000 02804nam a2200265 a 4500
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008 111212t2011 flua f 001 0 eng d
020 _a9781439835920
020 _a1439835926
039 9 _a201204161110
_basmadi
_c201202151614
_dasmadi
_y201112121248
_zshah
040 _aUMP
090 _aRM301.25 .C43 2011
100 1 _aChang, Mark
245 1 0 _aMonte Carlo simulation for the pharmaceutical industry :
_bconcepts, algorithms, and case studies /
_cMark Chang
260 _aBoca Raton, FL :
_bCRC Press,
_c2011
300 _axxiii, 539 p. :
_bill. (some col.), maps ;
_c25 cm.
490 0 _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
999 _aVIRTUA40
_c61004
_d61010
999 _aVTLSSORT0080*0200*0201*0400*0900*1000*2450*2600*3000*4900*5040*5200*6500*6501*9991