| 000 | nam a22 7a 4500 | ||
|---|---|---|---|
| 999 |
_c38742 _d38742 |
||
| 008 | 190124b2010 xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9780824798604 | ||
| 082 | _a615.1907 LEW-G | ||
| 100 | _aLewis, Gareth A. | ||
| 245 |
_aPharmaceutical experimental design / _cGareth A. Lewis, Didier Mathieu and Roger Phan-Tan-Luu |
||
| 260 |
_aNew York _bInforma Healthcare _c2010 |
||
| 300 | _a498 p. | ||
| 365 |
_aINR _b4995.00. |
||
| 440 |
_aDrugs and the Pharmaceutical Sciences. _vVolume-92. |
||
| 500 | _aThis useful reference describes the statistical planning and design of pharmaceutical experiments, covering all stages in the development process-including preformulation, formulation, process study and optimization, scale-up, and robust process and formulation development.Shows how to overcome pharmaceutical, technological, and economic constraints on experiment design!Directly comparing the advantages and disadvantages of specific techniques, Pharmaceutical Experimental Design· offers broad, detailed, up-to-date descriptions of designs and methods not easily accessible in other books· reviews screening designs for qualitative factors at different levels· presents designs for predictive models and their use in optimization· highlights optimization methods, such as steepest ascent, optimum path, canonical analysis, graphical analysis, and desirability· discusses the Taguchi method for quality assurance and approaches for robust scaling up and process transfer· details nonstandard designs and mixtures· analyzes factorial, D-optimal design, and offline quality assurance techniques· reveals how one experimental design evolves from another· and more!Featuring over 700 references, tables, equations, and drawings, Pharmaceutical Experimental Design is suitable for industrial, research, and clinical pharmaceutical scientists, pharmacists, and pharmacologists; statisticians and biostatisticians; drug regulatory affairs personnel; biotechnologists; formulation, analytical, and synthetic chemists and engineers, quality assurance personnel; all users of statistical experimental design in research and development; and postgraduate and postdoctoral research workers in these disciplines. | ||
| 650 | _aDrugs--Research--Statistical methods | ||
| 700 | _aMathieu, Didier | ||
| 700 | _aPhan-Tan-Luu, Roger | ||