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001 9781315100388
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005 20220509193005.0
006 m o d
007 cr cnu|||unuuu
008 190628s2019 flu ob 001 0 eng d
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781315100388
_q(electronic bk.)
020 _a131510038X
_q(electronic bk.)
020 _a9781351585941
_q(electronic bk. : PDF)
020 _a1351585940
_q(electronic bk. : PDF)
020 _a9781351585927
_q(electronic bk. : Mobipocket)
020 _a1351585924
_q(electronic bk. : Mobipocket)
020 _a9781351585934
_q(electronic bk. : EPUB)
020 _a1351585932
_q(electronic bk. : EPUB)
020 _z9781138295872
035 _a(OCoLC)1105988368
035 _a(OCoLC-P)1105988368
050 4 _aRM301.25
_b.Y36 2019eb
072 7 _aMAT
_x029000
_2bisacsh
072 7 _aMED
_x072000
_2bisacsh
072 7 _aMED
_x090000
_2bisacsh
072 7 _aMBGR
_2bicssc
082 0 4 _a615.1/9
_223
100 1 _aYang, Harry,
_eauthor.
245 1 0 _aBayesian analysis with R for drug development :
_bconcepts, algorithms, and case studies /
_cHarry Yang and Steven J. Novick.
264 1 _aBoca Raton :
_bCRC Press, Taylor & Francis Group,
_c2019.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _a"A Chapman & Hall book."
520 _aDrug development is an iterative process. The recent publications of regulatory guidelines further entail a lifecycle approach. Blending data from disparate sources, the Bayesian approach provides a flexible framework for drug development. Despite its advantages, the uptake of Bayesian methodologies is lagging behind in the field of pharmaceutical development. Written specifically for pharmaceutical practitioners, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems throughout pre-clinical, clinical, and Chemistry, Manufacturing, and Control (CMC) development. Authored by two seasoned statisticians in the pharmaceutical industry, the book provides detailed Bayesian solutions to a broad array of pharmaceutical problems. Features Provides a single source of information on Bayesian statistics for drug development Covers a wide spectrum of pre-clinical, clinical, and CMC topics Demonstrates proper Bayesian applications using real-life examples Includes easy-to-follow R code with Bayesian Markov Chain Monte Carlo performed in both JAGS and Stan Bayesian software platforms Offers sufficient background for each problem and detailed description of solutions suitable for practitioners with limited Bayesian knowledge Harry Yang, Ph.D., is Senior Director and Head of Statistical Sciences at AstraZeneca. He has 24 years of experience across all aspects of drug research and development and extensive global regulatory experiences. He has published 6 statistical books, 15 book chapters, and over 90 peer-reviewed papers on diverse scientific and statistical subjects, including 15 joint statistical works with Dr. Novick. He is a frequent invited speaker at national and international conferences. He also developed statistical courses and conducted training at the FDA and USP as well as Peking University. Steven Novick, Ph.D., is Director of Statistical Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian computer programmer and is frequently invited to speak at conferences, having developed and taught courses in several areas, including drug-combination analysis and Bayesian methods in clinical areas. Novick served on IPAC-RS and has chaired several national statistical conferences.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aDrug development.
650 0 _aBiopharmaceutics.
650 0 _aClinical trials.
650 0 _aBayesian statistical decision theory.
650 0 _aR (Computer program language)
650 7 _aMATHEMATICS / Probability & Statistics / General
_2bisacsh
650 7 _aMEDICAL / Pharmacy
_2bisacsh
650 7 _aMEDICAL / Biostatistics
_2bisacsh
700 1 _aNovick, Steven,
_eauthor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781315100388
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c127811
_d127811