FDA in the USA is a regulatory body which determines which drugs are favorable for human consumption and which not, but have you ever thought how pharmaceutical companies manufacture drugs adhering to all these standards by bringing the rejection rate to a bare minimum. Well we all say ‘to err is human’ but has anyone thought about how does pharma companies go about doing their work .No!!!…then just read on
Process Analytical Technology (PAT) is a very common term used in the Pharmaceutical sector, now the main advantage here is that it helps in detecting faults very early and also helps in determining the quality of a batch even before it’s completely produced. Now don’t stop here by screaming….Eureka!!!! Because this is just the tip of the iceberg and you still have a lot to understand.
Generally while manufacturing a drug the main feature that should be kept in mind is the conditions in which the process takes place and the stability of the final product. In the past what used to happen was that a drug was developed and then it went for a laboratory analysis to verify the quality. But what is really needed here is a good process that should be in place and that too without flaws so that the moment the final drug comes out we are sure that this product is our desired result and that we will not need to discard it since it matches our quality parameters.
The most important department is the Quality control as they must be present right from raw material collection to the final moment where the drug is packed. They look into the safety of every thing; random samples can be tested to check hardness, colour and other important features.
Now the main problem with the primitive form of testing is that we check to see if the final drug is good only after a batch is manufactured, so there is always a chance of a complete batch rejection in case a randomly tested sample does not pass QC .So it is this factor that has made the FDA encourage companies to use Process Analytical Technology (PAT) in pharmaceutical production and quality control.
Now PAT is a method which is based on timely measurement of critical quality parameters and other performance attributes so that the end result is having the desired quality and is acceptable. They involve optimal applications of process analytical chemistry tools, feedback process control strategies etc
Quality what I feel doesn’t come to a product from space but it should be incorporated into it i.e. it should be built in or should be by design. PAT actually helps to shift focus from the conventional off-line testing i.e. having a separate lab for testing to scientific and in-line testing.
Now in-line testing basically means infrared (NIR), Raman, Mid-IR spectroscopy, acoustic emission signals, and other imaging techniques, or other physiochemical techniques as a primary means of process monitoring. NIR as a method is very useful because while testing using other techniques there is a high chance of a reaction with the chemicals in the existing drug while NIR on the other hand has high penetration power and does not destroy or react with samples. Sampling error would be minimized with in-line probes placed strategically through out the production process.
So the advantage here is that we not only can have a continuous monitoring of the quality but can do timely adjustments as well to make sure the final product is of high quality and is of desired specification.
Chemometrics is the application of mathematical, statistical, graphical or symbolic methods to maximise the chemical information, which can be extracted from data. An important concept in chemometrics is Multivariate Data Analysis (MVA), which can be defined as considering multiple variables simultaneously. Multivariate Data Analysis includes the use of Principal Component Analysis (PCA), Multiplicative Scatter Correction (MSC), Partial Least Squares Regression (PLS), and Standard Normal Variate Transformation (SNV) and once the data from in-line testing is obtained, MVA finds relations between columns in data tables
The objective is often to use one set of variables (columns) to predict another for the purpose of optimisation and to find out which columns are important in the relation. There can be missing data in the data table and if they exist it would mean less information is available in the table to analyse.There are a lot of softwares in the market right now that helps us analyse these data like The Unscrambler from CAMO Software and other companies like Umetrics, Matlab etc also have similiar products.
So we can finally say that PAT as a technique is very useful since it helps us in saving a lot of time and money by reducing the number of rejected batches and prediction of quality of batch even before completion. Where as batch process on the other hand will work only after a batch is completed and if the red light blinks i.e. the rejection sign pops up then well it would mean a huge loss for the company