Shaileshkumar Karavadra - Applications Manager, Thermo Fisher Scientific
Introduction
One of the fastest growing parts of the pharmaceutical industry, biologics continue to gain traction due to their success in addressing previously untreatable diseases, while reducing the side effects associated with some therapeutics and invasive surgeries.
Yet the structure and chemical complexity of biologics, combined with the intricacy of cell-based manufacturing, can make it difficult to correctly characterize and quantify both upstream processes and downstream products.
Over the past decade and a half, the pharmaceutical industry has implemented Process Analytical Technologies (PAT) to design, analyze, and control manufacturing through timely measurements—with the goal of ensuring final product quality. A vibrational spectroscopy technology, Raman spectroscopy is particularly well-suited to PAT applications, especially in situations where information about the composition and variance of molecules is required.
Historically, pharmaceutical drugs were tested in the laboratory at the end of the manufacturing process to assure their quality before these products were released into the market. Yet in recent years, pharmaceutical manufacturers have been moving to Real-Time Release Testing (RTRT) to optimize release and stability testing—and ultimately improve quality and safety of the final biologic, while increasing productivity and reducing costs.
Rather than waiting until after the biologic is manufactured, RTRT assures the quality of in-process and the final product based on process data, typically by monitoring a combination of process controls and material attributes during the manufacturing process.
The exact approach to RTRT varies depending on the process requirements. RTRT may be used to control the process parameters, monitor product attributes, or both at appropriate steps throughout the manufacturing process. Critically, the RTRT strategy should be based on a firm understanding of the process and the relationship between process parameters, in-process material attributes, and product attributes.
As pharmaceutical manufacturers embrace this type of testing, Raman spectroscopy can be applied to many important aspects of the bio-manufacturing process—from identity and variance testing of raw materials and cell culture media to the final product testing of biologic drug products. Using Raman spectroscopy, researchers can obtain the high molecular specificity they need, while taking a non-destructive, non-contact approach to their analyses.
Testing Raw Materials
Today, biopharmaceuticals manufacturers typically use small-scale functional testing or limited analytical methods to test raw materials before accepting them. Yet these small-scale tests may not be representative of their overall performance. In some cases, this can lead to fluctuating process outputs—and in extreme cases, the failure to meet predefined release criteria.
Furthermore, many clinical products are developed using a small number of batches, resulting in a narrow range of raw material variation and thus a limited process understanding. Especially in upstream cell culture, the unforeseen variability of various components of the cell culture media can affect a product’s micro-heterogeneity and its critical quality attributes (CQA).
To evaluate high-risk raw materials, manufacturers typically employ a range of tests including identity tests, quantitative tests measuring the concentration of key ingredients in the raw material, batch-to-batch variability tests, and degradation tests.
One of the raw materials encountered in biologics manufacturing is cell culture media. Identification of cell culture media samples by traditional methods, such as amino acid or vitamin analysis, is expensive and requires significant analytical expertise and laboratory space. Using Raman spectroscopy, manufacturers can lower their costs, increase the portability of these tests, and extend analyses to researchers with limited skills operating the instruments.
Buffers are another set of critical raw materials used in downstream manufacturing. Osmolality is a measure of concentration and is considered a critical quality attribute and critical process parameter in bioprocessing. The yield and quality of a biologic are highly dependent on the optimization of the downstream process. Identity testing along with Osmolality of buffers can be carried out using a multi-attribute method based on Principal component analysis and Partial Least Squares.
Rapid testing of buffers through single-use flexi bags can be carried out using the fiber optics probe of a Raman spectrometer at the point of use with no need for sample preparation.
Final Product Identification of Biologics
Final product identification of biologics pre- and post-shipment is another regulatory requirement. Testing the product’s identity once the drug has been packaged, especially within glass vials, jars, and syringes, poses a significant analytical challenge in the manufacturing of biologics. Fill finish sites may not have the necessary analytical expertise to carry out the tests and may have to send the samples to the parent site or an external lab for testing—incurring additional time and costs.
Moreover, biologics must also be re-tested upon importation from an outside country into a European Union member state or when drug products are imported into the United States from other countries. A full list of tests is typically carried out, including final product Identity testing. For biopharma manufacturers, this involves either sending the samples back to the parent site for analysis or employing third-party labs in the country of import. This significantly increases costs and delays the delivery of highly needed drug products.
End product identity testing of biologics after fill-finish or pre-shipping to the fill-finish line is carried out by a variety of analytical techniques, depending on the molecule or registration dossier.
For example, the verification test for biologic proteins is peptide mapping—a long-established workflow for protein identification using liquid chromatography/mass spectrometry (LC/MS). This complex separation technique requires protein extraction and clean-up, enzyme digestion, one or more stages of liquid chromatography, and two phases of mass spectrometry before the final spectrum is matched against protein databases. Although a standard methodology, peptide mapping requires an analytical lab with qualified technical resources. It also entails extensive time for preparation, and introduces significant costs in solvents, columns, and analytical equipment.
With its high sensitivity and resolution, Raman spectroscopy can characterize the drug product by evaluating the fingerprint region of the molecule. Its sampling flexibility ensures repeatable measurements, with subsequent analysis that allows for rapid method development and deployment.
A Multi-Attribute, End Product Test Using Raman Spectroscopy
To test the use of Raman spectroscopy for a multi-attribute end product test, Thermo Fisher completed a feasibility study for a multinational drug manufacturer that involved differentiating 15 different types of drug products and determining the concentration of the two preservatives in these products.
The feasibility test involved 15 different types of biologic drug products varying in concentration from 0.5 mg/ml to 6 mg/ml. Concentration of two preservatives A and B ranged from 0.85 mg/ ml to 5.0 mg/ml and 0.42 mg/ml to 3.91 mg/ml, respectively. These commercial drug products were supplied in their native glass vials varying 
A reversed-phase high-performance liquid chromatographic (HPLC) is currently used for the final product identity test and quantitative measurement of two preservatives in the final drug product.
A Thermo Scientific DXR3 SmartRaman Spectrometer with universal sampling plate and 180-degree sampling module was used to acquire spectra of the 15 drug products. Each spectrum was acquired with one minute of scanning time using 532nm laser with 40 mW power. Ten spectra were acquired for each sample to accommodate the variability of glass vials and scattering effects.
Raman spectroscopy offers excellent selectivity, repeatability, and full wavelength range to characterize biologics based on the characteristic band assignment. Figure 1 shows the characteristic bands of a biologic drug product that were obtained using the DRX3 SmartRaman.
Due to the sensitivity of this technique, it was possible to detect the significant differences between the drug product and its placebo. Figure 2 shows the spectra of a sample containing a drug product against its placebo.
Figure 3 shows spectra of different classes of drug products. These spectra were used to build the discriminant analysis method with Thermo Scientific TQ Analyst Software, a validated qualitative and quantitative method building software offering full compliance for pharmaceutical applications.
The discriminant analysis classification technique can be used to determine the class or classes of known materials that are most similar to an unknown material by computing the unknown’s distance from each class center in Mahalanobis distance units. The discriminant analysis technique is typically used to screen incoming materials or final products to determine if they are compound or molecule a, b, or c.
Discriminant analysis methods typically specify at least two classes of known materials, but the method also works with only one class. Multiple standards may be used to describe each class (at least one class must contain two or more standards). In addition, multiple regions of the spectrum may be used for the analysis.
A discriminant analysis method applies the spectral information in the specified region or regions of an unknown sample spectrum to a stored calibration model to determine which class of standards is most similar to the unknown.
When the method is used to analyze an unknown sample or a class, the software performs a principal component analysis on the spectra of the standards and uses those results to determine score values for the unknown sample spectrum. The score plots are used to produce Mahalanobis distance values, which in turn are used to rank the classes.
The result of a discriminant analysis is the name of the class or classes that are most similar to the spectrum of the unknown sample. The Mahalanobis distance between the unknown sample and each reported class can also be reported. The closer each distance value is to zero, the better the match.
After cross-validation principal component scores revealed the class differentiation, the report indicated that all the classes of the different products were correctly identified and there were no mismatches to indicate false positives.
Measuring the Concentration of Drug Product Preservatives
As part of the feasibility study, the multinational drug manufacturer also wanted to determine if Raman spectroscopy could be utilized to replace the HPLC test for measuring the concentration of two preservatives in its drug products. The level of preservative A was 0.85 mg/ml to 3.07 mg/ml, and that of preservative B was 0.42 mg/ml to 2.57 mg/ml.
Pure samples of preservatives A and B were acquired for reference and to ascertain their presence in the final drug formulation.
Samples of varying concentrations were acquired using the same parameters as the spectra acquired for the identity test through the 3 ml vial (See Table 1).
Figure 4 shows the spectra of the drug product with the two preservatives. Four standards with the reference values were supplied in 3 ml and 10 ml vials and a validation sample to test the model for 3 ml and 10 ml vials.
Four spectra per standard were acquired and used to build the chemometric method. The final drug product samples were scanned with a DXR3 SmartRaman Spectrometer to acquire a full spectral range of 3500 to 50 cm-1 and captured with a single exposure of the CCD, avoiding the need to stitch together artifacts. The sample time took approximately one minute. Three spectra were collected per sample. The sample spectra were loaded into Thermo Scientific TQ Analyst Software for chemometric analysis using a partial least squares (PLS) method, relating the information present in two data tables that collect measurements on the same set of observations.
PLS analysis of the final drug product samples revealed excellent predictive capabilities within the range of materials tested. The spectra used to develop the PLS method for 3 ml cartridge are shown on calibration plots (Figure 5 and Figure 6) that compare the calculated preservative concentrations versus the actual concentrations. The calibration plot can be used to determine how well the method predicts the actual preservative concentrations in the samples.
The plot developed by the chemometric method resulted in a correlation coefficient of 0.998 for preservative A. The Root Mean Square Error of Calibration (RMSEC) was 0.0425 mg/ml, and the Root Mean Square Error of Prediction (RMSEP) calculated was 0.0372 for preservative A.
Additionally, the method for preservative B resulted in in a correlation coefficient of 0.999. The Root Mean Square Error of Calibration (RMSEC) was 0.0316 mg/ml, and the Root Mean Square Error of Prediction (RMSEP) calculated was 0.0496. The method was able to accurately predict the 3 mL validation sample and a real sample in solution (See Table 2). The prediction can be improved when suspensions are allowed to settle and liquid phase is analyzed.
When 10 ml vial calibration samples were added to the above PLS method, method performance remained the same and was able to accurately predict the validation samples (Table 3).
These results demonstrate that Raman spectrometry can be used in multi-attribute tests to establish final product identification and preservative concentrations by developing discriminant analysis and partial least square methods. Using these Raman techniques, researchers can successfully measure and monitor preservative concentrations either in a lab environment or at the line. The method developed shows excellent correlation with actual preservative concentrations with errors comparable to the reference analysis method.
Conclusion
As a growing number of pharmaceutical manufacturers adopt real-time release testing (RTRT), current methods can be laborious and time-consuming. With its high molecular sensitivity and non-destructive, non-contact approach, Raman spectroscopy can be used in many critical parts of the biologics manufacturing process—from identity and variance testing of raw materials and cell culture media to multi-attribute final testing of biologic drug products. Using Raman spectroscopy to monitor process controls and material attributes at the appropriate steps, pharmaceutical companies can speed their manufacturing processes, while obtaining the accurate and reproducible data they need to realize the promise of RTRT.
References
- European Medicines Agency. Guideline on Real Time Release Testing. https://www. ema.europa.eu/en/documents/scientific-guideline/guideline-real-time-release-testingformerly-guideline-parametric-release-revision-1_en.pdf
- Buckley, Kevin, & Ryder, Alan G. (2017). Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review. Applied Spectroscopy, 71(6), 1085- 1116. https://aran.library.nuigalway.ie/handle/10379/7177
Shaileshkumar Karavadra is an applications scientist at Thermo Fisher Scientific with more than 15 years of experience in the molecular spectroscopy industry. His experience includes working with the pharmaceutical, chemical, and food industries to implement vibrational spectroscopy solutions for material characterization, process monitoring, fault diagnosis, and final product characterization.
Subscribe to our e-Newsletters
Stay up to date with the latest news, articles, and events. Plus, get special offers
from American Pharmaceutical Review – all delivered right to your inbox! Sign up now!