Publications
7 results found
Hedberg S, Rapley J, Haigh JM, et al., 2018, Cross-interaction chromatography as a rapid screening technique to identify the stability of new antibody therapeutics, European Journal of Pharmaceutics and Biopharmaceutics, Vol: 133, Pages: 131-137, ISSN: 0939-6411
Protein aggregation can be a major problem in the manufacturing of new biopharmaceuticals and there is a desirability for development of techniques that can predict the behaviour of new biopharmaceuticals early on in the development process. A technique that can be used to predict aggregation is self-interaction chromatography that is used to determine the second virial coefficient, B22, but one of the limitations includes the need to immobilise every protein of interest. In this study a related technique, cross interaction chromatography (CIC), is evaluated which overcomes this limitation. Three antibodies were studied across a range of NaCl concentrations with each antibody being studied as both a mobile phase and as the stationary phase - in total 6 different stationary-mobile phase combinations. The B22 values obtained for all three proteins correlated strongly with the B23 results obtained for the same protein in the mobile phase, and were significantly independent of the protein immobilised on the stationary phase. This observation allows the use of pre-prepared columns with known immobilised model proteins such as a polyclonal antibody or mAb, with other unknown monoclonal antibodies in the mobile phase. Preliminary experiments using a series of known immobilised mAbs columns with an unknown mAb in the mobile phase resulted in at least a 50 fold reduction in the amount of unknown protein needed and a rapid semi-quantitative assessment of aggregation propensity. CIC can speed up the screening process with minimum preparation time and therefore more rapidly be able to identify the aggregation stability of new antibody formulations.
Williams DR, 2018, Mapping the mAb Aggregation Propensity Using Self-InteractionChromatography as a Screening Tool, Analytical Chemistry, ISSN: 0003-2700
Hedberg SHM, Heng JYY, Williams DR, et al., 2015, Micro scale self-interaction chromatography of proteins: a mAb case-study, Journal of Chromatography A, Vol: 1434, Pages: 57-63, ISSN: 0412-3425
Self-interaction chromatography is known to be a fast, automated and promising experimental technique for determination of B22, but with the primary disadvantage of needing a significant amount of protein (>50 mg). This requirement compromises its usage as a technique for the early screening of new biotherapeutic candidates. A new scaled down SIC method has been evaluated here using a number of micro LC columns of different diameters and lengths, using typically 10 times less stationary phase than traditional SIC. Scale-down was successfully accomplished using these micro-columns, where the SIC results for a range of differing columns sizes were in agreement, as reflected by k′, B22 and column volumes data. The results reported here demonstrate that a scaled down version of SIC can be easily implemented using conventional liquid chromatography system where the final amount of mAbs used was 10 times less than required by conventional SIC methodologies.
Hedberg SHM, Heng JYY, Williams DR, et al., 2015, Self-interaction chromatography of mAbs: accurate measurement of dead volumes, Pharmaceutical Research, Vol: 32, Pages: 3975-3985, ISSN: 1573-904X
Purpose: Measurement of the second virial coefficient B22 for proteins using self-interaction chromatography (SIC) is becoming an increasingly important technique for studying their solution behaviour. In common with all physicochemical chromatographic methods, measuring the dead volume of the SIC packed column is crucial for accurate retention data; this paper examines best practise for dead volume determination.Method: SIC type experiments using catalase, BSA, lysozyme and a mAb as model systems are reported, as well as a number of dead column measurements. Results: It was observed that lysozyme and mAb interacted specifically with Toyopearl AF-Formyl dead columns depending upon pH and [NaCl], invalidating their dead volume usage. Toyopearl AF-Amino packed dead columns showed no such problems and acted as suitable dead columns without any solution condition dependency. Dead volume determinations using dextran MW standards with protein immobilised SIC columns provided dead volume estimates close to those obtained using Toyopearl AF-Amino dead columns. Conclusion: It is concluded that specific interactions between proteins, including mAbs, and select SIC support phases can compromise the use of some standard approaches for estimating the dead volume of SIC columns. Two other methods were shown to provide good estimates for the dead volume.
Hedberg S, Heng JYY, Williams DR, et al., 2015, Chromatographic tools to predict the stability of mAbs for faster identification of therapeutic candidates, Pages: 1150-1151
Protein-protein molecular interactions are known to be involved in protein solution aggregation behaviour and are a common issue for the manufacturing of therapeutic proteins such as mAbs. Much effort has been employed to gain a better understanding of aggregation, however the mechanisms leading to protein aggregation are still not fully understood. The osmotic second virial coefficient (B22) is a fundamental physiochemical property that describes protein-protein interactions solution, which can be a useful tool to predict aggregation propensity of proteins. One way of predicting aggregation propensity is self-interaction chromatography (SIC), which recently have shown to be a promising tool for better understanding of phase behaviour of proteins. Another technique, cross-interaction chromatography (CIC), has shown to be an even more high-throughput technique than its predecessor with possibly the same capabilities. This work consists of two experimental studies with therapeutic mAbs to improve SIC and CIC as a tool to predict protein aggregation. The first part includes a 10 times scale-down study of therapeutic mAbs from laboratory scale macro-columns to micro-scale columns, which will enable the determination of B22 for the individual protein as well as the cross-virial coefficient, B23, between two proteins. Micro SIC and CIC uses only a few milligrams of mAb in order to obtain a complete formulation study. The results from the first part of the study proved to give good comparable results between the micro and macro scales enabling the use of micro SIC for B22 determinations. The second part of this work presents an extensive formulation study of mAbs, varying pH and salt, as well as the presence of different stabilisers as well as different external factors known to induce aggregation. The B22 and B23 values determined from the formulation study are then correlated with aggregation data obtained from size-exclusion chromatography. It was shown that over all te
Hedberg S, Quigley A, Heng JYY, et al., 2014, Self-interaction chromatography (SIC) of mabs: New methods for estimating the dead volume in SIC and using sic to predict mab stability, Pages: 897-907
Protein-protein molecular interactions are known to be involved in protein solution aggregation behaviour; however the mechanisms leading to protein aggregation are still not fully understood. The osmotic second virial coefficient (B22) is a fundamental physiochemical property that describes proteinprotein interactions in solution, which can be a useful tool to predict aggregation propensity of proteins. This work includes two experimental SIC studies on both model proteins and therapeutic mAbs of different sizes. The first study is an evaluation of two different experimental techniques used to determine SIC dead volumes and the second study uses SIC results for mAb to predict stability. Accurate dead retention volumes are essential for the accurate determinations of B22. The traditional method of estimating dead volume for SIC includes the use of a dead column (without protein immobilised) where the retention volume for proteins can be established. For this technique the dead volume was established for the proteins over a wide range of solution conditions (pH and salt concentrations), and then compared with a new method, where a number of non-interacting dextrans of different molecular weights (MW) (including the MW's of the protein) were employed to find the dead retention volume. The results for the traditional technique with a dead column changed depending on the protein used; only certain model proteins kept a constant dead retention volume when the pH was changing under a constant high salt concentration to minimise protein-surface interactions. Several proteins, including the mAb, exhibited an increased dead retention volume especially when exposed to lower pH. From this it can be concluded that there is no absolute dead volume that can be determined by this technique which are independent of solution conditions. The new technique involving dextrans gives a better overall result for the dead volume for proteins such as mAbs. The second study shows that the SI
Hou Y, Hedberg S, Schneider IC, 2012, Differences in adhesion and protrusion properties correlate with differences in migration speed under EGF stimulation, BMC Biophysics, Vol: 5
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Cell migration plays an essential role in many biological processes, such as cancer metastasis, wound healing and immune response. Cell migration is mediated through protrusion and focal adhesion (FA) assembly, maturation and disassembly. Epidermal growth factor (EGF) is known to enhance migration rate in many cell types; however it is not known how FA maturation, FA dynamics and protrusion dynamics are regulated during EGF-induced migration. Here we use total internal reflection fluorescence (TIRF) microscopy and image analysis to quantify FA properties and protrusion dynamics under different doses of EGF stimulation.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>EGF was found to broaden the distribution of cell migration rates, generating more fast and slow cells. Furthermore, groups based on EGF stimulation condition or cell migration speed were marked by characteristic signatures. When data was binned based on EGF stimulation conditions, FA intensity and FA number per cell showed the largest difference among stimulation groups. FA intensity decreased with increasing EGF concentration and FA number per cell was highest under intermediate stimulation conditions. No difference in protrusion behavior was observed. However, when data was binned based on cell migration speed, FA intensity and not FA number per cell showed the largest difference among groups. FA intensity was lower for fast migrating cells. Additionally, waves of protrusion tended to correlate with fast migrating cells.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Only a portion of the FA properties and protrusion dynamics that correlate with
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