Real-time control of purified product collection during chromatography of recombinant human insulin-like growth factor-I using an on-line assay

Advanced control strategies for bioprocess chromatography: Challenges and opportunities for intensified processes and next generation products

Recent advances in process analytical technologies and modelling techniques present opportunities to improve industrial chromatography control strategies to enhance process robustness, increase productivity and move towards real-time release testing. This paper provides a critical overview of batch and continuous industrial chromatography control systems for therapeutic protein purification. Firstly, the limitations of conventional industrial fractionation control strategies using in-line UV spectroscopy and on-line HPLC are outlined. Following this, an evaluation of monitoring and control techniques showing promise within research, process development and manufacturing is provided. These novel control strategies combine rapid in-line data capture (e.g. NIR, MALS and variable pathlength UV) with enhanced process understanding obtained from mechanistic and empirical modelling techniques. Finally, a summary of the future states of industrial chromatography control systems is proposed, including strategies to control buffer formulation, product fractionation, column switching and column fouling. The implementation of these control systems improves process capabilities to fulfil product quality criteria as processes are scaled, transferred and operated, thus fast tracking the delivery of new medicines to market.

Multi-attribute PAT for UF/DF of Proteins-Monitoring Concentration, particle sizes, and Buffer Exchange

Ultrafiltration/diafiltration (UF/DF) plays an important role in the manufacturing of biopharmaceuticals. Monitoring critical process parameters and quality attributes by process analytical technology (PAT) during those steps can facilitate process development and assure consistent quality in production processes. In this study, a lab-scale cross-flow filtration (CFF) device was equipped with a variable pathlength (VP) ultraviolet and visible (UV/Vis) spectrometer, a light scattering photometer, and a liquid density sensor (microLDS). Based on the measured signals, the protein concentration, buffer exchange, apparent molecular weight, and hydrodynamic radius were monitored. The setup was tested in three case studies. First, lysozyme was used in an UF/DF run to show the comparability of on-line and off-line measurements. The corresponding correlation coefficients exceeded 0.97. Next, urea-induced changes in protein size of glucose oxidase (GOx) were monitored during two DF steps. Here, correlation coefficients were ≥ 0.92 for static light scattering (SLS) and dynamic light scattering (DLS). The correlation coefficient for the protein concentration was 0.82, possibly due to time-dependent protein precipitation. Finally, a case study was conducted with a monoclonal antibody (mAb) to show the full potential of this setup. Again, off-line and on-line measurements were in good agreement with all correlation coefficients exceeding 0.92. The protein concentration could be monitored in-line in a large range from 3 to 120 g L^- 1. A buffer-dependent increase in apparent molecular weight of the mAb was observed during DF, providing interesting supplemental information for process development and stability assessment. In summary, the developed setup provides a powerful testing system for evaluating different UF/DF processes and may be a good starting point to develop process control strategies. Graphical Abstract Piping and instrumentation diagram of the experimental setup and data generated by the different sensors. A VP UV/Vis spectrometer (FlowVPE, yellow) measures the protein concentration. From the data of the light scattering photometer (Zetasizer, green) in the on-line measurement loop, the apparant molecular weight and z-average are calculated. The density sensor (microLDS) measures density and viscosity of the fluid in the on-line loop.

Trends in Process Analytical Technology: Present State in Bioprocessing

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

Factorization of preparative protein chromatograms with hard-constraint multivariate curve resolution and second-derivative pretreatment

Current biopharmaceutical production heavily relies on chromatography for protein purification. Recently, research has intensified towards finding suitable solutions to monitoring the chromatographic steps by multivariate spectroscopic sensors. Here, hard-constraint multivariate curve resolution (MCR) was investigated as a calibration-free method for factorizing bilinear preparative protein chromatograms into concentrations and spectra. Protein elutions were assumed to follow exponentially modified Gaussian (EMG) curves. In three case studies, MCR was applied to chromatograms of second-derivative ultraviolet and visible (UV-vis) spectra. The three case studies consisted of the separation of a ternary mixture (ribonuclease A, cytochrome c, and lysozyme), multiple binary chromatography runs of cytochrome c and lysozyme, and the separation of an antibody-drug conjugate (ADC) from unconjugated immunoglobulin G (IgG). In all case studies, good estimates of the elution curves were obtained. R² values compared to off-line analytics exceeded 0.90. The estimated spectra allowed for protein identification based on a protein spectral library. In summary, MCR was shown to be well able to factorize protein chromatograms without prior calibration. The method may thus substantially simplify analysis of multivariate protein chromatograms with multiple co-eluting species. It may be especially useful in process development.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given.

Application of spectral deconvolution and inverse mechanistic modelling as a tool for root cause investigation in protein chromatography

In chromatographic protein purification, process variations, aging of columns, or processing errors can lead to deviations of the expected elution behavior of product and contaminants and can result in a decreased pool purity or yield. A different elution behavior of all or several involved species leads to a deviating chromatogram. The causes for deviations are however hard to identify by visual inspection and complicate the correction of a problem in the next cycle or batch. To overcome this issue, a tool for root cause investigation in protein chromatography was developed. The tool combines a spectral deconvolution with inverse mechanistic modelling. Mid-UV spectral data and Partial Least Squares Regression were first applied to deconvolute peaks to obtain the individual elution profiles of co-eluting proteins. The individual elution profiles were subsequently used to identify errors in process parameters by curve fitting to a mechanistic chromatography model. The functionality of the tool for root cause investigation was successfully demonstrated in a model protein study with lysozyme, cytochrome c, and ribonuclease A. Deviating chromatograms were generated by deliberately caused errors in the process parameters flow rate and sodium-ion concentration in loading and elution buffer according to a design of experiments. The actual values of the three process parameters and, thus, the causes of the deviations were estimated with errors of less than 4.4%. Consequently, the established tool for root cause investigation is a valuable approach to rapidly identify process variations, aging of columns, or processing errors. This might help to minimize batch rejections or contribute to an increased productivity.

A tool for selective inline quantification of co-eluting proteins in chromatography using spectral analysis and partial least squares regression

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities.

Practical reversed-phase high-performance liquid chromatography method for laboratory-scale purification of recombinant human thyrotropin

A small, semi-preparative C(4) RP-HPLC column was used to set up the conclusive laboratory-scale purification of Chinese hamster ovary-derived human thyrotropin (hTSH), after a preliminary concentration-purification of an extremely dilute and poorly ( approximately 0.6 microg hTSH/mL; mass fraction=0.35%) conditioned medium on a cation exchanger. Several fractions of this eluate were repeatedly injected on the semi-preparative column, obtaining, in a single run (<1h chromatographic time), a concentrated pool ( approximately 1.2 mg/mL) of highly purified hTSH that could be further concentrated to >3 mg/mL and then efficiently lyophilized. The overall recovery in the rapid RP-HPLC purification step, including concentration and lyophilization, was of the order of 80%. The final product, when tested via a precise, single-dose in vivo bioassay, confirmed that it did not suffer any loss of bioactivity. This same methodology can be easily adapted to the small-scale purification of other recombinant products, even when obtained from genetically modified organisms at extremely low concentrations and mass fractions.

Real-time control of antibody loading during protein A affinity chromatography using an on-line assay

We show that an on-line chromatographic assay can reliably control antibody loading in real-time during protein A affinity chromatography purification of a recombinant antibody from clarified Chinese hamster ovary cell culture fluid. The on-line assay directly sampled preparative column effluent and provided real-time measurement of antibody breakthrough during loading. The on-line assay used protein A immobilized on perfusion chromatography media, equilibrated with phosphate-buffered saline at pH 7.2 and eluted with phosphate-buffered saline at pH 2.2. The assay reliably ended loading at 1% breakthrough with minimal yield loss. Reproducible yield and purity were obtained over 23 consecutive cycles. Yield remained constant while breakthrough capacity and the antibody concentration in the load changed.