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RD process opimization

What is the easy way to start RD process optimization for chemical experiments designing  where we can try out multiple different laboratory parameters (such as concentration, molar ratio, stirring rate, temperature, time and so on) in order to get the exact Active Pharmaceuticals Ingredients (APIs) profile.


Re: RD process opimization

It all starts with leadership of the R & D organization and creating a culture of analytics. Without this...the effort will either be stillborn or start and fizzle out. For some insight into the multitude of issues associated with the 'culture of analytics' I suggest watching this JMP Analytically Speaking On Demand webinar. My colleagues Lou Valente, @louv and Jon Weisz speak wisely from experience.


Re: RD process opimization



Just some thoughts/guidance on possible approaches. 


You will want to start off with a some sort of screening experimental design to find your active factors and any important interactions and this would require a Response Surface design or you could also try a Definitive Screening Design if it fits the bill.  You find more on both these approaches in JMP in the Help > Books > Design of Experiments Guide.


You mention wanting to achieve an "exact API profile".  For me exact indicates that it will be the one and only API profile, but with many active factors and interactions it is likely that there is more than one optimal solution or there are possibly uncontrolled or covariate factors that will only allow you to get close to exact with the equipment and knowledge that you have today.  As hard as they try, even NASA gets caught by surprise.


One other recommendation is to watch a video from Discovery Europe 2017.  Silvio Miccio offers an alternative approach for finding optimal material options using Principal Components, Covariate DOE and PLS.

This may or may not fit your needs, but it is worth taking a look at this approach.  


If you have JMP Pro, you should also look at alternative ways to model your data using the Generalized Regression platform.






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