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Exploiting Statistical Experiment Design to Accelerate Pharmaceutical R&D 

Statistics Made Easy by Stat-Ease
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Learn how multicomponent and multifactor design-of-experiment (DOE) tools empower experimenters to quickly converge on the quality by design (QbD) “sweet” spot-ingredient and factor settings that meet all specifications at minimal cost. All examples come directly from pharmaceutical industries.
Engineers, chemists and scientists working on drug development will do well by attending this briefing on DOEs for process screening and characterization, response surface methods (RSM) for process optimization (e.g., manufacturing of generics), and mixture design for optimal formulation (e.g., active pharmaceutical ingredients-APIs).
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Learn the Keys to Successful DOE: • Keys to Successful DOE
Process characterization in the pharma industry: • Process Characterizati...
Combine mixture & process designs: • Streamlined Models for...
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21 сен 2024

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Комментарии : 3   
@bidec6
@bidec6 5 месяцев назад
Based on your experience do you think mixture designs can be effective in the development of concrete mixes. Just a random question? 58:00:01
@StatisticsMadeEasybyStatEase
@StatisticsMadeEasybyStatEase 5 месяцев назад
Absolutely. Check out the Crash Course for Mixture Designs video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-yWDDCeQ0JVA.html
@bidec6
@bidec6 5 месяцев назад
@@StatisticsMadeEasybyStatEase I will definitely check it out.
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