Process Analytical Technology: Applications to the Pharmaceutical Industry

Peter Scott,
Quality Assurance Analytical Services ,
AstraZeneca, Westborough, MA

email for correspondence: peter.scott@astrazeneca.com

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 Technology
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 advantage 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 amount of 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 challenge that dissolution scientists face is to become familiar with this next generation of pharmaceutical testing and its potential applications in pharmaceutical testing.

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