It is becoming a necessity to demonstrate to the regulator that quality is built into a product by understanding the process by which it is developed and manufactured.
PAT and lab automation tools provide better data for modelling, and more quickly, than ever before.
QbD of API chemistry is facilitated using DynoChem by enabling chemists to capture understanding in simple models from experimental data. Then to explore the design space and predict process performance on change of scale or equipment with understanding and control of sources of variability.
DynoChem fully supports the QbD initiative in the pharmaceutical industry and sponsors the annual AIChE Award for Excellence in Quality by Design.
What our users say:
"The use of mechanistic models in process development has multiple benefits. Mechanistic models enable systematic analysis of experimental data and quantification of intrinsic and/or scale-dependent process attributes."