Artificial Intelligence (AI) Driven Machine Learning Modeling for Process Characterization of Dynamic Freeze Drying (Lyophilization) After Spray Freezing

Introduction

Spray freeze drying forms a frozen pellet from liquid under cryogenic conditions as droplets are formed and pass through a tower. Subsequently, the frozen pellets as a bulk bed of particles are dynamically lyophilized in a rotating drum. Energy application from an infrared source, the controlled temperature of the drum surface and vacuum conditions allow the drying of the pellets under freezing conditions (Figure 1). The process has distinct advantages in the product format, faster processing time, and lower energy consumption compared to a standard lyophilization process. (1, 2).

The creation of solid pellets in bulk (Figure 2), allows for room temperature stability and the opportunity to ship bulk drug substance without cold chain constraints. The pellet nature of the product is good for flexible filling of different doses and combination of different products. While most often considered for pharmaceuticals and diagnostics, the process has been used in a wide range of products and could even be considered for nutritional ingredients or foods where a high level of the product characteristics must be maintained during processing and volumes are limited (3, 4).