In order to obtain enhanced control over the process, PAT tools are
employed. In US FDA guidance for Industry regarding PAT [228], PAT
is defined as a “A system for designing, analyzing, and controlling
manufacturing through timely measurements (i.e., during processing)
of critical quality and performance attributes of raw and in-processmaterials
and processes with the goal of ensuring final product quality”.
Typically in the lab-scale spray drying equipment, temperature, relative
humidity and pressure probes are employed. PAT tools for spray drying
in small scale equipment are not so widely employed until now except
for research purposes. However, at pilot and industrial scale they are extensively
used and encompass various aspects of the process. Consistency
of the raw material is important from a regulatory perspective and
handheld near infra-red (NIR) devices can be used for raw material
characterization. Process turbidimetry, viscosimetry and laser diffraction based devices ensure that feed has optimumphysical characteristics
before being sprayed. Particle sizing of solute in feed is extremely
important not only to avoid nozzle clogging but to ensure that
no solute crystallization takes place in the solution itself. During the process
PAT tools areemployed for real-timespray pattern and particle size
distribution analysis. Spray pattern analysis can prevent deposition on
drying chamber and determine if droplet size distribution is appropriate.
Particle size distribution is critical for dissolution and tableting of
the powder [229,230]. Specifically for the spray drying of ASD, NIR
and Raman probes are useful to analyze the polymorphic changes in
the product and exhaust gas analysis for solvent content. In order to reduce
residual solvent content to appropriate level secondary drying step
is required [95]. Process mass spectrometry is useful to monitor the exhaust
gas and NIR probes can perform end-point solid state characterization.
All of these PAT tools can be employed in-line and helpmaintain
process feedback loops which lead to process correction by analyzing
the real-time data thereby saving time and money.