Historically, pharmaceutical production involves the manufacture of the finished product, followed by laboratory analysis to verify quality. The disadvantages associated with this approach are continual process optimization, recurring manufacturing difficulties, and the possibility of failed batches. The Food and Drug Administration (FDA) is inviting discussions throughout the pharmaceutical industry concerning a new mode of operation, which will address these concerns. This mode of operation is known as Process Analytical Technology (PAT).
This article provides an overview of Process Analytical Technology and its
application to the pharmaceutical industry. Techniques and terminology common
to these methods will be described to provide an introduction to PAT. The
scope of this article is to introduce the reader to PAT. It, however, is a
wide-ranging subject, which is expanding rapidly.
Process Analytical Technologies involve the use of raw material properties,
manufacturing parameters, process monitoring, and chemometric techniques to
produce finished products of acceptable quality. The central point of PAT is
to generate product quality information in real-time. The advantages of PAT
are many and varied. While process monitoring traditionally involved
temperature, pressure, flows, pH and other physical parameters, PAT focusses
on the use of in-line testing using near infrared, Raman, or other
physiochemical techniques as a primary means of process monitoring. The data
retrieved would provide information on the properties of blends, cores, and
other stages in the process. Through the use of probes in the process,
uniformity, drying, and mixing endpoints, and other targeted stages can be
pinpointed to a high degree of certainty. Sampling error would be minimized
with in-line probes placed strategically through out the production process.
The first step away from off-line testing (laboratory separated from the
production plant), would be at-line testing. This is the movement of process
dedicated testing equipment to the production line to provide rapid results.
One advantages is elimination of the transfer of samples involving time
delays. Along with traditional tests such as dissolution, assay, friability,
hardness, and thickness, this could also include accelerated dissolution rate
analysis, and NIR tablet analyzers. One approach of process analytical
chemistry is on-line testing, which either draws samples or monitors
periodically. Another mode is known as in-line testing, which places probes
in constant contact with drug product. The advantage of on/in line testing is
better control of the process. Beyond data such as blending, or drying, the
FDA has proposed creating on/at-line assurance of dissolution rates using
analytical data correlations. Near infrared (NIR) is one of the techniques
that has gained recent recognition as a means to add on or in-line analysis
at the production level. The near-infrared light does not destroy or react
with samples and is able to penetrate into and through solid samples. While
NIR has gotten most of the attention, PAT is not limited to NIR but can
include many other forms of monitoring, such as Raman, Mid-IR, acoustic
emission signals, and other imaging techniques.
Dissolution is the current primary method for evaluating solid oral dosage
form consistency and similarity. Using PAT, processes would be under such
high control that the dissolution results could be accurately predicted well
before the product is analyzed. Research on the correlation between
dissolution results and measured process parameters would be performed so
that the impact of process, raw materials, and finished product variables
would be understood. The manufacturing process could be continuously
monitored and adjustments made to ensure that the finished product would meet
the desired specifications. Measurements from these techniques have already
been used successfully to give predictive values for dissolution, content
uniformity, assay, moisture, and hardness. The data produced by these devices
are rich with information that is highly complex. These correlations must be
performed with the use of chemometrics.
Previously, manufacturing processes have been treated in a univariate manner,
with single parameters tracked by control charts. However, the reality is
that physio-chemical processes are multivariate with subtle interactions of
variables. Chemometrics is the intersection of chemistry and the mathematics
of large matrices of data. Chemometrics is complex and requires the use of
computers and software to perform the necessary computations. These
techniques reduce large amounts of data into a few recognizable components
without any loss of data. Two chemometric techniques that have been found to
be useful are Principal Component Analysis (PCA) and Partial Least Squares
Regression (PLS). These techniques are recognized for their ability to
eliminate noise, identify latent variables, and extrapolate missing data.
PCA is a technique of creating data models of previously produced and tested
batches to verify similarity to newly created batches. One advantage this
technique has over the commonly used f2 metric is that batches are now
compared to a substantial compilation of batches included in a validated
model. Trends could potentially be identified earlier than with an f2
comparison. This could help improvement of process consistency after scale up
and post approval changes. Another advantage of PCA is that it can handle the
large amounts a data produced by dissolution fiber optic (Dis-FO) techniques
without the need to reduce data points.
PLS is used to correlate data, such as finished product dissolution results,
to raw material, process parameters, and in-line readings. Variables which
affect the dissolution rate can be better understood and monitored. The
effect of scale ups and post approval changes can be quantified. Critical
parameters can be controlled, thereby creating high quality drug product,
less level/stage 2 testing, and minimal product failure. When out of
specification results do occur, drug products can be better investigated
through the use of PLS to determine which underlying variables contributed to
the failing drug product.
As can be seen in the above discussion, the use of PAT techniques can be a
huge benefit to those who choose to use the technology. Process Analytical
Technology provides better knowledge of raw materials, manufacturing
parameters and their impact on finished product quality. This will result in
a more robust process, better products, more uniform dissolution results, and
a huge cost savings for the manufacturer. The challenges that dissolution
scientists face are to become familiar with the next generation of
pharmaceutical testing and its potential applications in pharmaceutical
testing.
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