Use of Process Data To Assess Chromatographic Performance in Production‐Scale Protein Purification Columns

Larson, Tina M.; Davis, Jeff M; Lam, Harry; Cacia, Jerry

doi:10.1021/bp025639g

Cited by 44 publications

(33 citation statements)

References 8 publications

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“…For example, Larson et al used conductivity transitions to characterize column efficiencies and monitor breaches in fullscale column operations over repeated purification cycles. 16 In the current study, conductivity transitions were used to quantify spreading within the whole chromatography system, including both the Protein A column used for monoclonal antibody capture as well as the extra column volume.…”

Section: Laboratory-scale Studiesmentioning

confidence: 99%

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Ultra scale‐down approach to correct dispersive and retentive effects in small‐scale columns when predicting larger scale elution profiles

Hutchinson

Chhatre

Baldascini

et al. 2009

Biotechnology Progress

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Ultra scale-down approaches represent valuable methods for chromatography development work in the biopharmaceutical sector, but for them to be of value, scale-down mimics must predict large-scale process performance accurately. For example, one application of a scale-down model involves using it to predict large-scale elution profiles correctly with respect to the size of a product peak and its position in a chromatogram relative to contaminants. Predicting large-scale profiles from data generated by small laboratory columns is complicated, however, by differences in dispersion and retention volumes between the two scales of operation. Correcting for these effects would improve the accuracy of the scale-down models when predicting outputs such as eluate volumes at larger scale and thus enable the efficient design and operation of subsequent steps. This paper describes a novel ultra scale-down approach which uses empirical correlations derived from conductivity changes during operation of laboratory and pilot columns to correct chromatographic profiles for the differences in dispersion and retention. The methodology was tested by using 1 mL column data to predict elution profiles of a chimeric monoclonal antibody obtained from Protein A chromatography columns at 3 mL laboratory- and 18.3 L pilot-scale. The predictions were then verified experimentally. Results showed that the empirical corrections enabled accurate estimations of the characteristics of larger-scale elution profiles. These data then provide the justification to adjust small-scale conditions to achieve an eluate volume and product concentration which is consistent with that obtained at large-scale and which can then be used for subsequent ultra scale-down operations.

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Section: Laboratory-scale Studiesmentioning

confidence: 99%

“…Moment analysis of the transitions then allowed values for dispersion to be obtained from the whole response curves without making any assumptions about their distribution i.e. not assuming a Gaussian distribution 16 :…”

Section: Conductivity Transition Calculationmentioning

confidence: 99%

Ultra scale‐down approach to correct dispersive and retentive effects in small‐scale columns when predicting larger scale elution profiles

Hutchinson

Chhatre

Baldascini

et al. 2009

Biotechnology Progress

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show abstract

“…Applying PAT toward the various aspects of bioprocessing has been of great interest to the biotech community (Gnoth et al, 2007;Junker and Wang, 2006). It has been pointed out that bioprocessing unit operations are generally more complex to control, which is further exacerbated by the increased variability and relatively limited understanding of their raw materials and feed materials (Larson et al, 2003;Larson and Lam, 2004).…”

Section: Introductionmentioning

confidence: 99%

Large scale demonstration of a process analytical technology application in bioprocessing: Use of on‐line high performance liquid chromatography for making real time pooling decisions for process chromatography

Rathore

Parr

Dermawan

et al. 2009

Biotechnology Progress

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Process Analytical Technology (PAT) has been gaining a lot of momentum in the biopharmaceutical community because of the potential for continuous real time quality assurance resulting in improved operational control and compliance. In previous publications, we have demonstrated feasibility of applications involving use of high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) for real-time pooling of process chromatography column. In this article we follow a similar approach to perform lab studies and create a model for a chromatography step of a different modality (hydrophobic interaction chromatography). It is seen that the predictions of the model compare well to actual experimental data, demonstrating the usefulness of the approach across the different modes of chromatography. Also, use of online HPLC when the step is scaled up to pilot scale (a 2294 fold scale-up from a 3.4 mL column in the lab to a 7.8 L column in the pilot plant) and eventually to manufacturing scale (a 45930 fold scale-up from a 3.4 mL column in the lab to a 158 L column in the manufacturing plant) is examined. Overall, the results confirm that for the application under consideration, online-HPLC offers a feasible approach for analysis that can facilitate real-time decisions for column pooling based on product quality attributes. The observations demonstrate that the proposed analytical scheme allows us to meet two of the key goals that have been outlined for PAT, i.e., "variability is managed by the process" and "product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental, and other conditions". The application presented here can be extended to other modes of process chromatography and/or HPLC analysis.

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“…Several chromatographic steps are usually used to achieve the high levels of final product purity required [2]. During manufacturing, time-dependent and process-specific degradation in the performance of chromatography columns must be monitored and controlled to satisfy stringent regulatory requirements on product consistency between batches [3]. A number of components in process feed streams to chromatography columns may exert deleterious effects on the matrix bed characteristics, particularly under repeated or prolonged exposure.…”

Section: Introductionmentioning

confidence: 99%

Effect of fouling on the capacity and breakthrough characteristics of a packed bed ion exchange chromatography column

Siu

Baldascini

Hearle

et al. 2006

Bioprocess Biosyst Eng

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This study examined the impact of fouling with yeast homogenate on capacity and breakthrough performance of an ion exchange packed bed column. Column performance was assessed by analysis of breakthrough curves obtained with BSA as a test protein. The overall impact of fouling on breakthrough performance depended heavily on the level of clarification of the feed stream. Challenging the column with particulate-free homogenate caused no change in column performance. Loading successive small volumes of poorly clarified homogenate, interspersed with frequent column salt washes, did not alter significantly the column capacity. By contrast, when the column was challenged with an equivalent cumulative volume of poorly clarified homogenate, dynamic binding capacity decreased significantly and changes in breakthrough curves suggested increased intraparticle and external mass transfer limitations. These changes were ascribed to deposition of solid particulates in void spaces in the bed and colloidal contaminants in the bead pores.

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Use of Process Data To Assess Chromatographic Performance in Production‐Scale Protein Purification Columns

Cited by 44 publications

References 8 publications

Ultra scale‐down approach to correct dispersive and retentive effects in small‐scale columns when predicting larger scale elution profiles

Ultra scale‐down approach to correct dispersive and retentive effects in small‐scale columns when predicting larger scale elution profiles

Large scale demonstration of a process analytical technology application in bioprocessing: Use of on‐line high performance liquid chromatography for making real time pooling decisions for process chromatography

Effect of fouling on the capacity and breakthrough characteristics of a packed bed ion exchange chromatography column

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