Spectrometric techniques like near-infrared (NIR) and Raman are among the most appealing alternatives to traditional sensors for bioprocess monitoring. These techniques are robust, scalable, and capture tremendous quantities of process data in real time. Their only drawbacks are that they take effort and knowledge not only of spectroscopy, but of chemometrics and multivariate analysis.
The use of NIR has evolved, initially from raw materials testing, to final product quality control, and most recently to process monitoring. Advances in computing and chemometrics have contributed to this growth, together with the realization that NIR is suitable to microbial, fungal, yeast, and mammalian cell cultures (although not equally).
NIR's appeal stems from its advantages over traditional in- or at-line techniques: flexibility, simplicity of operation, rapidity of measurement, multiplicity of analysis, and the potential to predict chemical and physical parameters from a single spectrum.
Yet despite fulfilling nearly all objectives of FDA's Process Analytic Technology (PAT) initiative, adoption of NIR has been less than inspiring.
Not Ready for Prime Time?
AstraZeneca for example has experimented with NIR at the bench. “But we haven't yet had the opportunity to explore it at pilot scale,” admits Payal Roychoudhury, Ph.D., senior scientist at the company's Mölndal, Sweden facility. “To be honest, it is not used as extensively in process monitoring as it should be.”
NIR has numerous advantages for PAT programs, particularly with respect to critical-to-quality factors. NIR provides rapid, real-time, noninvasive, cost-effective monitoring with no sampling or sample preparation. Furthermore, it may be multiplexed with respect to both parameters and bioreactors.
It is also scalable and transfers well. “This is really important,” Dr. Roychoudhury explains, “as in its life cycle a typical biopharm product will transfer across scales and relocate geographically. Analytical models that are robust in the face of such changes are potentially applicable throughout the product's life cycle.”
NIR is not perfect. It is considered a secondary technique, meaning it does not directly measure analytes through intimate contact with a sensor. Users must expend significant effort into modeling, and the stability of fiber-optic probes it employs has been questioned.
For example, after repeated sterilization cycles, the NIR probe might undergo signal saturation or show drifting in spectral signals. “The fiber optics available today are generally silica or quartz and are quite fragile,” Dr. Roychoudhury notes. “Microfractures may, over time, lead to complete loss in transmission.”
NIR spectra are collected over the entire spectral range, from 800 to 2,200 nm, and provide multianalyte readings simultaneously in real time including cell counts, metabolite and nutrient uptake rates, and product levels. However, as Dr. Roychoudhury points out, the predictions from NIR are only as good as the reference assay method.
“Analytical modeling requires sophisticated mathematical treatments such as partial least squares in correlating the spectral data with the reference data for the respective analytes.”
NIR works especially well in cell culture (vs. fermentations) because the medium is clear and cell density, gassing, and agitation are low compared with microbial cultures. Barriers to adoption exist, however, including:
- investment of time, personnel, and equipment, particularly for one-off projects;
- validation and modeling;
- high level of user familiarity with the theory, mathematics, and instrumentation; and
- technology transfer issues, particularly transferring data from one system to another.
Functional groups do not absorb strongly in the NIR. This is a disadvantage for traditional benchtop analysis, but a powerful benefit in bioprocessing, says Robert Mattes, applications scientist at Foss NIRSystems.
NIR can simultaneously measure glucose glutamine, lactate, ammonia, pH, osmolality, and viable cell density. According to Mattes, NIR can distinguish between live and dead cells, which otherwise involves a time-consuming assay.
NIR is still considered an early-stage technology for bioprocessing. Biogen Idec and MedImmune have presented data on PAT applications. FDA appreciates the potential of NIR but has stopped short of endorsing it.
But NIR is not a simple plug-and-play technique. “It's not like a pH meter where you stick in the probe and get a number. NIR requires someone with an understanding of spectroscopy,” Mattes says. “People get excited about it, but then other high-priority projects come up or those championing the technology leave the company.”
In addition, chemometrics, statistics, spectroscopy, and multivariate analysis take time and skill that most biotechnology companies lack.