Developability assessment for monoclonal antibody drug candidates: a case study

References

• Brader ML, Estey T, Bai S, Alston RW, Lucas KK, Lantz S, Landsman P, Maloney KM. 2015. Examination of thermal unfolding and aggregation profiles of a series of developable therapeutic monoclonal antibodies. Mol Pharm. 12(4):1005–1017.
   PubMed Web of Science ®Google Scholar
• Connolly BD, Petry C, Yadav S, Demeule B, Ciaccio N, Moore JM, Shire SJ, Gokarn YR. 2012. Weak interactions govern the viscosity of concentrated antibody solutions: high-throughput analysis using the diffusion interaction parameter. Biophys J. 103(1):69–78.
   PubMed Web of Science ®Google Scholar
• Ecker DM, Jones SD, Levine HL. 2015. The therapeutic monoclonal antibody market. MAbs. 7(1):9–14.
   PubMed Web of Science ®Google Scholar
• Elgundi Z, Reslan M, Cruz E, Sifniotis V, Kayser V. 2017. The state-of-play and future of antibody therapeutics. Adv Drug Deliv Rev. 122:2–19.
   PubMed Web of Science ®Google Scholar
• Garidel P, Blume A, Wagner M. 2015. Prediction of colloidal stability of high concentration protein formulations. Pharm Dev Technol. 20(3):367–374.
   PubMed Web of Science ®Google Scholar
• Godar M, de Haard H, Blanchetot C, Rasser J. 2018. Therapeutic bispecific antibody formats: a patent applications review (1994-2017). Expert Opin Ther Pat. 28(3):251–276.
   PubMed Web of Science ®Google Scholar
• Heitmann D. 2014. Evaluation of chemical stability during developability assessment of therapeutic antibodies. Liverpool (UK): Novartis. https://www.formulation.org.uk/images/mibio2014/presentations/daniel-heitmann.pdf
   Google Scholar
• Helbig C, Ammann G, Menzen T, Friess W, Wuchner K, Hawe A. 2019. Backgrounded membrane imaging (BMI) for high-throughput characterization of subvisible particles during biopharmaceutical drug product development. J Pharm Sci. 109(1):264–276.
   PubMed Web of Science ®Google Scholar
• Insaidoo FK, Rauscher MA, Smithline SJ, Kaarsholm NC, Feuston BP, Ortigosa AD, Linden TO, Roush DJ. 2015. Targeted purification development enabled by computational biophysical modeling. Biotechnol Prog. 31(1):154–164.
   PubMed Web of Science ®Google Scholar
• Ionescu RM, Vlasak J, Price C, Kirchmeier M. 2008. Contribution of variable domains to the stability of humanized IgG1 monoclonal antibodies. J Pharm Sci. 97(4):1414–1426.
   PubMed Web of Science ®Google Scholar
• Ito T, Tsumoto K. 2013. Effects of subclass change on the structural stability of chimeric, humanized, and human antibodies under thermal stress. Protein Sci. 22(11):1542–1551.
   PubMed Web of Science ®Google Scholar
• Jones B. 2016. The development of biophysical screening methods to identify better candidates. https://cdn.ymaws.com/www.casss.org/resource/resmgr/HOS_Speaker_Slides/2016_HOS__JonesBryan.pdf
   Google Scholar
• Kalonia C, Kumru OS, Kim JH, Middaugh CR, Volkin DB. 2013. Radar chart array analysis to visualize effects of formulation variables on IgG1 particle formation as measured by multiple analytical techniques. J Pharm Sci. 102(12):4256–4267.
   PubMed Web of Science ®Google Scholar
• Neergaard MS, Kalonia DS, Parshad H, Nielsen AD, Moller EH, van de Weert M. 2013. Viscosity of high concentration protein formulations of monoclonal antibodies of the IgG1 and IgG4 subclass - prediction of viscosity through protein-protein interaction measurements. Eur J Pharm Sci. 49(3):400–410.
   PubMed Web of Science ®Google Scholar
• Creative Biolabs. 2018. New monoclonal antibody drug approvals hit record levels in 2017. Shirley (NY): Creative Biolabs. https://www.creative-biolabs.com/blog/index.php/new-monoclonal-antibody-drug-approvals-in-2017/
   Google Scholar
• Nichols P, Li L, Kumar S, Buck PM, Singh SK, Goswami S, Balthazor B, Conley TR, Sek D, Allen MJ. 2015. Rational design of viscosity reducing mutants of a monoclonal antibody: hydrophobic versus electrostatic inter-molecular interactions. MAbs. 7(1):212–230.
   PubMed Web of Science ®Google Scholar
• Nishi H, Miyajima M, Nakagami H, Noda M, Uchiyama S, Fukui K. 2010. Phase separation of an IgG1 antibody solution under a low ionic strength condition. Pharm Res. 27(7):1348–1360.
   PubMed Web of Science ®Google Scholar
• Pindrus M, Shire SJ, Kelley RF, Demeule B, Wong R, Xu Y, Yadav S. 2015. Solubility challenges in high concentration monoclonal antibody formulations: relationship with amino acid sequence and intermolecular interactions. Mol Pharm. 12(11):3896–3907.
   PubMed Web of Science ®Google Scholar
• Ramachander R, Rathore N. 2013. Molecule and manufacturability assessment leading to robust commercial formulation for therapeutic proteins. In: Kolhe P, Shah M, Rathore N, editors. Sterile product development: formulation, process, quality and regulatory considerations. New York (NY): Springer; p. 33–45.
   Google Scholar
• Raut AS, Kalonia DS. 2015. Opalescence in monoclonal antibody solutions and its correlation with intermolecular interactions in dilute and concentrated solutions. J Pharm Sci. 104(4):1263–1274.
   PubMed Web of Science ®Google Scholar
• Raut AS, Kalonia DS. 2016. Viscosity analysis of dual variable domain immunoglobulin protein solutions: role of size, electroviscous effect and protein-protein interactions. Pharm Res. 33(1):155–166.
   PubMed Web of Science ®Google Scholar
• Seeliger D, Fenn TD, Karow-Zwick AR. 2016. Developability predictions for antibody engineering and risk mitigation. Am Pharm Rev. 19(4). https://www.americanpharmaceuticalreview.com/Featured-Articles/188776-Developability-Predictions-for-Antibody-Engineering-and-Risk-Mitigation/
   Google Scholar
• Shah DD, Zhang J, Maity H, Mallela KMG. 2018. Effect of photo-degradation on the structure, stability, aggregation, and function of an IgG1 monoclonal antibody. Int J Pharm. 547(1–2):438–449.
   PubMed Web of Science ®Google Scholar
• Sharma VK, Kelley RF. 2015. Molecular assessment of monoclonal antibody-based therapeutics enabling lead selection for clinical development. In: Rosenberg A, Demeule B, editors. Biobetters: protein engineering to approach the curative. New York (NY): Springer; p. 153–180.
   Google Scholar
• Sharma VK, Patapoff TW, Kabakoff B, Pai S, Hilario E, Zhang B, Li C, Borisov O, Kelley RF, Chorny I, et al. 2014. In silico selection of therapeutic antibodies for development: viscosity, clearance, and chemical stability. Proc Natl Acad Sci USA. 111(52):18601–18606.
   PubMed Web of Science ®Google Scholar
• Singh S, Kumar NK, Dwiwedi P, Charan J, Kaur R, Sidhu P, Chugh VK. 2018. Monoclonal antibodies: a review. Curr Clin Pharmacol. 13(2):85–99.
   PubMed Web of Science ®Google Scholar
• Spiess C, Zhai Q, Carter PJ. 2015. Alternative molecular formats and therapeutic applications for bispecific antibodies. Mol Immunol. 67(2):95–106.
   PubMed Web of Science ®Google Scholar
• Thiagarajan G, Semple A, James JK, Cheung JK, Shameem M. 2016. A comparison of biophysical characterization techniques in predicting monoclonal antibody stability. MAbs. 8(6):1088–1097.
   PubMed Web of Science ®Google Scholar
• Vlasak J, Ionescu R. 2011. Fragmentation of monoclonal antibodies. MAbs. 3(3):253–263.
   PubMed Web of Science ®Google Scholar
• Wakankar AA, Borchardt RT. 2006. Formulation considerations for proteins susceptible to asparagine deamidation and aspartate isomerization. J Pharm Sci. 95(11):2321–2336.
   PubMed Web of Science ®Google Scholar
• Wang Y, Lomakin A, Latypov RF, Benedek GB. 2011. Phase separation in solutions of monoclonal antibodies and the effect of human serum albumin. Proc Nat Acad Sci. 108(40):16606–16611.
   PubMed Web of Science ®Google Scholar
• Warne NW. 2011. Development of high concentration protein biopharmaceuticals: the use of platform approaches in formulation development. Eur J Pharm Biopharm. 78(2):208–212.
   PubMed Web of Science ®Google Scholar
• Wu G, Wang S, Tian Z, Zhang N, Sheng H, Dai W, Qian F. 2017. Elucidating the weak protein-protein interaction mechanisms behind the liquid-liquid phase separation of a mAb solution by different types of additives. Eur J Pharm Biopharm. 120:1–8.
   PubMed Web of Science ®Google Scholar
• Yadav S, Laue TM, Kalonia DS, Singh SN, Shire SJ. 2012. The influence of charge distribution on self-association and viscosity behavior of monoclonal antibody solutions. Mol Pharm. 9(4):791–802.
   PubMed Web of Science ®Google Scholar
• Yadav S, Scherer TM, Shire SJ, Kalonia DS. 2011. Use of dynamic light scattering to determine second virial coefficient in a semidilute concentration regime. Anal Biochem. 411(2):292–296.
   PubMed Web of Science ®Google Scholar
• Yadav S, Shire SJ, Kalonia DS. 2012. Viscosity behavior of high-concentration monoclonal antibody solutions: correlation with interaction parameter and electroviscous effects. J Pharm Sci. 101(3):998–1011.
   PubMed Web of Science ®Google Scholar
• Yadav S, Sreedhara A, Kanai S, Liu J, Lien S, Lowman H, Kalonia DS, Shire SJ. 2011. Establishing a link between amino acid sequences and self-associating and viscoelastic behavior of two closely related monoclonal antibodies. Pharm Res. 28(7):1750–1764.
   PubMed Web of Science ®Google Scholar
• Yang X, Xu W, Dukleska S, Benchaar S, Mengisen S, Antochshuk V, Cheung J, Mann L, Babadjanova Z, Rowand J, et al. 2013. Developability studies before initiation of process development: improving manufacturability of monoclonal antibodies. MAbs. 5(5):787–794.
   PubMed Web of Science ®Google Scholar
• Zidar M, Susteric A, Ravnik M, Kuzman D. 2017. High throughput prediction approach for monoclonal antibody aggregation at high concentration. Pharm Res. 34(9):1831–1839.
   PubMed Web of Science ®Google Scholar