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10.1016/j.jchromb.2014.09.003 http://scihub22266oqcxt.onion/10.1016/j.jchromb.2014.09.003 C4254358!4254358 !25270058     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\25270058 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Chromatogr+B+Analyt+Technol+Biomed+Life+Sci 2014 ; 971 (ä): 99-106 Nephropedia Template TP {{tp|p=25270058 |t=2014. Protein solubilization: a novel approach |pdf=|usr=}}{{25270058 }} gab.com Text Protein solubilization: a novel approach JO: J Chromatogr B Analyt Technol Biomed Life Sci http://www.kidney.de/pget.php?&tw=1&pmid=25270058 #FOAvip Formulation development presents significant challenges with respect to protein therapeutics. One component of these challenges is to attain high protein solubility (>50mg/ml for immunoglobulins) with minimal aggregation. Protein-protein interactions contribute to aggregation and the integral sum of these interactions can be quantified by a thermodynamic parameter known as the osmotic second virial coefficient (B-value). The method presented here utilizes high-throughput measurement of B-values to identify the influence of additives on protein-protein interactions. The experiment design uses three tiers of screens to arrive at final solution conditions that improve protein solubility. The first screen identifies individual additives that reduce protein interactions. A second set of B-values are then measured for different combinations of these additives via an incomplete factorial screen. Results from the incomplete factorial screen are used to train an artificial neural network (ANN). The "trained" ANN enables predictions of B-values for more than 4000 formulations that include additive combinations not previously experimentally measured. Validation steps are incorporated throughout the screening process to ensure that (1) the protein's thermal and aggregation stability characteristics are not reduced and (2) the artificial neural network predictive model is accurate. The ability of this approach to reduce aggregation and increase solubility is demonstrated using an IgG protein supplied by Minerva Biotechnologies, Inc. Twit Text FOAVip Protein solubilization: a novel approach ????J Chromatogr B Analyt Technol Biomed Life Sci http://www.kidney.de/pget.php?&tw=1&pmid=25270058 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25270058 #FOAvip English Wikipedia <ref>{{Cite pmid|25270058 }}</ref> Protein solubilization: a novel approach #MMPMID25270058 Johnson DH ; Wilson WW ; DeLucas LJ J Chromatogr B Analyt Technol Biomed Life Sci 2014[Nov]; 971 (ä): 99-106 PMID25270058 show ga Formulation development presents significant challenges with respect to protein therapeutics. One component of these challenges is to attain high protein solubility (>50mg/ml for immunoglobulins) with minimal aggregation. Protein-protein interactions contribute to aggregation and the integral sum of these interactions can be quantified by a thermodynamic parameter known as the osmotic second virial coefficient (B-value). The method presented here utilizes high-throughput measurement of B-values to identify the influence of additives on protein-protein interactions. The experiment design uses three tiers of screens to arrive at final solution conditions that improve protein solubility. The first screen identifies individual additives that reduce protein interactions. A second set of B-values are then measured for different combinations of these additives via an incomplete factorial screen. Results from the incomplete factorial screen are used to train an artificial neural network (ANN). The "trained" ANN enables predictions of B-values for more than 4000 formulations that include additive combinations not previously experimentally measured. Validation steps are incorporated throughout the screening process to ensure that (1) the protein's thermal and aggregation stability characteristics are not reduced and (2) the artificial neural network predictive model is accurate. The ability of this approach to reduce aggregation and increase solubility is demonstrated using an IgG protein supplied by Minerva Biotechnologies, Inc. |*Chemistry, Pharmaceutical [MESH] |Chromatography/methods [MESH] |Drug Industry [MESH] |Drug Interactions [MESH] |Drug Stability [MESH] |Neural Networks, Computer [MESH] |Proteins/*chemistry/therapeutic use [MESH] |Solubility [MESH] |Solutions [MESH]Protein solubilization: a novel approach (epmc).pdf DeepDyve Pubget Overpricing