Recent Development of Optimization of Lyophilization Process

Table 2

Summary of the optimization of lyophilization.

	Target variables	Notes	Ref.
Trial-and-error without mathematical model	CQAs, CPPs, CMAs	Optimization of freezing process	[13, 31, 32, 33]
		Optimization of primary drying process	[12]
		Optimization of secondary drying process	[34]
Use of mathematical model	CMAs (Tb, Rp, and so on) and CPPs (Ts, Pc, the drying time, and so on)	A partial differential equation (PDE)	[31, 34–44]
		A model predictive control (MPC)	[29, 42, 45, 46]
		A computational fluid dynamics (CFD)	[15, 47, 48]
		Kv-based modeling	[49]
Designs space	Pc-dm/dt plane (Figure 4)	Control of primary drying process	[13, 17, 18, 50–52]
		Control of freezing process	[53]
Scale-up	Kv, Pc	Vial-position dependency of Kv	[12, 54]
		A use of empty vials at the edge of the shelf	[17]
		Equivalent resistance model under the dust-free condition using HEPA-filtered airflow (without empty vials)	[55]
Process analytical technology (PAT)	Kv, Rp, Tb, and Pc, dm/dt	In-line optimization	[56–67]