Keeping up with complexity — Bioprocesses are complex — thus, frequent measurement and data-driven real time process management are needed to keep complexity in check. The demand for a PAT that guarantees GMP and includes quality by design calls for specialised on-line sensor solutions. And recent technological developments are up to the task ...
Modern therapies of different diseases very often utilize drugs derived from living cells. However, manufacturing of these biopharmaceutical products is a complex process. One of the biggest challenges in biopharmaceutical production is to ensure reproducibility of the yield. The very nature of this challenge is rooted in the heterogeneity of a typical bioprocess, where minimal variations of the process conditions may lead to different yields.
It’s been 15 years since the FDA first released its Process Analytical Technology (PAT) initiative, challenging the biopharmaceutical market to adopt quality innovations through real-time monitoring and control of their processes.
To properly apply PAT, it is essential to move from the manual sampling and laboratory measurement procedures to automated control of critical process parameters. While the initiative has indeed spurred valuable new technologies, the journey to a fully quality-by-design future is still in its early stages with monitoring of many critical process parameters (or CPPs) having room for progress.
Critical Process Parameters for PAT
The most classical example of PAT applied to bioprocesses is the maintaining of a culture’s pH-value at a pre-defined set-point based on an in-situ electrochemical sensor signal. The signal is used to automatically regulate the addition of a base or acid (or the control of CO2 for processes using mammalian cells).
Other CPPs that have been available for in-line measurement for some years are dissolved CO2 and dissolved oxygen. Dissolved CO2 is a parameter, which is monitored due to its influence on pH values in mammalian cells and the synthesis fatty acids. The currently available dissolved CO2 process sensors are based on electrochemical principals. They are, however, affected by high maintenance costs to ensure an acceptable measurement accuracy.
Sensor specialist Hamilton is a pioneer in the optical sensor technology for the measurement and control of dissolved oxygen (DO). This technology has begun to supplant polarographic measurement and is now considered to be the state-of-the-art for the in-situ measurement of bioprocesses.
In addition to the above mentioned parameters, proper monitoring of the nutrient (or substrates) concentration, as well as the measurement of secondary metabolites is important, especially for fed-batch and perfusion processes, as the feeding strategies can be controlled during the process.
In-line and on-line sensors are typically based on molecular spectroscopy technologies like Near-Infrared (NIR) and Raman. They are secondary measurement technologies, meaning measurement with off-line reference methods are required to calibrate them through use of statistical multi variate data analysis (MVDA).
Last but not least, also the temperature is a fundamental and well-controlled parameter. Bioprocess productions are typically monitored and controlled tightly to an optimal process specific temperature, including during sterilization cycles.
Monitoring these CPPs makes it possible also to maintain the related product Critical Quality Attributes (CQA) and process Key Performance Indicators (KPI) within the pre-defined limits.
Measuring KPI On-Line: A Matter of Sensors
Besides product quality and product titer, the total and viable cell density are key performance indicators, which, according to PAT, should be measured as often as possible. While measurements of product quality and titer today are still mostly performed at-line (due to limitations of currently available in-line technologies based on spectroscopic principles), there are now new technologies available to measure total and viable cell density continuously in-line.
How Intelligent Sensors Assure PAT
The FDA’s PAT framework calls for in-line process sensors that can move a measurement from manual sampling and laboratory instruments to automated control of CPPs and KPIs. This not only requires sensor technologies that can measure the individual parameters in-line while being able to withstand the Cleaning-In-Place (CIP) and Sterilization-In-Place (SIP) procedures.
It also requires sensor intelligence that leverages communication with the PCS and documentation needs. In the past 30 years, Hamilton Process Analytics has reshaped the monitoring landscape and, since 2009, brought the PAT framework closer to reality with the introduction of intelligent Arc sensors.
These Arc sensors “talk” directly to the PCS without the need for an additional transmitter. They not only send a compensated measurement value used to control processes, but also a host of diagnostic functionality on each sensor that is recorded automatically. The data recording and transmission are designed to meet or exceed FDA and GMP regulatory guidelines.
The information may be used immediately, as in the case of a process deviation, or for a future decision, such as when to calibrate or replace the sensor. This information is available through Hamilton’s Arc Air software on a mobile device (Android or iOS) or PC.
Where we’re going
Recent technological advances were leveraged toward the development of intelligent sensors. Hamilton specifically developed the Arc intelligent sensor family in order to overcome the greatest challenges in previous user processes. Costly, bulky transmitters were eliminated, documentation automated, data enriched, and calibration simplified to vastly reduce the operational cost and effort and increase security. Despite all of these advances, there are always hurdles to overcome. PAT encourages more and more data acquisition, and technology will need to continue to advance for operators to acquire, maintain, and use this influx of data.
Hamilton is continually working on ways to simplify PAT compliance, from introducing new measurement parameters to progressing data management. Integration with cloud computing and Internet of Things (IoT) services will be the future of further simplifying the lives of plant operators and technicians. In the smart factory of the future, where so much is measured and documented, old data handling systems like those using the 4-20 mA protocol will not be able to keep up. The Ethernet protocol will be required to handle the rich data needed for modern processes. With more and more data available, a variety of new and retrospective analyses will be possible and could yield continuous improvement and new ideas for improving batch quality.
* * The author is Marketing Communication Manager at Hamilton Bonaduz, Planegg/Germany.