effective approaches in the development process. During this evolutionary process in the next decades, computer simulations will no doubt play a critical role. Computer simulation or Monte Carlo is the technique of simulating a dynamic system or process using a computer program. Computer simulations, as an efficient and effective research tool, have been used virtually in every concern of engineering, science, mathematics, etc. In this book, I am going to present the concept, theory, algorithm, and cases studies of Monte Carlo simulation in the pharmaceutical and health industries. The concepts refer not only to simulation in general, but also to various types of simulations in drug development. The theory will include virtual data sampling, game theory, deterministic and stochastic decision theories, adaptive design methods, Petrinet, genetic programming, resampling methods, and other strategies. These theories and methods either are necessary to carry out the simulations or make the simulations more efficient, even though there are many practical problems that can be simulated directly in ad hoc fashion without any theory of their efficiency or convergence considerations. The algorithms, which can be descriptive, computer pseudocode, or a combination of both, provide the basis for implementation of simulation methods. The case studies or applications are the simplified versions of the real world problems. These simplifications are necessary because a single case could otherwise occupy the whole book, preventing readers from exploring broad issues"--Provided by publisher.
588 $a Description based on print version record.
650 1 2 $a Drug Industry $x methods. $3 583209
650 2 2 $a Computer Simulation. $3 599654
650 2 2 $a Drug Design. $3 557397
650 2 2 $a Monte Carlo Method. $3 970831
650 2 2 $a Technology, Pharmaceutical $x methods. $3 583194
650 0 $a Drug development $x Computer simulation. $3 583229
650 0 $a Monte Carlo method. $3 672188
655 4 $a Electronic books. $2 local $3 554714
830 0 $a Chapman & Hall/CRC biostatistics series ; $v 38. $3 848174
856 4 0 $u http://www.crcnetbase.com/isbn/978-1-4398-3592-0