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Ideas to Implementation: Knowledge Management, Efficient Experimentation and Design Evaluation

 Ideas to Implementation: Knowledge Management, Efficient Experimentation and Design Evaluation

 

Kate Llewellyn, Scientific Investigator; Martin Owen, Quality by Design Innovation Leader, GlaxoSmithKline

Behind every new medicine from GlaxoSmithKline, there is a rigorous drug development process. This involves the evolution and optimization of the manufacturing process to produce medicines of consistently high quality (Quality by Design). This intensive work is underpinned by data and models that explain and predict the science that justifies our control strategies. In this talk we look at how we have translated innovative ideas from the JMP community and implemented JMP to add value. We will explain how we 1) use journals to make knowledge generation and communication more effective and efficient by structuring models and data visualization; 2) use JMP Scripting Language (JSL) for routine analysis tasks; 3) use data filters and performance plots to demonstrate the importance of sequential experimental design; 4) use custom design, supersaturated and definitive designs for efficient, tailored experimentation; 5) applied the Gauss-Danzig selector to analyze custom designs and collaborated with Brad Jones (SAS) and Dave Woods (University of Southampton) to write JSL that helped translate this into an accessible tool for mainstream scientists; 6) combine flexible exploratory data visualization with modeling techniques to provide on-the-spot insight; 7) increase our understanding of the benefits and limitations of different strategic approaches using simulations to evaluate design choices; 8) use the journal to collate best practices and accelerate learning across project teams by promoting "mindfulness and sense-making" when making design and analysis choices. Our aim is to share our experiences of implementation to provoke additional ideas for continuous improvement in implementing Quality by Design principles.

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