Critical evaluation of models developed for monitoring an industrial submerged bioprocess for antibiotic production using near-infrared spectroscopy

A Process Analytical Technology (PAT) approach to control a new API manufacturing process: development, validation and implementation

Pharmaceutical companies are progressively adopting and introducing Process Analytical Technology (PAT) and Quality-by-Design (QbD) concepts promoted by the regulatory agencies, aiming the building of the quality directly into the product by combining thorough scientific understanding and quality risk management. An analytical method based on near infrared (NIR) spectroscopy was developed as a PAT tool to control on-line an API (active pharmaceutical ingredient) manufacturing crystallization step during which the API and residual solvent contents need to be precisely determined to reach the predefined seeding point. An original methodology based on the QbD principles was designed to conduct the development and validation of the NIR method and to ensure that it is fitted for its intended use. On this basis, Partial least squares (PLS) models were developed and optimized using chemometrics methods. The method was fully validated according to the ICH Q2(R1) guideline and using the accuracy profile approach. The dosing ranges were evaluated to 9.0-12.0% w/w for the API and 0.18-1.50% w/w for the residual methanol. As by nature the variability of the sampling method and the reference method are included in the variability obtained for the NIR method during the validation phase, a real-time process monitoring exercise was performed to prove its fit for purpose. The implementation of this in-process control (IPC) method on the industrial plant from the launch of the new API synthesis process will enable automatic control of the final crystallization step in order to ensure a predefined quality level of the API. In addition, several valuable benefits are expected including reduction of the process time, suppression of a rather difficult sampling and tedious off-line analyses.

Automated measurement and monitoring of bioprocesses: key elements of the M(3)C strategy

The state-of-routine monitoring items established in the bioprocess industry as well as some important state-of-the-art methods are briefly described and the potential pitfalls discussed. Among those are physical and chemical variables such as temperature, pressure, weight, volume, mass and volumetric flow rates, pH, redox potential, gas partial pressures in the liquid and molar fractions in the gas phase, infrared spectral analysis of the liquid phase, and calorimetry over an entire reactor. Classical as well as new optical versions are addressed. Biomass and bio-activity monitoring (as opposed to "measurement") via turbidity, permittivity, in situ microscopy, and fluorescence are critically analyzed. Some new(er) instrumental analytical tools, interfaced to bioprocesses, are explained. Among those are chromatographic methods, mass spectrometry, flow and sequential injection analyses, field flow fractionation, capillary electrophoresis, and flow cytometry. This chapter surveys the principles of monitoring rather than compiling instruments.

Lipolytic activity of chromoblastomycosis agents measured by infrared spectroscopy and chemometric methods

The lipase activity of nine strains of six chromoblastomycosis agents (Fonsecaea pedrosoi, Phialophora verrucosa, Cladophialophora bantianum, Cladophialophora carrionii, Rhinocladiela aquaspersa and Exophiala jeanselmei) grown on solid medium was investigated using Fourier transform infrared spectroscopy and hierarchical clustering analysis. The data was quantified by p-nitrophenyl palmitate assay using partial least squares (PLS) regression. These methods allowed the correlation of six genera and species within the 1230-1650 and 2800+3000 cm(-1) spectral ranges among strains grown for 14 days from their respective lipolytic activity with RMSEV=0.048 and R2val=0.95 and ten latent variables. The lipolytic activity also was predicted using PLS models with 1230-1650 and 2800-3000 cm(-1) and 900-1450 cm(-1) spectral ranges for strains grown for 21 days. The separate analysis of F. pedrosoi strains yielded a prediction model for biomass at 21 days with RMSEV=0.065 and R2val=0.95 with eight latent variables using (1100-1300)+(1330-1460)+(1550-1650) cm(-1) spectral regions The best model obtained with the clustering of P. verrucosa, C. bantianum, C. carrionii, R. aquaspersa and E. jeanselmei strains was constructed with the same spectral ranges, but with RMSEV=0.074 and R2val=0.94 and ten latent variables. Infrared spectroscopy is suitable for the quantitation of extracellular lipase activity linked to the biomass of chromoblastomycosis agents.

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories. This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.

Multiplexing fibre optic near infrared (NIR) spectroscopy as an emerging technology to monitor industrial bioprocesses

The application of near infrared spectroscopy in bioprocessing has been limited by its dependence on calibrations derived from single bioreactor at a given time. Here, we propose a multiplexed calibration technique which allows calibrations to be built from multiple bioreactors run in parallel. This gives the flexibility to monitor multiple vessels and facilitates calibration model transfer between bioreactors. Models have been developed for the two key analytes: glucose and lactate using Chinese hamster ovary (CHO) cell lines and using analyte specific information obtained from the feasibility studies. We observe slight model degradation for the multiplexed models in comparison to the conventional (single probe) models, decrease in r(2) values from 89.4% to 88% for glucose whereas for lactate from 92% to 91.8% and a simultaneous increase in the number of factors as the model incorporates the inter-probe variability, nevertheless the models were fit for purpose. The results of this particular application of implementing multiplexed-NIRS to monitor multiple bioreactor vessels are very encouraging, as successful models have been built on-line and validated externally, which proffers the prospect of reducing timelines in monitoring the vessels considerably, and in turn, providing improved control.

Simultaneous determination of glycerol and clavulanic acid in an antibiotic bioprocess using attenuated total reflectance mid infrared spectroscopy

Attenuated total reflectance mid infrared (ATR-MIR) spectroscopy is a potential technique for the near real-time monitoring of filamentous bioprocesses. Here we investigate the utility of ATR-MIR to monitor and predict concentrations of glycerol and product (clavulanic acid) in a complex antibiotic bioprocess. Streptomyces clavuligerus exhibits filamentous growth, thus, as biomass accumulates the process fluid becomes much more viscous, and develops pronounced non-Newtonian behaviour. A multivariate statistical technique, partial least square (PLS) has been used to develop models for the key analytes over the time course of the bioprocess. These models were then validated externally using unseen samples, not used in the original modelling exercise. Despite the heterogeneous nature of the bioprocess and the resulting complexity of the spectra, the models developed had high correlation coefficient values and low prediction error values of 0.302 and 0.009 for glycerol and clavulanic acid, respectively. The findings extend the use of ATR-MIR in these difficult fluids which are typical of filamentous industrial bioprocesses, and demonstrate the practical utility of the technique in the measurement of a range of analyte types, including those present at relatively modest levels compared to the concentrations of biomass and major substrates.

Chemometric analysis of in-line multi-wavelength fluorescence measurements obtained during cultivations with a lipase producingAspergillus oryzae strain

The filamentous fungus, Aspergillus oryzae, was cultivated in batch and fed-batch cultivations in order to investigate the use of multi-wavelength fluorescence for monitoring course of events during filamentous fungi cultivations. The A. oryzae strain applied expressed a fungal lipase from Thermomyces lanuginosus. Spectra of multi-wavelength fluorescence were collected every 5 min with the BioView system (DELTA, Denmark) and both explorative and predictive models, correlating the fluorescence data with cell mass and lipase activity, were built. During the cultivations, A. oryzae displayed dispersed hyphal growth and under these conditions no fouling of the multi-wavelength fluorescence sensor was observed. The scores of a parallel factor analysis (PARAFAC) model, based on the fluorescence spectra, gave clear evidence of, for example, the on-set of the feeding phase. The predictive models, estimating the cell mass, showed correlations between 0.73 and 0.97 with root mean square error of cross validation (RMSECV) values between 1.48 and 0.77 g . kg(-1). A model estimating the lipase activity was also constructed for the fed-batch cultivations with a correlation of 0.93. The results presented here clearly show that multi-wavelength fluorescence is a useful tool for monitoring fed-batch cultivations of filamentous fungi.

Near infrared spectroscopy for bioprocess monitoring and control: current status and future trends

The development of Near Infrared Spectroscopy has paralleled that of the PC, and the application of NIR in many industries has undergone explosive growth in recent years. This has been particularly apparent in the area of microbial and cell culture system monitoring and control. Potentially, NIR offers the prospect of real-time control of the physiology of cultured cells in fermenters, leading to marked improvements in authenticity, purity and production efficiency. Despite this, NIR is not yet as widely applied within the bioprocessing industry as its potential might suggest. This review critically evaluates the development of this rapidly moving area as it pertains to microbial and cell culture system control and highlights the critical stages in the development of the technology. It indicates the work that must still be carried out if the full potential of NIR is to be exploited in making proteins, hormones and antibiotics by the fermentation route. The review comes at a particularly timely moment when NIR stands on the threshold of widespread acceptance in bioprocessing. This is the ideal moment to assess what the technology can offer the microbiologist, and where it may develop in the future.

Near-infrared spectroscopic monitoring of biomass, glucose, ethanol and protein content in a high cell density baker's yeast fed-batch bioprocess

The use of at-line NIRS to monitor a high cell density fed-batch baker's yeast bioprocess was investigated. Quantification of the key analytes (biomass, ethanol and glucose) and the product quality indicator (percentage protein content) was studied. Biomass was quantitatively modelled using whole matrix samples (as was percentage protein content). The dominance of the whole matrix spectrum by biomass, and its associated light scattering effects, were overcome by use of filtrate samples and adapted (semi-synthetic) filtrate samples, which allowed successful ethanol and glucose modelling, respectively. Calibrations were rigorously challenged via external validation with large sample sets relative to the calibration sample size, ensuring model robustness and potential practical utility. The standard errors of calibration for biomass, glucose, ethanol and total intracellular protein were (g/l) 1.79, 0.19, 0.79 and 0.91, respectively, comparable to those of the primary assays. The calibration strategies necessary to generate quantitative models for this range of analytes in such a complex high cell density bioprocess fluid are discussed.

Monitoring complex media fermentations with near-infrared spectroscopy: Comparison of different variable selection methods

Near-infrared spectroscopy (NIRS) is known to be a suitable technique for rapid fermentation monitoring. Industrial fermentation media are complex, both chemically (ill-defined composition) and physically (multiphase sample matrix), which poses an additional challenge to the development of robust NIRS calibration models. We investigated the use of NIRS for at-line monitoring of the concentration of clavulanic acid during an industrial fermentation. An industrial strain of Streptomyces clavuligerus was cultivated at 200-L scale for the production of clavulanic acid. Partial least squares (PLS) regression was used to develop calibration models between spectral and analytical data. In this work, two different variable selection methods, genetic algorithms (GA) and PLS-bootstrap, were studied and compared with models built using all the spectral variables. Calibration models for clavulanic acid concentration performed well both on internal and external validation. The two variable selection methods improved the predictive ability of the models up to 20%, relative to the calibration model built using the whole spectra.

Spectral analysis and fingerprinting for biomedia characterisation

Classical culture media, as well as domestic and/or industrial wastewater treated by biological processes, have a complex composition. The on-line and/or in situ determination of some substances is possible, but expensive, as sample collection and pre-treatment are often necessary with strict rules of sterility. More global methods can be used to detect rapidly "accidents" such as the appearance of an undesirable by-product in a fermentation broth or of a toxic substance in wastewater. These methods combine a "hard" part, for sensing, and a "soft" part, for data treatment. Among potential "hard" candidates, spectroscopy can be the basis for non-invasive and non-destructive measuring systems. Some of them have been already tested in situ: ultra-violet-visible, infra-red (mid or near), fluorescence (mono-dimensional, two-dimensional or synchronous), dielectric, while others, more sophisticated, such as mass spectrometry, coupled or not to pyrolysis, nuclear magnetic resonance and Raman spectroscopy, have been proposed. All these methods provide spectra, i.e. large sets of data, from which meaningful information should be rapidly extracted, either for analysis or fingerprinting. The recourse to data-mining techniques (the "soft" part) such as principal components analysis, projection on latent structures or artificial neural networks, is a necessary step for that task. A review of techniques, mostly based on spectroscopy, with examples taken in the bioengineering field in general is proposed.

On-line multisensor monitoring of yogurt and filmjölk fermentations on production scale

Near-infrared (NIR) spectrometry and electronic nose (EN) data were used for on-line monitoring of yogurt and filmjölk (a Swedish yogurt-like sour milk) fermentations under industrial conditions. The NIR and EN signals were selected by evaluation of principal component analysis loading vectors and further analyzed by studying the variability of the selected principal components. First principal components for the NIR and the EN signals were used for on-line generation of a process trajectory plot visualizing the actual state of fermentation. The NIR signals were also used to set up empirical partial least-squares (PLS) models for prediction of the cultures' pH and titratable acidity (expressed as Thorner degrees, degrees T). By using five or six PLS factors the models yielded acceptable predictions that could be further improved by increasing the number of reliable and precise calibration data. The presented results demonstrate that the fusion of the NIR and EN signals has a potential for rapid on-line monitoring and assessment of process quality of yogurt fermentation.

In-situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation

The use of in-situ near infrared spectroscopy (NIRS) as a tool for monitoring four key analytes in a CHO-K1 animal cell culture was investigated. Previous work using on-line NIRS to monitor bioprocesses has involved its application ex-situ where the analyzer is physically outside the fermentor, or to microbial bioprocesses. This novel application of NIRS to monitor analytes within an animal cell culture using a steam sterilizable in-situ fiber optic probe is very important for furthering the use of NIRS within the bioprocessing industry. The method of calibration used to develop the models involved the use of large data sets so that all likely variation in stoichiometry was incorporated within the models. Successful models for glucose, lactate, glutamine, and ammonia were built with Standard Error of Predictions (SEP's) of 0.072 (g/L), 0.0144 (g/L), 0.308 (mM), and 0.036 (mM), respectively of the total concentration range.

Optical sensor systems for bioprocess monitoring

Bioreactors are closed systems in which microorganisms can be cultivated under defined, controllable conditions that can be optimized with regard to viability, reproducibility, and product-oriented productivity. To drive the biochemical reaction network of the biological system through the desired reaction optimally, the complex interactions of the overall system must be understood and controlled. Optical sensors which encompass all analytical methods based on interactions of light with matter are efficient tools to obtain this information. Optical sensors generally offer the advantages of noninvasive, nondestructive, continuous, and simultaneous multianalyte monitoring. However, at this time, no general optical detection system has been developed. Since modern bioprocesses are extremely complex and differ from process to process (e.g., fungal antibiotic production versus mammalian cell cultivation), appropriate analytical systems must be set up from different basic modules, designed to meet the special demands of each particular process. In this minireview, some new applications in bioprocess monitoring of the following optical sensing principles will be discussed: UV spectroscopy, IR spectroscopy, Raman spectroscopy, fluorescence spectroscopy, pulsed terahertz spectroscopy (PTS), optical biosensors, in situ microscope, surface plasmon resonance (SPR), and reflectometric interference spectroscopy (RIF).

Use of at-line and in-situ near-infrared spectroscopy to monitor biomass in an industrial fed-batch Escherichia coli process

One of the key goals in bioprocess monitoring is to achieve real-time knowledge of conditions within the bioreactor, i.e., in-situ. Near-infrared spectroscopy (NIRS), with its ability to carry out multi-analyte quantification rapidly with little sample presentation, is potentially applicable in this role. In the present study, the application of NIRS to a complex, fed-batch industrial E. coli (RV308/PHKY531) process was investigated. This process undergoes a series of temperature changes and is vigorously agitated and aerated. These conditions can pose added challenges to in-situ NIRS. Using the measurement of a key analyte (biomass) as an illustration, the details of the relationship between the at-line and in-situ use of NIRS are considered from the viewpoint of both theory and practical application. This study shows that NIRS can be used both at-line and in-situ in order to achieve good predictive models for biomass. There are particular challenges imposed by in-situ operation (loss of wavelength regions and noise) which meant the need for signal optimisation studies. This showed that whilst the at-line modelling process may provide some useful information for the in-situ process, there were distinct differences. This study shows that the in-situ use of NIRS in a highly challenging matrix (similar to those encountered in current industrial practice) is possible, and thus extends previous works in the area.

Bioprocess monitoring

Electrochemical sensors for pH and dissolved oxygen remain the most commonly used in bioprocess monitoring, but continued research has resulted in improved optical sensors. Optical sensors for dissolved oxygen and dissolved carbon dioxide are now commercially available. Advances in optics and electronics are further driving down the costs of these sensors. In the near future, bioprocess optimization will change paradigms as massively parallel, fully instrumented bioreactors become available and high-throughput bioprocessing becomes a reality.

Real-time in situ monitoring of freely suspended and immobilized cell cultures based on mid-infrared spectroscopic measurements

Glucose and lactate profiles in Chinese hamster ovary cell cultures were accurately monitored in real time and in situ during three bioreactor batch cultures lasting 11,15, and 15 days performed within a 60-day period. Monitoring was accomplished using in situ-collected mid-infrared spectra analyzed with a priori one-time established partial least-squares regression models. The robustness of the technique was demonstrated by application of these models without modification after 2.3 years. Neither recalibration nor instrument maintenance was required during the 2.3-year period, except for the daily filling of liquid nitrogen for detector cooling during operation. The lactate calibration model yielded accurate absolute concentration estimations during each of the batch cultures with standard errors of estimate from 1 to 3 mM. The a priori-established glucose calibration model yielded concentration estimations with an off-set, which was constant throughout a culture. Adjustment of the off-set before inoculation resulted in accurate concentration estimations with Standard errors of estimate of approximately 1 mM for each of the bioreactor cultures. Sensitivity in detecting differences of 0.5 mM and selectivity against variation of one metabolite while the other was kept constant was demonstrated during standard additions of either glucose or lactate. The sensor system proved to be reliable, simple, accurate, sterile, and capable of long-term automatic operation and is considered to be mature enough to be routinely applied for in situ (on-line) cell culture monitoring.

At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy

The use of near infra-red spectroscopy (NIRS) to monitor a submerged filamentous bacterial bioprocess was investigated. An industrial strain of the filamentous bacterium Streptomyces fradiae was cultured in a 12 litre stirred tank reactor (STR) using a complex medium. This mycelial 4 phase (oil, water, gas and solid) system produced highly complex and variable matrices, therefore monitoring such a complex fluid with NIRS represented a considerable challenge. Nevertheless, successful models for four key analytes (methyl oleate, glucose, glutamate and ammonium) were built at-line (rapid off-line) using NIRS. In the present study, the methods used to formulate, select and validate the models for the key analytes are discussed, with particular emphasis on how the model performance can be critically evaluated. Since previous reports on NIRS in monitoring bioprocesses have either involved simpler matrices, or, in filamentous systems, have not discussed how NIRS models can be critically assessed, the emphasis in the present study on providing an insight into the modelling process in such a complex matrix, may be particularly important to the applicability of NIRS to such industrial bioprocesses.