To understand the removal of impurities during biopharmaceutical manufacturing processes, analytical techniques such as high
performance liquid chromatography (HPLC), enzyme-linked immunosorbent assay (ELISA), and real-time-polymerase chain reaction
(PCR) are required. Typically, the product-related impurities are analyzed by HPLC and process-related impurities are analyzed
by real time-PCR for host-cell DNA and ELISA for host-cell proteins content. Here, we present work done to enable HPLC and
real time-PCR analysis for use as process analytical technology tools.
(GARY S CHAPMAN/GETTY IMAGES)
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Manufacturing of a majority of biotech therapeutics involves using a host cell to produce the product of interest. However,
the cell produces not only the product of interest, but also various product-related impurities (via deamidation, aggregation,
and truncations) and host-cell-related impurities (endotoxins, nucleic acids, and host-cell proteins). This necessitates developing
a multistep, robust purification process that is capable of providing adequate clearance to these impurities and yielding
a product of purity that meets regulatory expectations. Chromatography often forms the core of the purification process because
of its capability to provide high resolution separations, scalability, and robustness.
Process analytical technology (PAT) is a system used for designing, analyzing, and controlling manufacturing through
timely measurement (that is, during processing) of critical quality and performance attributes of raw and in-process materials
and processes, with the goal of ensuring consistent product quality (1–5). It is important to understand that the goal of
PAT is not only the use of these analytical techniques for monitoring, but also to control the manufacturing process to consistently
yield the desired product quality (2,3).
When performing process-scale chromatography, because of the high resolution separation being performed, it is often the case
that baseline separation between the product and the impurities is not achieved. Typical industry practice in such cases involves
fractionation of the product peak into multiple small fractions, analysis of the various fractions for purity, and pooling
of the fractions as per preset purity-based pooling criteria (6–8). This practice, however, has its own share of deficiencies.
Collection of fractions, sampling of fractions, holding the fractions until analysis is complete, and, finally, pooling of
fractions may necessitate open operation and increases the vulnerability toward product contamination. Product degradation
may occur while it is held in storage for the analysis of the fractions to be complete (often 10–20 h). High performance liquid
chromatography (HPLC) and quantitative polymerase chain reaction (qPCR) are two of the most commonly used analytical methods
for monitoring product-related impurities and host-cell nucleic acids, respectively. This article addresses how to use these
tools in a manner that facilitates PAT implementation and results in an efficient and robust process.
Case Study
The application under consideration uses process-scale chromatography (cycle time 2 h) to separate the product from a product-related
impurity. Presently, the eluate from the column is collected as fractions (every 5 min) and stored until the analytical results
are declared. The analysis time is 45 min, and it takes ~10 h for analysis. This long analysis time decreases the productivity
of the manufacturing plant. HPLC is used in this case for the measurement of product purity.
Host-cell nucleic acid (DNA) is a critical quality attribute for biotech therapeutics. Near complete removal of DNA is necessary
for achieving product approval (9–11). For robust operations, DNA is measured at the various stages of the process: the harvested
broth, clarified harvest, affinity chromatography, anion-exchange chromatography, cation-exchange chromatography, and tangential
flow filtration. The currently available analytical methods such as the threshold method, slot-blot hybridization, and qPCR
require high analysis times (~9 h). Furthermore, presently each sample type requires a different sample preparation protocol,
which is often tedious to perform.
In the following sections, we discuss the development of these two methods to enable us to monitor these critical quality
attributes (CQA) with the same accuracy and precision as the existing methods, but at a significantly smaller analysis time
to facilitate PAT implementation.
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