Tracing NIRís Trajectory for Bioprocess Monitoring
By better combining and interpreting readily available data, biomanufacturing experts are gaining better control of fermentation and other processes, says Sartoriusí Roland Bienert.
By Paul Thomas, Senior Editor
From my perspective, a misstep we are still facing is the sole focus on accurate analyte concentration as a universal remedy for process monitoring. As far as closed loop process control is involved, that is crucial, no doubt, but in terms of process optimization, a qualitative overview of the process is much more beneficial than an ammonia profile. The strong demand of monitoring analyte concentrations inveigled some vendors and users to over-interpret correlations between analyte concentrations and spectral information, which led to instable calibration models.
Model robustness is another issue that is often concealed. A model based on one or two cultivation runs can not be used in a production environment, but shows nice error bars if an internal prediction set or cross validation is used. But to take batch-to-batch variations into account, a validation test set necessarily needs to be “unseen.”
That means the prediction error must be calculated from one (or more) cultivation runs, which are not part of the calibration set. By doing so, all errors increase to a certain extend but reflect real life. However, this is the recommended way of method validation for any NIR application.
PhM: In your view, are manufacturers getting more sophisticated in, say, titer prediction or end-point determination of fermentation processes? What's allowing them to do so?
R.B.: Both are highly requested and a lot of efforts have been made to set up robust models especially for titer. NIR spectroscopy is capable of high-titer prediction as well as highly suitable for end-point determination. For low-titer concentration and other hard-to-get parameters, the important step is to overcome the univariate sensor by sensor evaluation but use a multivariate model with several sensors contributing valuable information regarding the desired parameter.
The sensor information is usually available in real time. The crucial step here is data handling and automated combination for multivariate evaluation. Sartorius, in close cooperation with Umetrics, offers sophisticated solutions for next level models using multiple sensors. To think that a little further, it is not satisfactory to either offer sensors or software. It is important to have the expertise from spectra acquisition to generation and interpretation of trajectory in order to offer a one-stop solution. This is the road Sartorius will take.
PhM: Finally, our readers might not be familiar with Sartorius Stedim's PAT unit. What is the focus of the unit's work and offerings?
R.B.: Sartorius Stedim Biotech is a leading provider of cutting-edge equipment in the field of fermentation and cell cultivation supporting the biopharmaceutical industry. For a long time, Sartorius has offered a large variety of online sensors for both stainless steel and single-use bioreactors, including not only NIR but also micro wave resonance, off-gas sensors, glucose-lactate analysers, refractometry and many more.
Despite this broad sensor portfolio, for Sartorius, PAT is not only the implementation of a sensor. Our PAT unit is involved in numerous in-house projects that are part of an internal global PAT program initiated several years ago. We use PAT very successfully to optimize our own manufacturing processes as well as helping our customers to implement suitable PAT solutions.
As a total solution provider, Sartorius offers the whole range of PAT tools. This includes PAT consulting starting with risk analysis and the identification of critical process parameters. Therefore, we implemented Umetric DoE tool MODDE in our own SCADA software, the multi-fermentation control software (MFCS), in order to run designed experiments in several bioreactors in parallel. We also support our customers if requested in terms of MVDA and process integration. Here we accompany or perform the generation of robust calibration models based on one or more sensors. In terms of MVDA we are very happy to cooperate closely with Umetrics leading in multivariate software tools.
PhM: Also, can you share a bit about your group's work with TCI Hannover?
R.B.: We understand that not all players in the pharmaceutical industry want to evaluate a new sensor technology from scratch. Therefore, we are very happy to have a strong partner in academia like the group of Prof. Thomas Scheper. This cooperation allows us to provide our customers an overview of the new NIR adaptor, based on sound data and knowledge. The results of the Ingold port evaluation will be published in peer-reviewed journals. With this first step in sensor evaluation we can now focus on process specific topics at the customer site.