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001 9781315099798
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040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781315099798
_q(electronic bk.)
020 _a1315099799
_q(electronic bk.)
020 _a9781351584173
_q(electronic bk. : PDF)
020 _a1351584170
_q(electronic bk. : PDF)
020 _a9781351584166
_q(electronic bk. : EPUB)
020 _a1351584162
_q(electronic bk. : EPUB)
020 _a9781351584159
_q(electronic bk. : Mobipocket)
020 _a1351584154
_q(electronic bk. : Mobipocket)
020 _z9781138296763
020 _z1138296767
035 _a(OCoLC)1128095424
035 _a(OCoLC-P)1128095424
050 4 _aRM301.25
072 7 _aMAT
_x029000
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072 7 _aMED
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072 7 _aMED
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072 7 _aTDCW
_2bicssc
082 0 4 _a615.1901519542
_223
245 0 0 _aBayesian applications in pharmaceutical development /
_cedited by Mani Lakshminarayanan, Fanni Natanegara.
264 1 _aBoca Raton :
_bChapman & Hall/CRC,
_c2019.
300 _a1 online resource (1 volume)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aChapman & Hall/CRC biostatistics series
520 _aThe cost for bringing new medicine from discovery to market has nearly doubled in the last decade and has now reached $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs/ analyses such as the Bayesian approach are essential to meet this need. This book will be the first to provide comprehensive coverage of Bayesian applications across the span of drug development, from discovery, to clinical trial, to manufacturing with practical examples. This book will have a wide appeal to statisticians, scientists, and physicians working in drug development who are motivated to accelerate and streamline the drug development process, as well as students who aspire to work in this field. The advantages of this book are: Provides motivating, worked, practical case examples with easy to grasp models, technical details, and computational codes to run the analyses Balances practical examples with best practices on trial simulation and reporting, as well as regulatory perspectives Chapters written by authors who are individual contributors in their respective topics Dr. Mani Lakshminarayanan is a researcher and statistical consultant with more than 30 years of experience in the pharmaceutical industry. He has published over 50 articles, technical reports, and book chapters besides serving as a referee for several journals. He has a PhD in Statistics from Southern Methodist University, Dallas, Texas and is a Fellow of the American Statistical Association. Dr. Fanni Natanegara has over 15 years of pharmaceutical experience and is currently Principal Research Scientist and Group Leader for the Early Phase Neuroscience Statistics team at Eli Lilly and Company. She played a key role in the Advanced Analytics team to provide Bayesian education and statistical consultation at Eli Lilly. Dr. Natanegara is the chair of the cross industry-regulatory-academic DIA BSWG to ensure that Bayesian methods are appropriately utilized for design and analysis throughout the drug-development process.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aDrug development
_xStatistical methods.
650 0 _aBayesian statistical decision theory.
650 7 _aMATHEMATICS / Probability & Statistics / General
_2bisacsh
650 7 _aMEDICAL / Pharmacology
_2bisacsh
650 7 _aMEDICAL / Biostatistics
_2bisacsh
700 1 _aLakshminarayanan, Mani,
_eeditor.
700 1 _aNatanegara, Fanni,
_eeditor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781315099798
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c126806
_d126806