New Scale-Up Technologies for Multipurpose Pharmaceutical Production Plants: Use Case of a Heterogeneous Hydrogenation Process

Minimizing the effort associated with the pilot and laboratory-scaleexperiments needed for a successful scale-up of a process from laboratoryto production scale is a significant challenge in process development.Efficient scale-up is becoming increasingly important in process developmentdue to the growing pressure to reduce costs and timelines while achievinga first-time-right approach. This article describes innovative technologiesthat enable direct and efficient process scale-up from the laboratoryto production scale, while concurrently optimizing scale-dependentparameters through in-depth process understanding. Those technologiesinclude a dynamic process model (based on a digital twin) and a laboratory-scaleimitation (Scale-Down-Reactor) of a specific production-scale reactor(4000 L). The core component of the Scale-Down-Reactor is a 3D-printedmetallic insert (H/C-Finger), designed to replicate the heat transferbehavior of the production reactor by maintaining a similar heat transfercoefficient and surface-to-volume ratio. In order to maintain comparablegas-liquid mass transfer between the scales, the Scale-Down-Reactorwas designed with geometric similarity to its large-scale counterpart.Both mass transfer and heat transfer were experimentally evaluatedfor the two scales, and the comparison demonstrated an excellent agreement.To finally prove and validate the concept, a hydrogenation processcurrently running at the production scale was conducted in the Scale-Down-Reactor.As a second technology, a dynamic process model is described thatincludes a kinetic model of the chemical reactions and a heat/masstransfer model (digital twin) of the aforementioned production-scalereactor. For the gas-liquid mass transfer model, an improvedmathematical description (equation) was developed. Moreover, the production-scalehydrogenation process conditions were efficiently optimized usingthe dynamic process model. The measured reaction mixture temperatureprofile of the optimized production batch demonstrated excellent agreementwith the profile predicted by the dynamic process model. By enablingdirect and efficient process scale-up while concurrently optimizingscale-dependent parameters, the technologies described within thisarticle offer a promising approach to reducing costs and timelineswhile improving process understanding.