Over the past few years, the FDA has increased pressure on the pharmaceutical and biotechnology industry to become more innovative in manufacturing. Through issuing new guidance to the industry in 2003 and 2004, the FDA encouraged the use of new quality measurement tools known as Process Analytical Technology (PAT) that greatly increase the need for data collection, data access and data analysis systems.
The Road To Better Process Understanding
Implementing PAT not only helps ensure continuous compliance with FDA regulations, but such technologies offer bottom line business benefits to manufacturers who can now leverage greater process understanding. For example, time to revenue can be accelerated by shortening the tech transfer time and effort involved in the start-up of new product manufacturing. Process problems and failures can be minimized by using analytical technology to discern trends in the variability of critical process parameters and identify problems before they occur.
The Current State Of Affairs
There is no doubt that the requirements for systems validation/qualification (IQ, OQ, PQ) are based upon sound principles of software development and implementation. However, the FDA and the pharmaceutical industry both know that it is time to raise the bar and implement changes that focus not just on the control of systems within a GxP environment but that also lead to greater process understanding and improvement.
developing interoperability mechanisms to traditional enterprise business solutions such as ERP. At the same time, ERP vendors like SAP, known primarily for transactional processing systems, have purchased companies like Lighthammer (now re-badged as xMII) and are developing the linkage with shop floor systems such as MES, DCS, LIMS, etc. • Many of the large systems and services companies have realized that they can position themselves at the center of any systems strategies by providing a hub or middleware layer to act as the “policeman” or director
External manual data input for PAT purposes is shared and passed on to many different functional areas. |
Many pharmaceutical companies are standardizing the desktop and back office environments not only for economic and management reasons but also for consistency and reduced validation efforts. Typically these standards have been born out of the more conventional transactional processing arena. As we move towards analyzing more process (continuous) data, we may find some challenges to these standards and modifications may be required. One area of specific note is the existence of data warehouses and the potential that they bring to process understanding. Typically data warehouses are not real time and don’t contain continuous data. However, they can contain significant elements of data that will identify trends or directions. A PAT approach may be able to take advantage of this data/information even though it may be somewhat after the fact. PAT should lead to a framework that is capable of managing the manufacturing process and enabling far greater analysis of the resulting data to improve quality of both operations and product. Key to this will be accessing not just the raw production data but extended data that goes with it in order to maintain the context of that data. Clearly data recording of times, temperatures, flow rates, etc. are specific to the process, but data such as an equipment calibration date is supportive of the actual process and could be defined as meta data. As manufacturing companies increasingly recognize the benefits to adopting a PAT approach, they will drive the convergence of technology and application integration to a greater level. This, in turn, will drive more effective, risk-based manufacturing and ultimately will have a direct impact on the economic health of the entire industry.
About the Author
Stuart Davie is chief technology officer for Aegis Analytical Corporation. Davie’s experience includes more than 20 years of senior IT and management positions in the pharmaceutical, automotive, aerospace and engineering industries.