@article {46639,
	title = {Engineering staphylococcal protein A for high-throughput affinity purification of monoclonal antibodies},
	journal = {Biotechnology Advances},
	volume = {44},
	year = {2020},
	month = {NOV },
	pages = {107632},
	type = {Review},
	abstract = {<p>Protein A chromatography is one of the most widely used purification steps in the manufacturing of the various classes of recombinant and non-recombinant antibodies. Due to the higher cost, lower binding capacity, and limited life cycle of Protein A ligand, this affinity-based purification step is often one of the most significant contributors to the cost of manufacturing of monoclonal antibody (mAb) products. In the last decade, there has been significant progress in improving the Protein A chromatography throughput by designing new engineered Staphylococcal Protein A (SPA) variants with higher dynamic binding capacity, considerable alkaline tolerance, and mild acidic elution pH. This review aims at summarizing the various protein engineering approaches used for improving the throughput of the Protein A-based affinity purification of various immunoglobulins. With biopharmaceutical producers operating under ever-increasing pressure towards reducing the cost of manufacturing, these advances in engineered protein A variants will help in processing larger cell culture volumes with high throughput and thereby significantly lower the cost of raw materials.</p>
},
	keywords = {Alkaline tolerance, Dynamic binding capacity, Elution pH, Monoclonal antibodies, Protein A},
	issn = {0734-9750},
	doi = {10.1016/j.biotechadv.2020.107632},
	author = {Amritkar, Vinod and Adat, Satish and Tejwani, Vijay and Rathore, Anurag and Bhambure, Rahul}
}
@article {48394,
	title = {Mechanistic modeling of continuous capture step purification of biosimilar monoclonal antibody therapeutic},
	journal = {Journal of Chemical Technology and Biotechnology},
	volume = {97},
	year = {2022},
	month = {SEP},
	pages = {2404-2419},
	type = {Article},
	abstract = {<p>
	{BACKGROUND Continuous multicolumn Protein A chromatography offers various advantages for capture stage purification of monoclonal antibody therapeutics, like higher productivity and resin capacity utilization, lower buffer consumption, small footprint, etc. Due to the complexity of the continuous process, experimental optimization is time-consuming and cost-intensive. This investigation proposes a hybrid process development approach integrating experimental and mechanistic modeling for time- and cost-effective development and optimization of continuous Protein A affinity chromatography. RESULTS Productivity and capacity utilization of the continuous CaptureSMB process under varying operating conditions were predicted using the Chromatography Analysis and Design Toolkit (CADET) framework and validated with experimental results. Effects of critical process parameters like feed concentration (c(0)), loading breakthrough (s) and residence time (RT) on productivity and capacity utilization were evaluated. Model predictions were validated using the experimental results proving the reliability and feasibility of the modeling approach. At 15.00 +/- 0.20 mg mL(-1) feed model mAb concentration, the model-based approach predicted the best performance giving 27.56 g L-1 h(-1) productivity (RT = 2 min</p>
},
	keywords = {CaptureSMB, continuous chromatography, Mathematical modeling, Protein A, simulation},
	issn = {0268-2575},
	doi = {10.1002/jctb.6922},
	author = {Deulgaonkar, Prashant and Bhambure, Rahul and Prasad, Bhaskarjyoti and Mishra, Ashok and Tiwari, Sanjay and Mody, Rustom}
}
