Introduction
Quality Control is an integral operational part of the pharma industry where drugs at various stages of production, raw materials, finished products, and other related states are systematically checked for efficacy and safety to detect and remove deviations and defects.
Quality Control, along with different sections of pharma, works to mitigate the risks related to the product’s adverse effects, recall, and legal complications to improve the product’s reliability, safety, and quality.
Pharmaceutical Quality control generates a considerable amount of data due to its critical nature of measuring and monitoring product quality. Additionally, using electronic devices & instruments for sample collection, analytical instruments to test the sample, and computers for record-keeping has also increased the amount of data in pharma quality control.
The amount of data generated through QC processes is analyzed to make many useful decisions. It helps to detect faults or deviations at various stages of different manufacturing operations. Additionally, process improvement is also performed through the use of data collected at QC.
Traditional Strategy for Quality Control
The traditional QC approach is to use manual and human-based methods to inspect & collect samples. The sample is taken at the end of the manufacturing process and after fixed frequency. The process is also repeated when a defect is detected.
The sample is transferred to the laboratory, where the analyst performs the required test. Depending on the test, it could sometimes take days for the final result; until then, the production process remains on hold. Human error is also possible during the test, which could also hamper the quality of the product. The capacity of the instrument is also limited, making the process more dependent and time-consuming.
This type of intermittent sample collection and measurement is reactive and initiates on a fixed frequency or time interval. Process improvement can be achieved in limited terms and does not focus on real-time analysis, rather than initiates on a fixed frequency or time interval. It is also not capable of testing the entire manufacturing process continuously because testing the process continuously will disturb the productivity of the pharma organization.
Data-driven strategies for quality control
The opposite of a transitional QC strategy is a data-driven strategy. In this technique, different data points are used to collect all relevant datasets and use these data sets to detect quality issues. Different data techniques effectively collect all the required data and pass collected data to analytics to make informed & early detection and decisions. Quality control can be applied continuously rather than spontaneously and/or after fixed intervals. It increases flexibility for the QC personnel for monitoring and decision-making.
Data data-driven strategy enables personnel to act proactively to predict and prevent faults before they occur. It is made possible by smart sensors that provide real - time value of the process going on. The data collected is then used to improve the process during the production stage by altering different process variables. It results in higher efficiency and quality control in the pharma process.
Components of a Data-Driven Quality Control Strategy
Data-driven strategies are enabled by a series of components that play their corresponding part in implementing their role.
Some core components of data-driven quality control include but are not limited to, the following.
Data Collection
Data collection is used to measure the required parameters from the manufacturing process. The main difference between these data collection and traditional data collection techniques is their ability to measure the parameter without taking out the sample to the lab and waiting for the results. These data collection sensors can collect directly from the process and measure the real - time value.
Another major difference is that result of sensors are made available in a real-time manner.
The sensors for data collection are direct...
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