MARC Record from Library of Congress

LEADER: 03147cam a22003854a 4500
001 2010019530
003 DLC
005 20150129081213.0
008 100518s2011 fluab b 001 0 eng
010 $a 2010019530
016 7 $a101531192$2DNLM
020 $a9781439835920 (hardcover : alk. paper)
020 $a1439835926 (hardcover : alk. paper)
035 $a(OCoLC)ocn624405718
040 $aDNLM/DLC$cDLC$dYDX$dNLM$dYDXCP$dCDX$dDLC
042 $apcc
050 00 $aRM301.25$b.C46 2011
060 00 $a2010 M-583
060 10 $aQV 736$bC4555m 2011
082 00 $a615/.190113$222
100 1 $aChang, Mark.
245 10 $aMonte Carlo simulation for the pharmaceutical industry :$bconcepts, algorithms, and case studies /$cMark Chang.
260 $aBoca Raton, FL :$bCRC Press,$cc2011.
300 $axxiii, 539 p. :$bill. (some col.), maps ;$c25 cm.
490 1 $aChapman & Hall/CRC biostatistics series ;$v36
504 $aIncludes 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.
650 0 $aDrug development$xComputer simulation.
650 0 $aMonte Carlo method.
650 12 $aDrug Industry$xmethods.
650 22 $aComputer Simulation.
650 22 $aDrug Design.
650 22 $aMonte Carlo Method.
650 22 $aTechnology, Pharmaceutical$xmethods.
830 0 $aChapman & Hall/CRC biostatistics series ;$v36.