Best Practices for Formulation and Manufacturing of Biotech Drug Products - How to maintain product stability and prevent particulates. - BioPharm International
Various light transmission or camera-based commercial systems are currently available in the market and can be used to perform
automated visual inspection (AVI) of sterile drug products.24–26 The automated inspection machine (AIM) used in this study uses a light transmission–based static division system to detect
particles of foreign contaminants in vials filled with liquid product. The vial containing the product is spun at a specified
speed followed by the application of brakes to stop the rotating vials. As the vial stops, the particles continue to stay
in motion while being suspended in the liquid, thereby causing interference in the incident light that is detected by the
sensor. The performance of an automated visual inspection system should be qualified and characterized before its usage for
inspecting drug products filled in sealed containers such as vials and syringes. A Knapp study can be conducted to establish
the human capability for visual inspection and to set the performance acceptance criteria for the AIM.27–28 In the case study presented here, process parameters that affect the performance of the AVI system, such as machine parameters,
product formulation, and fill configuration were evaluated. A standard vial defect set was prepared by seeding filled clean
vials with a single glass bead of size 70 μm, 100 μm, and 400 μm. Each seeded vial contained only one glass bead of a specific
size. Two vial sets comprising 24 vials each (six clean, and six of each particle size) were run through the AVI system 32
times and the detection results (accept/reject) for each vial were recorded. At the end, percent detection rate (% DR) of
the machine for each vial was evaluated as the ratio of the number of times the vial was rejected by the machine and the number
of times the vial was inspected. Studies using product mimic solutions were designed to evaluate the effect of each process
parameter on the defect detection rate by the machine.
Role of Machine Parameters
Figure 3
Key machine parameters affecting the process performance include spin speed (how fast the vial is spun, measured in rpm),
brake setting (how quickly inspection is performed after applying the brakes), sensitivity (signal to noise ratio), inspection
view height (based on liquid meniscus height), and background light intensity. Sensitivity and background light settings were
optimized and held constant throughout this study. Inspection view height was altered based on meniscus height. Various formulations
of different viscosities were then tested by changing the brake and spin speed settings. Figure 3 shows that increasing the
spin speed improves the detection rate, the impact being more significant for high viscosity products. Detection of the glass
particle by the machine requires the particle to move and stay suspended in the detection window. Higher spin speeds transfer
more momentum from vial to liquid and then from liquid to the glass particle, thereby resulting in larger particle movement
over longer durations. Inspecting the vials quickly after applying the brakes (a higher brake setting) also seemed to help
the detection rates.
Anurag S. Rathore, PhD, is a consultant, Biotech CMC Issues, and a member of the faculty in the department of chemical engineering at the Indian Institute of Technology. Rathore is also a member of BioPharm International's Editorial Advisory Board.
Articles by Anurag S. Rathore, PhD
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