Tag Archive | "DynoChem"

Envelope Please: AIChE Hands Out QbD Awards


In Minneapolis on Tuesday night, Joe Hannon, CEO of Scale-up Systems (DynoChem), noted how the Quality by Design track at this year’s AIChE annual meeting in Minneapolis was “more like going to M.I.T. than Las Vegas”–substance over glamor, in other words.

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America’s Top Modelers: Accelerating Pharma Process Development


By Paul Thomas, Senior Editor

This week in Rosemont, Illinois, DynoChem software (from Ireland’s Scale-Up Systems) hosted its annual North American user group meeting. User groups are wonderful opportunities to learn what’s really happening behind closed doors at leading companies. At the DynoChem meeting, chemical engineers and modeling experts from Eli Lilly, Abbott, Pfizer, Merck, GSK, Amgen, and other major manufacturers shared details of their current advanced process modeling.

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Well Versed: Remembering the Great Bards of QbD


Scientists often take to poetry to help make sense of the world, or perhaps just to take mental vacations. On his “Design Space and Quality by Design” blog this week, DynoChem’s Joe Hannon (also Program Chair for AIChE’s Pharma division) takes an enjoyable, and culturally uplifting, look back at two scientists, Stanley Corrsin and Lewis Fry Richardson, whose work may have helped shape today’s pharma chemistry and Quality by Design thinking, and who also took to rhyme and verse on occasion.

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A Very Brief History of the Dynamic Design Space


Joe Hannon, COO, DynoChem

(Editor’s Note: This first appeared, as a comment on the previous post, on the excellent QbD Viewpoint group on LinkedIn. A loaded question to you QbD practitioners: if the concept of such mechanistic models is  scientifically sound, could the apparent criticism of it at IFPAC have been politically motivated? – AMS)

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When Is a CPP Not a CPP?


By Alistair Gillanders, CTO & VP North America, DynoChem

I had a interesting discussion recently with a colleague in one of our major pharma customers about what should be used as a CPP. His concern was that often the CPP’s are basic parameters that are not scale sensitive and so if a process is moved between equipment and/or scales the parameters do not fully capture the challenges to retain quality and performance.

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