Role of Product Formulation
Figure 4
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In addition to machine parameters, the product formulation also can have a significant effect on the ability of the machine
to detect particles. Similar to the observations in Figure 3, we observe deterioration in the detection rate as product viscosity
increases. For low viscosity solutions, a spin speed of 1,600 rpm is sufficient to achieve detection rates of >80%. However,
for high concentration products with viscosities >4 cP, process performance deteriorates significantly at low spin speeds.
Higher spin speeds of 2,200 and 2,800 are needed to achieve the same detection rate. Other product properties such as density
(relative to defect particle density) and surface tension also may affect the performance of an AVI system. Figure 4 compares
the detection rate (average of 100 μm and 400 μm) of the machine for two mimic solutions of equal viscosity (2.3 cP) but different
surface tensions. The formulation without polysorbate (PS-20) had a higher surface tension and was more challenging for the
AIM than the one with polysorbate for the detection of 400-μm particles. The results highlight the importance of using a representative
mimic solution that mimics not only a product's viscosity but other properties as well.
Role of Fill Configuration
Figure 5
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The fill configuration of the product SKU also affects AVI performance. The automated inspection of syringes can be more challenging
than vials because the smaller radius of syringe barrels reduces the momentum imparted to particles for a given spin speed.
The fill volume of the liquid in the container also can have a bearing on the ability of the machine to detect particles.
Figure 5 compares the machine performance for low and high fill volumes for two different vial sizes. For both 5 cc and 10
cc, the detection rate (plotted as the average of 100 μm and 400 μm) is lower for very low fill volumes. When the fill volume
is reduced, the inspection window available to the sensor becomes smaller, thereby reducing the detection rates. Intermediate
fill volumes did not impede performance as much as the low fill volumes.
The automated visual inspection of biopharmaceuticals is a key process step in the fill–finish process and offers several
benefits over manual inspection, including higher speed, better detection, and improved process consistency. The machine should,
however, be qualified and characterized before its usage for product lot inspection. Machine parameters, product properties,
and fill configuration are all important factors that determine the performance of the AVI system. In addition to actual product,
appropriate mimic solutions can be used to characterize the effect of these parameters and design an AVI process that is robust
and consistent.
PARTICULATES IN BIOPHARMACEUTICAL FORMULATION
Particles may be generated as a result of large-scale manufacture or because of an inherent property of the protein molecule.
The large-scale manufacturing of protein drug products involves processing steps such as purification, formulation, freeze–thaw,
filling, shipping, and storage. Stresses that are introduced during these steps can cause instabilities that can lead to aggregation
and particulation.29
Figure 6
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In this case study, we discuss some important factors that may be used to control particulation for a monoclonal antibody
product. The data presented are from the formulation development of a monoclonal IgG2 antibody. A typical example of visual
particulation in a biopharmaceutical liquid formulation is shown in Figure 6.
The particles in these formulations can be counted by instruments such as the HIAC Royco liquid particle counter and characterized
by purifying the particles and subjecting them to protein analysis. During formulation development, screening studies are
performed to study the effect of factors such as pH, buffering agents, excipients (sugars, surfactants), and protein concentration
to minimize the presence of particles.
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