Boyan Li

Rapid characterization and quality control of complex cell culture media solutions using raman spectroscopy and chemometrics

The use of Raman spectroscopy coupled with chemometrics for the rapid identification, characterization, and quality assessment of complex cell culture media components used for industrial mammalian cell culture was investigated. Raman spectroscopy offers significant advantages for the analysis of complex, aqueous‐based materials used in biotechnology because there is no need for sample preparation and water is a weak Raman scatterer. We demonstrate the efficacy of the method for the routine analysis of dilute aqueous solution of five different chemically defined (CD) commercial media components used in a Chinese Hamster Ovary (CHO) cell manufacturing process for recombinant proteins.The chemometric processing of the Raman spectral data is the key factor in developing robust methods. Here, we discuss the optimum methods for eliminating baseline drift, background fluctuations, and other instrumentation artifacts to generate reproducible spectral data. Principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) were then employed in the development of a robust routine for both identification and quality evaluation of the five different media components. These methods have the potential to be extremely useful in an industrial context for “in‐house” sample handling, tracking, and quality control. Biotechnol. Bioeng. 2010;107: 290–301.

Performance monitoring of a mammalian cell based bioprocess using Raman spectroscopy

Being able to predict the final product yield at all stages in long-running, industrial, mammalian cell culture processes is vital for both operational efficiency, process consistency, and the implementation of quality by design (QbD) practices. Here we used Raman spectroscopy to monitor (in terms of glycoprotein yield prediction) a fed-batch fermentation from start to finish. Raman data were collected from 12 different time points in a Chinese hamster ovary (CHO) based manufacturing process and across 37 separate production runs. The samples comprised of clarified bioprocess broths extracted from the CHO cell based process with varying amounts of fresh and spent cell culture media. Competitive adaptive reweighted sampling (CoAdReS) and ant colony optimization (ACO) variable selection methods were used to enhance the predictive ability of the chemometric models by removing unnecessary spectral information. Using CoAdReS accurate prediction models (relative error of predictions between 2.1% and 3.3%) were built for the final glycoprotein yield at every stage of the bioprocess from small scale up to the final 5000 L bioreactor. This result reinforces our previous studies which indicate that media quality is one of the most significant factors determining the efficiency of industrial CHO-cell processes. This Raman based approach could thus be used to manage production in terms of selecting which small scale batches are progressed to large-scale manufacture, thus improving process efficiency significantly.

Fluorescence Excitation—Emission Matrix (EEM) Spectroscopy for Rapid Identification and Quality Evaluation of Cell Culture Media Components

The application of fluorescence excitation–emission matrix (EEM) spectroscopy to the quantitative analysis of complex, aqueous solutions of cell culture media components was investigated. These components, yeastolate, phytone, recombinant human insulin, eRDF basal medium, and four different chemically defined (CD) media, are used for the formulation of basal and feed media employed in the production of recombinant proteins using a Chinese Hamster Ovary (CHO) cell based process. The comprehensive analysis (either identification or quality assessment) of these materials using chromatographic methods is time consuming and expensive and is not suitable for high-throughput quality control. The use of EEM in conjunction with multiway chemometric methods provided a rapid, nondestructive analytical method suitable for the screening of large numbers of samples. Here we used multiway robust principal component analysis (MROBPCA) in conjunction with n-way partial least squares discriminant analysis (NPLS-DA) to develop a robust routine for both the identification and quality evaluation of these important cell culture materials. These methods are applicable to a wide range of complex mixtures because they do not rely on any predetermined compositional or property information, thus making them potentially very useful for sample handling, tracking, and quality assessment in biopharmaceutical industries.

Rapid quantification of tryptophan and tyrosine in chemically defined cell culture media using fluorescence spectroscopy

The rapid and inexpensive analysis of the complex cell culture media used in industrial mammalian cell culture is required for quality and variance monitoring. Excitation-emission matrix (EEM) spectroscopy combined with multi-way chemometrics is a robust methodology applicable for the analysis of raw materials, media, and bioprocess broths. We have shown that the methodology can identify compositional changes and predict the efficacy of media in terms of downstream titer [1]. Here we describe how to extend the measurement methodology for the quantification of tryptophan (Trp), tyrosine (Tyr) in complex chemically defined media. The sample type is an enriched basal RDF medium in which five significant fluorophores were identified: Trp, Tyr, pyridoxine, folic acid, and riboflavin. The relatively high chromophore concentrations and compositional complexity lead to very significant matrix effects which were assessed using PARAllel FACtor analysis2 (PARAFAC2). Taking these effects into account, N-way partial least squares (NPLS) combined with a modified standard addition method was used to build calibration models capable of quantifying Trp and Tyr with errors of ∼4.5 and 5.5% respectively. This demonstrates the feasibility of using the EEM method for the rapid, quantitative analysis of Trp and Tyr in complex cell culture media with minimal sample handling as an alternative to chromatographic based methods.

A rapid fluorescence based method for the quantitative analysis of cell culture media photo-degradation.

Cell culture media are very complex chemical mixtures that are one of the most important aspects in biopharmaceutical manufacturing. The complex composition of many media leads to materials that are inherently unstable and of particular concern, is media photo-damage which can adversely affect cell culture performance. This can be significant particularly with small scale transparent bioreactors and media containers are used for process development or research. Chromatographic and/or mass spectrometry based analyses are often time-consuming and expensive for routine high-throughput media analysis particularly during scale up or development processes. Fluorescence excitation-emission matrix (EEM) spectroscopy combined with multi-way chemometrics is a robust methodology applicable for the analysis of raw materials, media, and bioprocess broths. Here we demonstrate how EEM spectroscopy was used for the rapid, quantitative analysis of media degradation caused by ambient visible light exposure. The primary degradation pathways involve riboflavin (leading to the formation of lumichrome, LmC) which also causes photo-sensitised degradation of tryptophan, which was validated using high pressure liquid chromatography (HPLC) measurements. The use of PARallel FACtor analysis (PARAFAC), multivariate curve resolution (MCR), and N-way partial least squares (NPLS) enabled the rapid and easy monitoring of the compositional changes in tryptophan (Trp), tyrosine (Tyr), and riboflavin (Rf) concentration caused by ambient light exposure. Excellent agreement between HPLC and EEM methods was found for the change in Trp, Rf, and LmC concentrations.

Low-content quantification in powders using Raman spectroscopy: a facile chemometric approach to sub 0.1% limits of detection.

A robust and accurate analytical methodology for low-content (<0.1%) quantification in the solid-state using Raman spectroscopy, subsampling, and chemometrics was demonstrated using a piracetam-proline model. The method involved a 5-step process: collection of a relatively large number of spectra (8410) from each sample by Raman mapping, meticulous data pretreatment to remove spectral artifacts, use of a 0-100% concentration range partial least-squares (PLS) regression model to estimate concentration at each pixel, use of a more accurate, reduced concentration range PLS model to calculate analyte concentration at each pixel, and finally statistical analysis of all 8000+ concentration predictions to produce an accurate overall sample concentration. The relative prediction accuracy was ∼2.4% for a 0.05-1.0% concentration range, and the limit of detection was comparable to high performance liquid chromatography (0.03% versus 0.041%). For data pretreatment, we developed a unique cosmic ray removal method and used an automated baseline correction method, neither of which required subjective user intervention and thus were fully automatable. The method is applicable to systems which cannot be easily analyzed chromatographically, such as hydrate, polymorph, or solvate contamination.

Comprehensive, quantitative bioprocess productivity monitoring using fluorescence EEM spectroscopy and chemometrics

This study demonstrates the application of fluorescence excitation-emission matrix (EEM) spectroscopy to the quantitative predictive analysis of recombinant glycoprotein production cultured in a Chinese hamster ovary (CHO) cell fed-batch process. The method relies on the fact that EEM spectra of complex solutions are very sensitive to compositional change. As the cultivation progressed, changes in the emission properties of various key fluorophores (e.g., tyrosine, tryptophan, and the glycoprotein product) showed significant differences, and this was used to follow culture progress via multiple curve resolution alternating least squares (MCR-ALS). MCR-ALS clearly showed the increase in the unique dityrosine emission from the product glycoprotein as the process progressed, thus provided a qualitative tool for process monitoring. For the quantitative predictive modelling of process performance, the EEM data was first subjected to variable selection and then using the most informative variables, partial least-squares (PLS) regression was implemented for glycoprotein yield prediction. Accurate predictions with relative errors of between 2.3 and 4.6% were obtained for samples extracted from the 100 to 5000 L scale bioreactors. This study shows that the combination of EEM spectroscopy and chemometric methods of evaluation provides a convenient method for monitoring at-line or off-line the productivity of industrial fed-batch mammalian cell culture processes from the small to large scale. This method has applicability to the advancement of process consistency, early problem detection, and quality-by-design (QbD) practices.

Anisotropy resolved multidimensional emission spectroscopy (ARMES): A new tool for protein analysis

Structural analysis of proteins using the emission of intrinsic fluorophores is complicated by spectral overlap. Anisotropy resolved multidimensional emission spectroscopy (ARMES) overcame the overlap problem by the use of anisotropy, with chemometric analysis, to better resolve emission from different fluorophores. Total synchronous fluorescence scan (TSFS) provided information about all the fluorophores that contributed to emission while anisotropy provided information about the environment of each fluorophore. Here the utility of ARMES was demonstrated via study of the chemical and thermal denaturation of human serum albumin (HSA). Multivariate curve resolution (MCR) analysis of the constituent polarized emission ARMES data resolved contributions from four emitters: fluorescence from tryptophan (Trp), solvent exposed tyrosine (Tyr), Tyr in a hydrophobic environment, and room temperature phosphorescence (RTP) from Trp. The MCR scores, anisotropy, and literature validated these assignments and showed all the expected transitions during HSA unfolding. This new methodology for comprehensive intrinsic fluorescence analysis of proteins is applicable to any protein containing multiple fluorophores.

Chemometric approaches to low-content quantification (LCQ) in solid-state mixtures using Raman mapping spectroscopy

The low-content quantification (LCQ) of active pharmaceutical ingredients or impurities in solid mixtures is important in pharmaceutical manufacturing and analysis. We previously demonstrated the feasibility of using Raman mapping of the micro-scale heterogeneity in solid-state samples combined with partial least squares (PLS) regression for LCQ in a binary system. However, PLS is limited by the need for relatively large calibration sample numbers to attain high accuracy, and a rather significant computational time requirement for processing large Raman maps. Here we evaluated alternative chemometric methods which might overcome these issues. The methods were: net analyte signal coupled with classical least squares (NAS-CLS), multivariate curve resolution (MCR), principal component analysis with CLS (PCA-CLS), and the ratio of characteristic analyte/matrix bands combined with shape-preserving piecewise cubic polynomial interpolation curve fitting (BR-PCHIP). For high (>1.0%) piracetam analyte content, all methods were accurate with relative errors of prediction (REP) of <1.1%. For LCQ (0.05–1.0% w/w), three methods were able to predict piracetam content with reasonable levels of accuracy: 6.97% (PCA-CLS), 9.13% (MCR), and 12.8% (NAS-CLS). MCR offered the best potential as a semi-quantitative screening method as it was ∼40% quicker than PLS, but was less accurate due to being more sensitive to spectral noise factors.

Quantitative Analysis of Complex Liquids using Multi-dimensional Fluorescence Spectroscopy: from Oil to Vegemite

The quantitative analysis of complex fluorescent cell culture media mixtures used in industrial biotechnology is very desirable. Here we show how multi-dimensional fluorescence spectroscopy and chemometrics can be used across a complete industrial bioprocess.