12,511
Views
12
CrossRef citations to date
0
Altmetric
Review

Blueprint for antibody biologics developability

, , , , , , , & show all
Article: 2185924 | Received 12 Dec 2022, Accepted 24 Feb 2023, Published online: 07 Mar 2023

References

  • Kaplon H, Chenoweth A, Crescioli S, Reichert JM. Antibodies to watch in 2022. MAbs. 2022;14:2014296. doi:10.1080/19420862.2021.2014296. PMID: 35030985.
  • Mullard A. FDA approves 100th monoclonal antibody product. Nat Rev Drug Discov. 2021;20:491–20. doi:10.1038/d41573-021-00079-7. PMID: 33953368.
  • Lu X, Machiesky LA, De Mel N, Du Q, Xu W, Washabaugh M, Jiang XR, Wang J. Characterization of IgG1 Fc deamidation at asparagine 325 and its impact on antibody-dependent cell-mediated cytotoxicity and FcgammaRIIIa binding. Sci Rep. 2020;10:383. doi:10.1038/s41598-019-57184-2. PMID: 31941950.
  • Chiu ML, Goulet DR, Teplyakov A, Gilliland GL. Antibody structure and function: the basis for engineering therapeutics. Antibodies (Basel). 2019;8 PMID: 31816964. doi:10.3390/antib8040055.
  • Wang X, Mathieu M, Brezski RJ. IgG Fc engineering to modulate antibody effector functions. Protein Cell. 2018;9:63–73. doi:10.1007/s13238-017-0473-8. PMID: 28986820.
  • Jiang XR, Song A, Bergelson S, Arroll T, Parekh B, May K, Chung S, Strouse R, Mire-Sluis A, Schenerman M. Advances in the assessment and control of the effector functions of therapeutic antibodies. Nat Rev Drug Discov. 2011;10:101–11. doi:10.1038/nrd3365. PMID: 21283105.
  • Saunders KO. Conceptual approaches to modulating antibody effector functions and circulation half-Life. Front Immunol. 2019;10:1296. doi:10.3389/fimmu.2019.01296. PMID: 31231397.
  • Fonseca MHG, Furtado GP, Bezerra MRL, Pontes LQ, Fernandes CFC. Boosting half-life and effector functions of therapeutic antibodies by Fc-engineering: an interaction-function review. Int J Biol Macromol. 2018;119:306–11. doi:10.1016/j.ijbiomac.2018.07.141. PMID: 30041038.
  • Kim SJ, Park Y, Hong HJ. Antibody engineering for the development of therapeutic antibodies. Mol Cells PMID: 16258237. 2005;20:17–29. https://www.ncbi.nlm.nih.gov/pubmed/16258237.
  • Maynard J, Georgiou G. Antibody engineering. Annu Rev Biomed Eng. 2000;2:339–76. doi:10.1146/annurev.bioeng.2.1.339. PMID: 11701516.
  • Yang X, Xu W, Dukleska S, Benchaar S, Mengisen S, Antochshuk V, Cheung J, Mann L, Babadjanova Z, Rowand J, et al. Developability studies before initiation of process development: improving manufacturability of monoclonal antibodies. MAbs. 2013;5:787–94. PMID: 23883920. doi:10.4161/mabs.25269.
  • Xu Y, Wang D, Mason B, Rossomando T, Li N, Liu D, Cheung JK, Xu W, Raghava S, Katiyar A, et al. Structure, heterogeneity and developability assessment of therapeutic antibodies. MAbs. 2019;11:239–64. PMID: 30543482. doi:10.1080/19420862.2018.1553476.
  • Garripelli VK, Wu Z, Gupta S. Developability assessment for monoclonal antibody drug candidates: a case study. Pharm Dev Technol. 2021;26:11–20. doi:10.1080/10837450.2020.1829641. PMID: 32986499.
  • Kaur H. Stability testing in monoclonal antibodies. Crit Rev Biotechnol. 2021;41:692–714. doi:10.1080/07388551.2021.1874281. PMID: 33596751.
  • Wang SS, Yan YS, Ho K. US FDA-approved therapeutic antibodies with high-concentration formulation: summaries and perspectives. Antib Ther. 2021;4:262–72. doi:10.1093/abt/tbab027. PMID: 34909579.
  • Kannan A, Shieh IC, Hristov P, Fuller GG. In-Use Interfacial Stability of Monoclonal Antibody Formulations Diluted in Saline i.V. Bags J Pharm Sci. 2021;110:1687–92. doi:10.1016/j.xphs.2020.10.036. PMID: 33141046.
  • Igawa T, Tsunoda H, Tachibana T, Maeda A, Mimoto F, Moriyama C, Nanami M, Sekimori Y, Nabuchi Y, Aso Y, et al. Reduced elimination of IgG antibodies by engineering the variable region. Protein Eng Des Sel. 2010;23:385–92. PMID: 20159773. doi:10.1093/protein/gzq009.
  • Carpenter JF, Randolph TW, Jiskoot W, Crommelin DJ, Middaugh CR, Winter G, Fan YX, Kirshner S, Verthelyi D, Kozlowski S, et al. Overlooking subvisible particles in therapeutic protein products: gaps that may compromise product quality. J Pharm Sci. 2009;98:1201–05. PMID: 18704929. doi:10.1002/jps.21530.
  • Jain T, Sun T, Durand S, Hall A, Houston NR, Nett JH, Sharkey B, Bobrowicz B, Caffry I, Yu Y, et al. Biophysical properties of the clinical-stage antibody landscape. Proc Natl Acad Sci U S A. 2017;114:944–49. PMID: 28096333. doi:10.1073/pnas.1616408114.
  • Jarasch A, Koll H, Regula JT, Bader M, Papadimitriou A, Kettenberger H. Developability assessment during the selection of novel therapeutic antibodies. J Pharm Sci. 2015;104:1885–98. doi:10.1002/jps.24430. PMID: 25821140.
  • Vi R, Mj T, Gw B. Accelerated formulation development of monoclonal antibodies (mAbs) and mAb-based modalities: review of methods and tools. J Biomol Screen. 2015;20:468–83. doi:10.1177/1087057114565593. PMID: 25576149.
  • Svilenov HL, Arosio P, Menzen T, Tessier P, Sormanni P. Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties. MAbs. 2023;15:2164459. doi:10.1080/19420862.2022.2164459. PMID: 36629855.
  • Spencer S, Bethea D, Raju TS, Giles-Komar J, Feng Y. Solubility evaluation of murine hybridoma antibodies. MAbs. 2012;4:319–25. doi:10.4161/mabs.19869. PMID: 22531448.
  • Wu SJ, Luo J, O’neil KT, Kang J, Lacy ER, Canziani G, Baker A, Huang M, Tang QM, Raju TS, et al. Structure-based engineering of a monoclonal antibody for improved solubility. Protein Eng Des Sel. 2010;23:643–51. PMID: 20543007. doi:10.1093/protein/gzq037.
  • Pepinsky RB, Silvian L, Berkowitz SA, Farrington G, Lugovskoy A, Walus L, Eldredge J, Capili A, Mi S, Graff C, et al. Improving the solubility of anti-LINGO-1 monoclonal antibody Li33 by isotype switching and targeted mutagenesis. Protein Sci. 2010;19:954–66. PMID: 20198683. doi:10.1002/pro.372.
  • Cunningham O, Scott M, Zhou ZS, Finlay WJJ. Polyreactivity and polyspecificity in therapeutic antibody development: risk factors for failure in preclinical and clinical development campaigns. MAbs. 2021;13:1999195. doi:10.1080/19420862.2021.1999195. PMID: 34780320.
  • Sidhu SS, Li B, Chen Y, Fellouse FA, Eigenbrot C, Fuh G. Phage-displayed antibody libraries of synthetic heavy chain complementarity determining regions. J Mol Biol. 2004;338:299–310. doi:10.1016/j.jmb.2004.02.050. PMID: 15066433.
  • Jespers L, Schon O, Famm K, Winter G. Aggregation-resistant domain antibodies selected on phage by heat denaturation. Nat Biotechnol. 2004;22:1161–65. doi:10.1038/nbt1000. PMID: 15300256.
  • Traxlmayr MW, Obinger C. Directed evolution of proteins for increased stability and expression using yeast display. Arch Biochem Biophys. 2012;526:174–80. doi:10.1016/j.abb.2012.04.022. PMID: 22575387.
  • Cherf GM, Cochran JR. Applications of Yeast Surface Display for Protein Engineering. Methods Mol Biol. 2015;1319:155–75. doi:10.1007/978-1-4939-2748-7_8. PMID: 26060074.
  • Rossant CJ, Carroll D, Huang L, Elvin J, Neal F, Walker E, Benschop JJ, Kim EE, Barry ST, Vaughan TJ. Phage display and hybridoma generation of antibodies to human CXCR2 yields antibodies with distinct mechanisms and epitopes. MAbs. 2014;6:1425–38. doi:10.4161/mabs.34376. PMID: 25484064.
  • Mehta N, Maddineni S, Kelly RL, Lee RB, Hunter SA, Silberstein JL, Parra Sperberg RA, Miller CL, Rabe A, Labanieh L, et al. An engineered antibody binds a distinct epitope and is a potent inhibitor of murine and human VISTA. Sci Rep. 2020;10:15171. PMID: 32938950. doi:10.1038/s41598-020-71519-4.
  • Safdari Y, Farajnia S, Asgharzadeh M, Khalili M. Antibody humanization methods - a review and update. Biotechnol Genet Eng Rev. 2013;29:175–86. doi:10.1080/02648725.2013.801235. PMID: 24568279.
  • Bailly M, Mieczkowski C, Juan V, Metwally E, Tomazela D, Baker J, Uchida M, Kofman E, Raoufi F, Motlagh S, et al. Predicting Antibody Developability Profiles Through Early Stage Discovery Screening. MAbs. 2020;12:1743053. PMID: 32249670. doi:10.1080/19420862.2020.1743053.
  • Xu A, Kim HS, Estee S, ViaJar S, Galush WJ, Gill A, Hotzel I, Lazar GA, McDonald P, Andersen N, et al. Susceptibility of Antibody CDR Residues to Chemical Modifications Can Be Revealed Prior to Antibody Humanization and Aid in the Lead Selection Process. Mol Pharm. 2018;15:4529–37. PMID: 30118239. doi:10.1021/acs.molpharmaceut.8b00536.
  • Sawant MS, Streu CN, Wu L, Tessier PM. Toward Drug-Like Multispecific Antibodies by Design. Int J Mol Sci. 2020;21 PMID: 33053650. doi:10.3390/ijms21207496.
  • Trianni Inc. Whitepaper: transgenic Mice: transforming Targeted Monoclonal Antibody (mAb) Therapeutics (2017).
  • Lu RM, Hwang YC, Liu IJ, Lee CC, Tsai HZ, Li HJ, Wu HC. Development of therapeutic antibodies for the treatment of diseases. J Biomed Sci. 2020;27:1. doi:10.1186/s12929-019-0592-z. PMID: 31894001.
  • Vidarsson G, Dekkers G, Rispens T. IgG subclasses and allotypes: from structure to effector functions. Front Immunol. 2014;5:520. doi:10.3389/fimmu.2014.00520. PMID: 25368619.
  • Phakham T, Boonkrai C, Wongtangprasert T, Audomsun T, Attakitbancha C, Saelao P, Muanwien P, Sooksai S, Hirankarn N, Pisitkun T. Highly efficient hybridoma generation and screening strategy for anti-PD-1 monoclonal antibody development. Sci Rep. 2022;12:17792. doi:10.1038/s41598-022-20560-6. PMID: 36273231.
  • Estes B, Hsu YR, Tam LT, Sheng J, Stevens J, Haldankar R. Uncovering methods for the prevention of protein aggregation and improvement of product quality in a transient expression system. Biotechnol Prog. 2015;31:258–67. doi:10.1002/btpr.2021. PMID: 25395220.
  • Ma H, O’fagain C, O’kennedy R. Antibody stability: a key to performance - Analysis, influences and improvement. Biochimie. 2020;177:213–25. PMID: 32891698. doi:10.1016/j.biochi.2020.08.019.
  • Cromwell ME, Hilario E, Jacobson F. Protein aggregation and bioprocessing. Aaps J. 2006;8:E572–579. doi:10.1208/aapsj080366. PMID: 17025275.
  • Some D, Amartely H, Tsadok A, Lebendiker M. Characterization of Proteins by Size-Exclusion Chromatography Coupled to Multi-Angle Light Scattering (SEC-MALS). J Vis Exp [ PMID: 31282880]. 2019. doi:10.3791/59615-v.
  • Vazquez-Rey M, Lang DA. Aggregates in monoclonal antibody manufacturing processes. Biotechnol Bioeng. 2011;108:1494–508. doi:10.1002/bit.23155. PMID: 21480193.
  • Lechner A, Giorgetti J, Gahoual R, Beck A, Leize-Wagner E, Francois YN. Insights from capillary electrophoresis approaches for characterization of monoclonal antibodies and antibody drug conjugates in the period 2016-2018. J Chromatogr B Analyt Technol Biomed Life Sci. 2019;1122-1123:1–17. doi:10.1016/j.jchromb.2019.05.014. PMID: 31128359.
  • Vlasak J, Ionescu R. Fragmentation of monoclonal antibodies. MAbs. 2011;3:253–63. doi:10.4161/mabs.3.3.15608. PMID: 21487244.
  • Le Basle Y, Chennell P, Tokhadze N, Astier A, Sautou V. Physicochemical Stability of Monoclonal Antibodies: a Review. J Pharm Sci. 2020;109:169–90. doi:10.1016/j.xphs.2019.08.009. PMID: 31465737.
  • Wang W. Protein aggregation and its inhibition in biopharmaceutics. Int J Pharm. 2005;289:1–30. doi:10.1016/j.ijpharm.2004.11.014. PMID: 15652195.
  • Philo JS, Arakawa T. Mechanisms of protein aggregation. Curr Pharm Biotechnol. 2009;10:348–51. doi:10.2174/138920109788488932. PMID: 19519409.
  • Mieczkowski C, Bahmanjah S, Yu Y, Baker J, Raghunathan G, Tomazela D, Hsieh M, McCoy M, Strickland C, Fayadat-Dilman L. Crystal Structure and Characterization of Human Heavy-Chain Only Antibodies Reveals a Novel, Stable Dimeric Structure Similar to Monoclonal Antibodies. Antibodies (Basel). 2020;9 PMID: 33266498. doi:10.3390/antib9040066.
  • Stoyle CL, Stephens PE, Humphreys DP, Heywood S, Cain K, Bulleid NJ. IgG light chain-independent secretion of heavy chain dimers: consequence for therapeutic antibody production and design. Biochem J. 2017;474:3179–88. doi:10.1042/BCJ20170342. PMID: 28784690.
  • Rajendra Y, Peery RB, Hougland MD, Barnard GC, Wu X, Fitchett JR, Bacica M, Demarest SJ. Transient and stable CHO expression, purification and characterization of novel hetero-dimeric bispecific IgG antibodies. Biotechnol Prog. 2017;33:469–77. doi:10.1002/btpr.2414. PMID: 27977915.
  • Tam SH, McCarthy SG, Armstrong AA, Somani S, Wu SJ, Liu X, Gervais A, Ernst R, Saro D, Decker R, et al. Functional, Biophysical, and Structural Characterization of Human IgG1 and IgG4 Fc Variants with Ablated Immune Functionality. Antibodies (Basel). 2017;6: PMID: 31548527. doi:10.3390/antib6030012.
  • Thiagarajan G, Semple A, James JK, Cheung JK, Shameem M. A comparison of biophysical characterization techniques in predicting monoclonal antibody stability. MAbs. 2016;8:1088–97. doi:10.1080/19420862.2016.1189048. PMID: 27210456.
  • Ionescu RM, Vlasak J, Price C, Kirchmeier M. Contribution of variable domains to the stability of humanized IgG1 monoclonal antibodies. J Pharm Sci. 2008;97:1414–26. doi:10.1002/jps.21104. PMID: 17721938.
  • Rabia LA, Desai AA, Jhajj HS, Tessier PM. Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility. Biochem Eng J. 2018;137:365–74. doi:10.1016/j.bej.2018.06.003. PMID: 30666176.
  • Vermeer AW, Norde W. The thermal stability of immunoglobulin: unfolding and aggregation of a multi-domain protein. Biophys J. 2000;78:394–404. doi:10.1016/S0006-3495(00)76602-1. PMID: 10620303.
  • Brader ML, Estey T, Bai S, Alston RW, Lucas KK, Lantz S, Landsman P, Maloney KM. Examination of thermal unfolding and aggregation profiles of a series of developable therapeutic monoclonal antibodies. Mol Pharm. 2015;12:1005–17. doi:10.1021/mp400666b. PMID: 25687223.
  • Lehermayr C, Mahler HC, Mader K, Fischer S. Assessment of net charge and protein-protein interactions of different monoclonal antibodies. J Pharm Sci. 2011;100:2551–62. doi:10.1002/jps.22506. PMID: 21294130.
  • Li Y. Effective strategies for host cell protein clearance in downstream processing of monoclonal antibodies and Fc-fusion proteins. Protein Expr Purif. 2017;134:96–103. doi:10.1016/j.pep.2017.04.006. PMID: 28414067.
  • Cui Y, Cui P, Chen B, Li S, Guan H. Monoclonal antibodies: formulations of marketed products and recent advances in novel delivery system. Drug Dev Ind Pharm. 2017;43:519–30. doi:10.1080/03639045.2017.1278768. PMID: 28049357.
  • Strickley RG, Lambert WJ. A review of Formulations of Commercially Available Antibodies. J Pharm Sci. 2021;110:2590–608 e2556. doi:10.1016/j.xphs.2021.03.017. PMID: 33789155.
  • Singh SK, Kumar D, Nagpal S, Dubey SK, Rathore AS. A Charge Variant of Bevacizumab Offers Enhanced FcRn-Dependent Pharmacokinetic Half-Life and Efficacy. Pharm Res. 2022;39:851–65. doi:10.1007/s11095-022-03236-8. PMID: 35355206.
  • Li B, Tesar D, Boswell CA, Cahaya HS, Wong A, Zhang J, Meng YG, Eigenbrot C, Pantua H, Diao J, et al. Framework selection can influence pharmacokinetics of a humanized therapeutic antibody through differences in molecule charge. MAbs. 2014;6:1255–64. PMID: 25517310. doi:10.4161/mabs.29809.
  • Boswell CA, Tesar DB, Mukhyala K, Theil FP, Fielder PJ, Khawli LA. Effects of charge on antibody tissue distribution and pharmacokinetics. Bioconjug Chem. 2010;21:2153–63. doi:10.1021/bc100261d. PMID: 21053952.
  • Bumbaca Yadav D, Sharma VK, Boswell CA, Hotzel I, Tesar D, Shang Y, Ying Y, Fischer SK, Grogan JL, Chiang EY, et al. Evaluating the Use of Antibody Variable Region (Fv) Charge as a Risk Assessment Tool for Predicting Typical Cynomolgus Monkey Pharmacokinetics. J Biol Chem. 2015;290:29732–41. PMID: 26491012. doi:10.1074/jbc.M115.692434.
  • Schoch A, Kettenberger H, Mundigl O, Winter G, Engert J, Heinrich J, Emrich T. Charge-mediated influence of the antibody variable domain on FcRn-dependent pharmacokinetics. Proc Natl Acad Sci U S A. 2015;112:5997–6002. doi:10.1073/pnas.1408766112. PMID: 25918417.
  • Gupta S, Jiskoot W, Schoneich C, Rathore AS. Oxidation and Deamidation of Monoclonal Antibody Products: potential Impact on Stability, Biological Activity, and Efficacy. J Pharm Sci. 2022;111:903–18. doi:10.1016/j.xphs.2021.11.024. PMID: 34890632.
  • Voynov V, Chennamsetty N, Kayser V, Helk B, Trout BL. Predictive tools for stabilization of therapeutic proteins. MAbs. 2009;1:580–82. doi:10.4161/mabs.1.6.9773. PMID: 20068399.
  • Wu H, Randolph TW. Aggregation and Particle Formation During Pumping of an Antibody Formulation are Controlled by Electrostatic Interactions Between Pump Surfaces and Protein Molecules. J Pharm Sci. 2020;109:1473–82. doi:10.1016/j.xphs.2020.01.023. PMID: 32004539.
  • Tomar DS, Kumar S, Singh SK, Goswami S, Li L. Molecular basis of high viscosity in concentrated antibody solutions: strategies for high concentration drug product development. MAbs. 2016;8:216–28. doi:10.1080/19420862.2015.1128606. PMID: 26736022.
  • Shire SJ. Formulation and manufacturability of biologics. Curr Opin Biotechnol. 2009;20:708–14. doi:10.1016/j.copbio.2009.10.006. PMID: 19880308.
  • Yadav S, Shire SJ, Kalonia DS. Factors affecting the viscosity in high concentration solutions of different monoclonal antibodies. J Pharm Sci. 2010;99:4812–29. doi:10.1002/jps.22190. PMID: 20821382.
  • Quigley A, Williams DR. The second virial coefficient as a predictor of protein aggregation propensity: a self-interaction chromatography study. Eur J Pharm Biopharm. 2015;96:282–90. doi:10.1016/j.ejpb.2015.07.025. PMID: 26259782.
  • Sule SV, Sukumar M, WFt W, Marcelino-Cruz AM, Sample T, Tessier PM. High-throughput analysis of concentration-dependent antibody self-association. Biophys J. 2011;101:1749–57. doi:10.1016/j.bpj.2011.08.036. PMID: 21961601.
  • Wu J, Schultz JS, Weldon CL, Sule SV, Chai Q, Geng SB, Dickinson CD, Tessier PM. Discovery of highly soluble antibodies prior to purification using affinity-capture self-interaction nanoparticle spectroscopy. Protein Eng Des Sel. 2015;28:403–14. doi:10.1093/protein/gzv045. PMID: 26363633.
  • Phan S, Walmer A, Shaw EW, Chai Q. High-throughput profiling of antibody self-association in multiple formulation conditions by PEG stabilized self-interaction nanoparticle spectroscopy. MAbs. 2022;14:2094750. doi:10.1080/19420862.2022.2094750. PMID: 35830420.
  • Lu X, Nobrega RP, Lynaugh H, Jain T, Barlow K, Boland T, Sivasubramanian A, Vasquez M, Xu Y. Deamidation and isomerization liability analysis of 131 clinical-stage antibodies. MAbs. 2019;11:45–57. doi:10.1080/19420862.2018.1548233. PMID: 30526254.
  • Yuk IH, Zhang B, Yang Y, Dutina G, Leach KD, Vijayasankaran N, Shen AY, Andersen DC, Snedecor BR, Joly JC. Controlling glycation of recombinant antibody in fed-batch cell cultures. Biotechnol Bioeng. 2011;108:2600–10. doi:10.1002/bit.23218. PMID: 21618472.
  • Bee JS, Goletz TJ, Ragheb JA. The future of protein particle characterization and understanding its potential to diminish the immunogenicity of biopharmaceuticals: a shared perspective. J Pharm Sci. 2012;101:3580–85. doi:10.1002/jps.23247. PMID: 22736570.
  • Narhi LO, Corvari V, Ripple DC, Afonina N, Cecchini I, Defelippis MR, Garidel P, Herre A, Koulov AV, Lubiniecki T, et al. Subvisible (2-100 μm) Particle Analysis During Biotherapeutic Drug Product Development: part 1, Considerations and Strategy. J Pharm Sci. 2015;104:1899–908. PMID: 25832583. doi:10.1002/jps.24437.
  • Vargas SK, Eskafi A, Carter E, Ciaccio N. A comparison of background membrane imaging versus flow technologies for subvisible particle analysis of biologics. Int J Pharm. 2020;578:119072. doi:10.1016/j.ijpharm.2020.119072. PMID: 32001293.
  • Singh SK, Afonina N, Awwad M, Bechtold-Peters K, Blue JT, Chou D, Cromwell M, Krause HJ, Mahler HC, Meyer BK, et al. An industry perspective on the monitoring of subvisible particles as a quality attribute for protein therapeutics. J Pharm Sci. 2010;99:3302–21. PMID: 20310025. doi:10.1002/jps.22097.
  • Grabarek AD, Bozic U, Rousel J, Menzen T, Kranz W, Wuchner K, Jiskoot W, Hawe A. What Makes Polysorbate Functional? Impact of Polysorbate 80 Grade and Quality on IgG Stability During Mechanical Stress. J Pharm Sci. 2020;109:871–80. doi:10.1016/j.xphs.2019.10.015. PMID: 31614127.
  • Morar-Mitrica S, Brisbane C, Nesta D, Ketkar A. Biophysical approaches to the detection and characterization of particles in an antibody solution. American Pharma Rev. 2009;12:34–40.
  • Durbin KR, Nottoli MS, Catron ND, Richwine N, Gj J. High-Throughput, Multispecies, Parallelized Plasma Stability Assay for the Determination and Characterization of Antibody-Drug Conjugate Aggregation and Drug Release. ACS Omega. 2017;2:4207–15. doi:10.1021/acsomega.7b00452. PMID: 30023717.
  • Rodrigues D, Tanenbaum LM, Thirumangalathu R, Somani S, Zhang K, Kumar V, Amin K, Thakkar SV. Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development. J Pharm Sci. 2021;110:1077–82. doi:10.1016/j.xphs.2020.12.016. PMID: 33340533.
  • Bramham JE, Davies SA, Podmore A, Golovanov AP. Stability of a high-concentration monoclonal antibody solution produced by liquid-liquid phase separation. MAbs. 2021;13:1940666. doi:10.1080/19420862.2021.1940666. PMID: 34225583.
  • Zhang T, Zhang J, Hewitt D, Tran B, Gao X, Qiu ZJ, Tejada M, Gazzano-Santoro H, Kao YH. Identification and characterization of buried unpaired cysteines in a recombinant monoclonal IgG1 antibody. Anal Chem. 2012;84:7112–23. doi:10.1021/ac301426h. PMID: 22794164.
  • Robotham AC, Kelly JF. Detection and quantification of free sulfhydryls in monoclonal antibodies using maleimide labeling and mass spectrometry. MAbs. 2019;11:757–66. doi:10.1080/19420862.2019.1595307. PMID: 30894096.
  • Shukla AA, Hubbard B, Tressel T, Guhan S, Low D. Downstream processing of monoclonal antibodies–application of platform approaches. J Chromatogr B Analyt Technol Biomed Life Sci. 2007;848:28–39. doi:10.1016/j.jchromb.2006.09.026. PMID: 17046339.
  • Wurm FM. Production of recombinant protein therapeutics in cultivated mammalian cells. Nat Biotechnol. 2004;22:1393–98. doi:10.1038/nbt1026. PMID: 15529164.
  • Liu HF, Ma J, Winter C, Bayer R. Recovery and purification process development for monoclonal antibody production. MAbs. 2010;2:480–99. doi:10.4161/mabs.2.5.12645. PMID: 20647768.
  • Falconer RJ, Chan C, Hughes K, Munro TP. Stabilization of a monoclonal antibody during purification and formulation by addition of basic amino acid excipients. J Chem Tech Biotech. 2011;86:942–48. doi:10.1002/jctb.2657.
  • ICH Harmonised Tripartite Guideline. Evaluation for Stability Data Q1E Step 4. Geneva, Switzerland: The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use; 2003. [accessed 2022 Dec 1]. https://www.ich.org/page/quality-guidelines
  • Kuzman D, Bunc M, Ravnik M, Reiter F, Zagar L, Boncina M. Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics. Sci Rep. 2021;11:20534. doi:10.1038/s41598-021-99875-9. PMID: 34654882.
  • Wang W, Roberts CJ. Non-Arrhenius protein aggregation. Aaps J. 2013;15:840–51. doi:10.1208/s12248-013-9485-3. PMID: 23615748.
  • Hauptmann A, Podgorsek K, Kuzman D, Srcic S, Hoelzl G, Loerting T. Impact of Buffer, Protein Concentration and Sucrose Addition on the Aggregation and Particle Formation during Freezing and Thawing. Pharm Res. 2018;35:101. doi:10.1007/s11095-018-2378-5. PMID: 29556730.
  • Haeuser C, Goldbach P, Huwyler J, Friess W, Allmendinger A. Excipients for Room Temperature Stable Freeze-Dried Monoclonal Antibody Formulations. J Pharm Sci. 2020;109:807–17. doi:10.1016/j.xphs.2019.10.016. PMID: 31622600.
  • Halley J, Chou YR, Cicchino C, Huang M, Sharma V, Tan NC, Thakkar S, Zhou LL, Al-Azzam W, Cornen S, et al. An Industry Perspective on Forced Degradation Studies of Biopharmaceuticals: survey Outcome and Recommendations. J Pharm Sci. 2020;109:6–21. PMID: 31563512. doi:10.1016/j.xphs.2019.09.018.
  • Sule SV, Cheung JK, Antochshuk V, Bhalla AS, Narasimhan C, Blaisdell S, Shameem M, Tessier PM. Solution pH that minimizes self-association of three monoclonal antibodies is strongly dependent on ionic strength. Mol Pharm. 2012;9:744–51. doi:10.1021/mp200448j. PMID: 22221144.
  • Hong T, Iwashita K, Shiraki K. Viscosity Control of Protein Solution by Small Solutes: a Review. Curr Protein Pept Sci. 2018;19:746–58. doi:10.2174/1389203719666171213114919. PMID: 29237380.
  • Wang S, Zhang N, Hu T, Dai W, Feng X, Zhang X, Qian F. Viscosity-Lowering Effect of Amino Acids and Salts on Highly Concentrated Solutions of Two IgG1 Monoclonal Antibodies. Mol Pharm. 2015;12:4478–87. doi:10.1021/acs.molpharmaceut.5b00643. PMID: 26528726.
  • Zeng Y, Tran T, Wuthrich P, Naik S, Davagnino J, Greene DG, Mahoney RP, Soane DS. Caffeine as a Viscosity Reducer for Highly Concentrated Monoclonal Antibody Solutions. J Pharm Sci. 2021;110:3594–604. doi:10.1016/j.xphs.2021.06.030. PMID: 34181992.
  • Nowak C, Kc J, Md S, Katiyar A, Bhat R, Sun J, Ponniah G, Neill A, Mason B, Beck A, et al. Forced degradation of recombinant monoclonal antibodies: a practical guide. MAbs. 2017;9:1217–30. doi:10.1080/19420862.2017.1368602. PMID: 28853987.
  • Wang W, Singh S, Zeng DL, King K, Nema S. Antibody structure, instability, and formulation. J Pharm Sci. 2007;96:1–26. doi:10.1002/jps.20727. PMID: 16998873.
  • Chelius D, Rehder DS, Bondarenko PV. Identification and characterization of deamidation sites in the conserved regions of human immunoglobulin gamma antibodies. Anal Chem. 2005;77:6004–11. doi:10.1021/ac050672d. PMID: 16159134.
  • Peters B, Trout BL. Asparagine deamidation: pH-dependent mechanism from density functional theory. Biochemistry. 2006;45:5384–92. doi:10.1021/bi052438n. PMID: 16618128.
  • Svilenov HL, Kulakova A, Zalar M, Golovanov AP, Harris P, Winter G. Orthogonal Techniques to Study the Effect of pH, Sucrose, and Arginine Salts on Monoclonal Antibody Physical Stability and Aggregation During Long-Term Storage. J Pharm Sci. 2020;109:584–94. doi:10.1016/j.xphs.2019.10.065. PMID: 31689429.
  • Robinson NE, Robinson AB. Prediction of protein deamidation rates from primary and three-dimensional structure. Proc Natl Acad Sci U S A. 2001;98:4367–72. doi:10.1073/pnas.071066498. PMID: 11296285.
  • Sydow JF, Lipsmeier F, Larraillet V, Hilger M, Mautz B, Molhoj M, Kuentzer J, Klostermann S, Schoch J, Voelger HR, et al. Structure-based prediction of asparagine and aspartate degradation sites in antibody variable regions. PLoS One. 2014;9:e100736. PMID: 24959685. doi:10.1371/journal.pone.0100736.
  • Qiu H, Wei R, Jaworski J, Boudanova E, Hughes H, VanPatten S, Lund A, Day J, Zhou Y, McSherry T, et al. Engineering an anti-CD52 antibody for enhanced deamidation stability. MAbs. 2019;11:1266–75. PMID: 31199181. doi:10.1080/19420862.2019.1631117.
  • Wang W, Meeler AR, Bergerud LT, Hesselberg M, Byrne M, Wu Z. Quantification and characterization of antibody deamidation by peptide mapping with mass spectrometry. Int J Mass Spectrom. 2012;312:107–13. doi:10.1016/j.ijms.2011.06.006.
  • Dashivets T, Stracke J, Dengl S, Knaupp A, Pollmann J, Buchner J, Schlothauer T. Oxidation in the complementarity-determining regions differentially influences the properties of therapeutic antibodies. MAbs. 2016;8:1525–35. doi:10.1080/19420862.2016.1231277. PMID: 27612038.
  • Folzer E, Diepold K, Bomans K, Finkler C, Schmidt R, Bulau P, Huwyler J, Mahler HC, Koulov AV. Selective Oxidation of Methionine and Tryptophan Residues in a Therapeutic IgG1 Molecule. J Pharm Sci. 2015;104:2824–31. doi:10.1002/jps.24509. PMID: 26010344.
  • Mieczkowski C, Cheng A, Fischmann T, Hsieh M, Baker J, Uchida M, Raghunathan G, Strickland C, Fayadat-Dilman L. Characterization and Modeling of Reversible Antibody Self-Association Provide Insights into Behavior, Prediction, and Correction. Antibodies (Basel). 2021;10 PMID: 33671864. doi:10.3390/antib10010008.
  • Ji JA, Zhang B, Cheng W, Wang YJ. Methionine, tryptophan, and histidine oxidation in a model protein, PTH: mechanisms and stabilization. J Pharm Sci. 2009;98:4485–500. doi:10.1002/jps.21746. PMID: 19455640.
  • U.S. Department of Health and Human Services, Food and Drug Administration. Guidance for Industry: Container Closure Systems for Packaging Human Drugs and Biologics. Chemistry, Manufacturing, and Controls Documentation. Rockville, Maryland: Office of Training and Communications; 1999. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/container-closure-systems-packaging-human-drugs-and-biologics
  • Bhattacharya S, De A, Narasimhan CN, Sharma MK, Yang X, Sharpe M, Dohme A. Stable formulations of anti-ctla4 antibodies alone and in combination with programmed death receptor 1 (pd-1) antibodies and methods of use thereof. WIPO (PCT) Patent WO2018204343A1. 2018 May 1.
  • Chu GC, Chelius D, Xiao G, Khor HK, Coulibaly S, Bondarenko PV. Accumulation of succinimide in a recombinant monoclonal antibody in mildly acidic buffers under elevated temperatures. Pharm Res. 2007;24:1145–56. doi:10.1007/s11095-007-9241-4. PMID: 17385019.
  • Carpenter JF, Arakawa T, Crowe JH. Interactions of stabilizing additives with proteins during freeze-thawing and freeze-drying. Dev Biol Stand. 1992;74:225–38. discussion 238-229. PMID: 1592173.
  • Kueltzo LA, Wang W, Randolph TW, Carpenter JF. Effects of solution conditions, processing parameters, and container materials on aggregation of a monoclonal antibody during freeze-thawing. J Pharm Sci. 2008;97:1801–12. doi:10.1002/jps.21110. PMID: 17823949.
  • Kolhe P, Amend E, Singh SK. Impact of freezing on pH of buffered solutions and consequences for monoclonal antibody aggregation. Biotechnol Prog. 2010;26:727–33. doi:10.1002/btpr.377. PMID: 20039442.
  • Wang X, An Z, Luo W, Xia N, Zhao Q. Molecular and functional analysis of monoclonal antibodies in support of biologics development. Protein Cell. 2018;9:74–85. doi:10.1007/s13238-017-0447-x. PMID: 28733914.
  • Ding Y, Marino M, Zen K, Sheffer J, Almaguer N, Caddy K, Praseuth A. Considerations for Monoclonal Antibody Bioprocess and Manufacturing Validation. Pharma Tech. 2022;44:31–36. https://www.pharmtech.com/view/considerations-for-monoclonal-antibody-bioprocess-and-manufacturing-validation.
  • Reinhart D, Damjanovic L, Kaisermayer C, Sommeregger W, Gili A, Gasselhuber B, Castan A, Mayrhofer P, Grunwald-Gruber C, Kunert R. Bioprocessing of Recombinant CHO-K1, CHO-DG44, and CHO-S: cHO Expression Hosts Favor Either mAb Production or Biomass Synthesis. Biotechnol J. 2019;14:e1700686. doi:10.1002/biot.201700686. PMID: 29701329.
  • Schmieder V, Fieder J, Drerup R, Gutierrez EA, Guelch C, Stolzenberger J, Stumbaum M, Mueller VS, Higel F, Bergbauer M, et al. Towards maximum acceleration of monoclonal antibody development: leveraging transposase-mediated cell line generation to enable GMP manufacturing within 3 months using a stable pool. J Biotechnol. 2022;349:53–64. PMID: 35341894. doi:10.1016/j.jbiotec.2022.03.010.
  • Wang Y, Qiu H, Minshull J, Tam W, Hu X, Mieczkowski C, Zheng W, Chu C, Liu W, Boldog F, et al. An innovative platform to improve asymmetric bispecific antibody assembly, purity, and expression level in stable pool and cell line development. Biochem Eng J. pp.188. 2022. doi:10.1016/j.bej.2022.108683
  • Hunter M, Yuan P, Vavilala D, Fox M. Optimization of Protein Expression in Mammalian Cells. Curr Protoc Protein Sci. 2019;95:e77. doi:10.1002/cpps.77. PMID: 30265450.
  • Mimura Y, Katoh T, Saldova R, O’flaherty R, Izumi T, Mimura-Kimura Y, Utsunomiya T, Mizukami Y, Yamamoto K, Matsumoto T, et al. Glycosylation engineering of therapeutic IgG antibodies: challenges for the safety, functionality and efficacy. Protein Cell. 2018;9:47–62. PMID: 28597152. doi:10.1007/s13238-017-0433-3.
  • Aldington S, Bonnerjea J. Scale-up of monoclonal antibody purification processes. J Chromatogr B Analyt Technol Biomed Life Sci. 2007;848:64–78. doi:10.1016/j.jchromb.2006.11.032. PMID: 17224311.
  • Jin W, Xing Z, Song Y, Huang C, Xu X, Ghose S, Li ZJ. Protein aggregation and mitigation strategy in low pH viral inactivation for monoclonal antibody purification. MAbs. 2019;11:1479–91. doi:10.1080/19420862.2019.1658493. PMID: 31441367.
  • Feroz H, Chennamsetty N, Byers S, Holstein M, Li ZJ, Ghose S. Assessing detergent-mediated virus inactivation, protein stability, and impurity clearance in biologics downstream processes. Biotechnol Bioeng. 2022;119:1091–104. doi:10.1002/bit.28034. PMID: 35023152.
  • Low D, O’leary R, Pujar NS. Future of antibody purification. J Chromatogr B Analyt Technol Biomed Life Sci. 2007;848:48–63. doi:10.1016/j.jchromb.2006.10.033. PMID: 17134947.
  • Kelley B. Very large scale monoclonal antibody purification: the case for conventional unit operations. Biotechnol Prog. 2007;23:995–1008. doi:10.1021/bp070117s. PMID: 17887772.
  • Teeters M, Bezila D, Benner T, Alfonso P, Alred P. Predicting diafiltration solution compositions for final ultrafiltration/diafiltration steps of monoclonal antibodies. Biotechnol Bioeng. 2011;108:1338–46. doi:10.1002/bit.23067. PMID: 21328314.
  • Lolas A, Hughes P, Suvarna K, Chi B. CMC Microbiology Review of Biologics License Applications and Pre-License/Pre-Approval Inspections: therapeutic Biological Proteins. American Pharma Rev. 2010. https://www.americanpharmaceuticalreview.com/Featured-Articles/117310-CMC-Microbiology-Review-of-Biologics-License-Applications-and-Pre-License-Pre-Approval-Inspections-Therapeutic-Biological-Proteins/
  • Ausserwöger H, Schneider MM, Herling TW, Arosio P, Invernizzi G, Knowles TPJ, Lorenzen N. Non-specificity as the sticky problem in therapeutic antibody development. Nat Rev Chem. 2022;6:844–61. doi:10.1038/s41570-022-00438-x.
  • Alam ME, Slaney TR, Wu L, Das TK, Kar S, Barnett GV, Leone A, Tessier PM. Unique Impacts of Methionine Oxidation, Tryptophan Oxidation, and Asparagine Deamidation on Antibody Stability and Aggregation. J Pharm Sci. 2020;109:656–69. doi:10.1016/j.xphs.2019.10.051. PMID: 31678251.
  • Li W, Prabakaran P, Chen W, Zhu Z, Feng Y, Dimitrov DS. Antibody Aggregation: insights from Sequence and Structure. Antibodies (Basel). 2016;5 PMID: 31558000. doi:10.3390/antib5030019.
  • Chi EY, Krishnan S, Randolph TW, Carpenter JF. Physical stability of proteins in aqueous solution: mechanism and driving forces in nonnative protein aggregation. Pharm Res. 2003;20:1325–36. doi:10.1023/a:1025771421906. PMID: 14567625.
  • Brummitt RK, Nesta DP, Chang L, Chase SF, Laue TM, Roberts CJ. Nonnative aggregation of an IgG1 antibody in acidic conditions: part 1. Unfolding, colloidal interactions, and formation of high-molecular-weight aggregates. J Pharm Sci. 2011;100:2087–103. doi:10.1002/jps.22448. PMID: 21213308.
  • Kim N, Remmele RL Jr., Liu D, Vi R, Ej F, Cj R. Aggregation of anti-streptavidin immunoglobulin gamma-1 involves Fab unfolding and competing growth pathways mediated by pH and salt concentration. Biophys Chem. 2013;172:26–36. doi:10.1016/j.bpc.2012.12.004. PMID: 23334430.
  • Mahler HC, Friess W, Grauschopf U, Kiese S. Protein aggregation: pathways, induction factors and analysis. J Pharm Sci. 2009;98:2909–34. doi:10.1002/jps.21566. PMID: 18823031.
  • Knight MJ, Floret L, Patel N, O’hara J, Rodriguez E. The impact of forced degradation conditions on mAb dimer formation and subsequent influence on aggregation propensity. MAbs. 2022;14:2127172. doi:10.1080/19420862.2022.2127172. PMID: 36198003.
  • Schon A, Freire E. Reversibility and irreversibility in the temperature denaturation of monoclonal antibodies. Anal Biochem. 2021;626:114240. doi:10.1016/j.ab.2021.114240. PMID: 33964250.
  • Sahin E, Grillo AO, Perkins MD, Roberts CJ. Comparative effects of pH and ionic strength on protein-protein interactions, unfolding, and aggregation for IgG1 antibodies. J Pharm Sci. 2010;99:4830–48. doi:10.1002/jps.22198. PMID: 20821389.
  • Bauer J, Mathias S, Kube S, Otte K, Garidel P, Gamer M, Blech M, Fischer S, Karow-Zwick AR. Rational optimization of a monoclonal antibody improves the aggregation propensity and enhances the CMC properties along the entire pharmaceutical process chain. MAbs. 2020;12:1787121. doi:10.1080/19420862.2020.1787121. PMID: 32658605.
  • Haverick M, Mengisen S, Shameem M, Ambrogelly A. Separation of mAbs molecular variants by analytical hydrophobic interaction chromatography HPLC: overview and applications. MAbs. 2014;6:852–58. doi:10.4161/mabs.28693. PMID: 24751784.
  • Demeule B, Messick S, Shire SJ, Liu J. Characterization of particles in protein solutions: reaching the limits of current technologies. Aaps J. 2010;12:708–15. doi:10.1208/s12248-010-9233-x. PMID: 20953747.
  • Wakankar AA, Borchardt RT, Eigenbrot C, Shia S, Wang YJ, Shire SJ, Liu JL. Aspartate Isomerization in the Complementarity-Determining Regions of Two Closely Related Monoclonal Antibodies. Biochemistry. 2007;46:1534–44. doi:10.1021/bi061500t.
  • Dillon TM, Bondarenko PV, Speed Ricci M. Development of an analytical reversed-phase high-performance liquid chromatography-electrospray ionization mass spectrometry method for characterization of recombinant antibodies. J Chromatogr A. 2004;1053:299–305. doi:10.1016/S0021-9673(04)01410-4. PMID: 15543996.
  • Jefferis R. Glycosylation of recombinant antibody therapeutics. Biotechnol Prog. 2005;21:11–16. doi:10.1021/bp040016j. PMID: 15903235.
  • Grassi L, Cabrele C. Susceptibility of protein therapeutics to spontaneous chemical modifications by oxidation, cyclization, and elimination reactions. Amino Acids. 2019;51:1409–31. doi:10.1007/s00726-019-02787-2. PMID: 31576455.
  • Zeunik R, Ryuzoji AF, Peariso A, Wang X, Lannan M, Spindler LJ, Knierman M, Copeland V, Patel C, Wen Y. Investigation of Immune Responses to Oxidation, Deamidation, and Isomerization in Therapeutic Antibodies using Preclinical Immunogenicity Risk Assessment Assays. J Pharm Sci. 2022;111:2217–29. doi:10.1016/j.xphs.2022.05.005. PMID: 35577116.
  • Wang W, Vlasak J, Li Y, Pristatsky P, Fang Y, Pittman T, Roman J, Wang Y, Prueksaritanont T, Ionescu R. Impact of methionine oxidation in human IgG1 Fc on serum half-life of monoclonal antibodies. Mol Immunol. 2011;48:860–66. doi:10.1016/j.molimm.2010.12.009. PMID: 21256596.
  • Laue TM, Shire SJ. The Molecular Interaction Process. J Pharm Sci. 2020;109:154–60. doi:10.1016/j.xphs.2019.10.045. PMID: 31676268.
  • Liu L, Randolph TW, Carpenter JF. Particles shed from syringe filters and their effects on agitation-induced protein aggregation. J Pharm Sci. 2012;101:2952–59. doi:10.1002/jps.23225. PMID: 22674153.
  • Liu J, Yadav S, Andya J, Demeule B, Shire SJ. Analytical Ultracentrifugation and Its Role in Development and Research of Therapeutical Proteins. Methods Enzymol. 2015;562:441–76. doi:10.1016/bs.mie.2015.04.008. PMID: 26412663.
  • Shire SJ. The molecular basis of high viscosity of monoclonal antibodies (mAbs) at high concentration. Monoclonal Antibodies. Cambridge, UK: Woodhead Publishing; 2015. p. 163–192. doi:10.1016/C2014-0-04095-6.
  • Liu J, Nguyen MD, Andya JD, Shire SJ. Reversible self-association increases the viscosity of a concentrated monoclonal antibody in aqueous solution. J Pharm Sci. 2005;94:1928–40. doi:10.1002/jps.20347. PMID: 16052543.
  • Bethea D, Wu SJ, Luo J, Hyun L, Lacy ER, Teplyakov A, Jacobs SA, O’neil KT, Gilliland GL, Feng Y. Mechanisms of self-association of a human monoclonal antibody CNTO607. Protein Eng Des Sel. 2012;25:531–37. doi:10.1093/protein/gzs047. PMID: 22915597.
  • Salinas BA, Sathish HA, Bishop SM, Harn N, Carpenter JF, Randolph TW. Understanding and modulating opalescence and viscosity in a monoclonal antibody formulation. J Pharm Sci. 2010;99:82–93. doi:10.1002/jps.21797. PMID: 19475558.
  • Casaz P, Boucher E, Wollacott R, Pierce BG, Rivera R, Sedic M, Ozturk S, Thomas WD Jr., Wang Y. Resolving self-association of a therapeutic antibody by formulation optimization and molecular approaches. MAbs. 2014;6:1533–39. doi:10.4161/19420862.2014.975658. PMID: 25484044.
  • Dobson CL, Devine PW, Phillips JJ, Higazi DR, Lloyd C, Popovic B, Arnold J, Buchanan A, Lewis A, Goodman J, et al. Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo. Sci Rep. 2016;6:38644. PMID: 27995962. doi:10.1038/srep38644.
  • Schrag JD, Picard ME, Gaudreault F, Gagnon LP, Baardsnes J, Manenda MS, Sheff J, Deprez C, Baptista C, Hogues H, et al. Binding symmetry and surface flexibility mediate antibody self-association. MAbs. 2019;11:1300–18. PMID: 31318308. doi:10.1080/19420862.2019.1632114.
  • Nishi H, Miyajima M, Wakiyama N, Kubota K, Hasegawa J, Uchiyama S, Fukui K. Fc domain mediated self-association of an IgG1 monoclonal antibody under a low ionic strength condition. J Biosci Bioeng. 2011;112:326–32. doi:10.1016/j.jbiosc.2011.06.017. PMID: 21783411.
  • Scherer TM, Liu J, Shire SJ, Minton AP. Intermolecular interactions of IgG1 monoclonal antibodies at high concentrations characterized by light scattering. J Phys Chem B. 2010;114:12948–57. doi:10.1021/jp1028646. PMID: 20849134.
  • Wang W, Ignatius AA, Thakkar SV. Impact of residual impurities and contaminants on protein stability. J Pharm Sci. 2014;103:1315–30. doi:10.1002/jps.23931. PMID: 24623189.
  • Bee JS, Chiu D, Sawicki S, Stevenson JL, Chatterjee K, Freund E, Carpenter JF, Randolph TW. Monoclonal antibody interactions with micro- and nanoparticles: adsorption, aggregation, and accelerated stress studies. J Pharm Sci. 2009;98:3218–38. doi:10.1002/jps.21768. PMID: 19492408.
  • Huang M, Horwitz TS, Zweiben C, Singh SK. Impact of extractables/leachables from filters on stability of protein formulations. J Pharm Sci. 2011;100:4617–30. doi:10.1002/jps.22670. PMID: 21695696.
  • Bee JS, Davis M, Freund E, Carpenter JF, Randolph TW. Aggregation of a monoclonal antibody induced by adsorption to stainless steel. Biotechnol Bioeng. 2010;105:121–29. doi:10.1002/bit.22525. PMID: 19725039.
  • Brusotti G, Calleri E, Colombo R, Massolini G, Rinaldi F, Temporini C. Advances on Size Exclusion Chromatography and Applications on the Analysis of Protein Biopharmaceuticals and Protein Aggregates: a Mini Review. Chromatographia. 2017;81:3–23. doi:10.1007/s10337-017-3380-5.
  • Khan TA, Mahler HC, Kishore RS. Key interactions of surfactants in therapeutic protein formulations: a review. Eur J Pharm Biopharm. 2015;97:60–67. doi:10.1016/j.ejpb.2015.09.016. PMID: 26435336.
  • Roy I, Patel A, Kumar V, Nanda T, Assenberg R, Wuchner K, Amin K. Polysorbate Degradation and Particle Formation in a High Concentration mAb: formulation Strategies to Minimize Effect of Enzymatic Polysorbate Degradation. J Pharm Sci. 2021;110:3313–23. doi:10.1016/j.xphs.2021.05.012. PMID: 34077768.
  • Molden R, Hu M, Yen ES, Saggese D, Reilly J, Mattila J, Qiu H, Chen G, Bak H, Li N. Host cell protein profiling of commercial therapeutic protein drugs as a benchmark for monoclonal antibody-based therapeutic protein development. MAbs. 2021;13:1955811. doi:10.1080/19420862.2021.1955811. PMID: 34365906.
  • Magalhaes PO, Lopes AM, Mazzola PG, Rangel-Yagui C, Penna TC, Pessoa A Jr. Methods of endotoxin removal from biological preparations: a review. J Pharm Pharm Sci. 2007;10:388–404. PMID: 17727802.
  • Basu P, Krishnan S, Thirumangalathu R, Randolph TW, Carpenter JF. IgG1 aggregation and particle formation induced by silicone-water interfaces on siliconized borosilicate glass beads: a model for siliconized primary containers. J Pharm Sci. 2013;102:852–65. doi:10.1002/jps.23434. PMID: 23280943.
  • Thirumangalathu R, Krishnan S, Ricci MS, Brems DN, Randolph TW, Carpenter JF. Silicone oil- and agitation-induced aggregation of a monoclonal antibody in aqueous solution. J Pharm Sci. 2009;98:3167–81. doi:10.1002/jps.21719. PMID: 19360857.
  • Hollowell P, Li Z, Hu X, Ruane S, Kalonia C, Cf VDW, Lu JR. Recent Advances in Studying Interfacial Adsorption of Bioengineered Monoclonal Antibodies. Molecules. 2020;25 PMID: 32353995. doi:10.3390/molecules25092047.
  • Datta-Mannan A, Thangaraju A, Leung D, Tang Y, Witcher DR, Lu J, Wroblewski VJ. Balancing charge in the complementarity-determining regions of humanized mAbs without affecting pI reduces non-specific binding and improves the pharmacokinetics. MAbs. 2015;7:483–93. doi:10.1080/19420862.2015.1016696. PMID: 25695748.
  • Hotzel I, Theil FP, Bernstein LJ, Prabhu S, Deng R, Quintana L, Lutman J, Sibia R, Chan P, Bumbaca D, et al. A strategy for risk mitigation of antibodies with fast clearance. MAbs. 2012;4:753–60. PMID: 23778268. doi:10.4161/mabs.22189.
  • Xu Y, Roach W, Sun T, Jain T, Prinz B, Yu TY, Torrey J, Thomas J, Bobrowicz P, Vasquez M, et al. Addressing polyspecificity of antibodies selected from an in vitro yeast presentation system: a FACS-based, high-throughput selection and analytical tool. Protein Eng Des Sel. 2013;26:663–70. PMID: 24046438. doi:10.1093/protein/gzt047.
  • Kraft TE, Richter WF, Emrich T, Knaupp A, Schuster M, Wolfert A, Kettenberger H. Heparin chromatography as an in vitro predictor for antibody clearance rate through pinocytosis. MAbs. 2020;12:1683432. doi:10.1080/19420862.2019.1683432. PMID: 31769731.
  • Hu S, Datta-Mannan A, D’argenio DZ. Physiologically Based Modeling to Predict Monoclonal Antibody Pharmacokinetics in Humans from in vitro Physiochemical Properties. MAbs. 2022;14:2056944. doi:10.1080/19420862.2022.2056944. PMID: 35491902.
  • Jacobs SA, Wu SJ, Feng Y, Bethea D, O’neil KT. Cross-interaction chromatography: a rapid method to identify highly soluble monoclonal antibody candidates. Pharm Res. 2010;27:65–71. doi:10.1007/s11095-009-0007-z. PMID: 19911257.
  • Kohli N, Jain N, Geddie ML, Razlog M, Xu L, Lugovskoy AA. A novel screening method to assess developability of antibody-like molecules. MAbs. 2015;7:752–58. doi:10.1080/19420862.2015.1048410. PMID: 25961854.
  • Kuroda D, Tsumoto K. Engineering Stability, Viscosity, and Immunogenicity of Antibodies by Computational Design. J Pharm Sci. 2020;109:1631–51. doi:10.1016/j.xphs.2020.01.011. PMID: 31958430.
  • Fernandez-Escamilla AM, Rousseau F, Schymkowitz J, Serrano L. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat Biotechnol. 2004;22:1302–06. doi:10.1038/nbt1012. PMID: 15361882.
  • Chennamsetty N, Voynov V, Kayser V, Helk B, Trout BL. Design of therapeutic proteins with enhanced stability. Proc Natl Acad Sci U S A. 2009;106:11937–42. doi:10.1073/pnas.0904191106. PMID: 19571001.
  • Lauer TM, Agrawal NJ, Chennamsetty N, Egodage K, Helk B, Trout BL. Developability index: a rapid in silico tool for the screening of antibody aggregation propensity. J Pharm Sci. 2012;101:102–15. doi:10.1002/jps.22758. PMID: 21935950.
  • Vatsa S. In silico prediction of post-translational modifications in therapeutic antibodies. MAbs. 2022;14:2023938. doi:10.1080/19420862.2021.2023938. PMID: 35040751.
  • Thorsteinson N, Gunn JR, Kelly K, Long W, Labute P. Structure-based charge calculations for predicting isoelectric point, viscosity, clearance, and profiling antibody therapeutics. MAbs. 2021;13:1981805. doi:10.1080/19420862.2021.1981805. PMID: 34632944.
  • Agrawal NJ, Helk B, Kumar S, Mody N, Sathish HA, Samra HS, Buck PM, Li L, Trout BL. Computational tool for the early screening of monoclonal antibodies for their viscosities. MAbs. 2016;8:43–48. doi:10.1080/19420862.2015.1099773. PMID: 26399600.
  • Tomar DS, Li L, Broulidakis MP, Luksha NG, Burns CT, Singh SK, Kumar S. In-silico prediction of concentration-dependent viscosity curves for monoclonal antibody solutions. MAbs. 2017;9:476–89. doi:10.1080/19420862.2017.1285479. PMID: 28125318.
  • Sharma VK, Patapoff TW, Kabakoff B, Pai S, Hilario E, Zhang B, Li C, Borisov O, Kelley RF, Chorny I, et al. In silico selection of therapeutic antibodies for development: viscosity, clearance, and chemical stability. Proc Natl Acad Sci U S A. 2014;111:18601–06. PMID: 25512516. doi:10.1073/pnas.1421779112.
  • Raybould MIJ, Marks C, Krawczyk K, Taddese B, Nowak J, Lewis AP, Bujotzek A, Shi J, Deane CM. Five computational developability guidelines for therapeutic antibody profiling. Proc Natl Acad Sci U S A. 2019;116:4025–30. doi:10.1073/pnas.1810576116. PMID: 30765520.
  • Hebditch M, Warwicker J. Charge and hydrophobicity are key features in sequence-trained machine learning models for predicting the biophysical properties of clinical-stage antibodies. PeerJ. 2019;7:e8199. PMID: 31976163. doi:10.7717/peerj.8199.
  • Dunbar J, Krawczyk K, Leem J, Marks C, Nowak J, Regep C, Georges G, Kelm S, Popovic B, Deane CM. SAbPred: a structure-based antibody prediction server. Nucleic Acids Res. 2016;44:W474–478. doi:10.1093/nar/gkw361. PMID: 27131379.
  • Chen X, Dougherty T, Hong C, Schibler R, Zhao YC, Sadeghi R, Matasci N, Wu Y-C, Kerman IPredicting Antibody Developability from Sequence using Machine LearningbioRxiv202010.1101/2020.06.18.159798
  • Wilman W, Wrobel S, Bielska W, Deszynski P, Dudzic P, Jaszczyszyn I, Kaniewski J, Mlokosiewicz J, Rouyan A, Satlawa T, et al. Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery. Brief Bioinform. 2022;23: PMID: 35830864. doi:10.1093/bib/bbac267.
  • Akbar R, Bashour H, Rawat P, Robert PA, Smorodina E, Cotet TS, Flem-Karlsen K, Frank R, Mehta BB, Vu MH, et al. Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies. MAbs. 2022;14:2008790. PMID: 35293269. doi:10.1080/19420862.2021.2008790.
  • Makowski EK, Kinnunen PC, Huang J, Wu L, Smith MD, Wang T, Desai AA, Streu CN, Zhang Y, Zupancic JM, et al. Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space. Nat Commun. 2022;13:3788. PMID: 35778381. doi:10.1038/s41467-022-31457-3.
  • Jia L, Sun Y, de Brevern AG. Protein asparagine deamidation prediction based on structures with machine learning methods. PLoS One. 2017;12:e0181347. PMID: 28732052. doi:10.1371/journal.pone.0181347.
  • Sankar K, Hoi KH, Yin Y, Ramachandran P, Andersen N, Hilderbrand A, McDonald P, Spiess C, Zhang Q. Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method. MAbs. 2018;10:1281–90. doi:10.1080/19420862.2018.1518887. PMID: 30252602.
  • Lai PK, Gallegos A, Mody N, Sathish HA, Trout BL. Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics. MAbs. 2022;14:2026208. doi:10.1080/19420862.2022.2026208. PMID: 35075980.
  • Narayanan H, Dingfelder F, Butte A, Lorenzen N, Sokolov M, Arosio P. Machine Learning for Biologics: opportunities for Protein Engineering, Developability, and Formulation. Trends Pharmacol Sci. 2021;42:151–65. doi:10.1016/j.tips.2020.12.004. PMID: 33500170.
  • Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, Tunyasuvunakool K, Bates R, Zidek A, Potapenko A, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583–89. PMID: 34265844. doi:10.1038/s41586-021-03819-2.
  • Bryant P, Pozzati G, Elofsson A. Improved prediction of protein-protein interactions using AlphaFold2. Nat Commun. 2022;13:1265. doi:10.1038/s41467-022-28865-w. PMID: 35273146.
  • Abanades B, Georges G, Bujotzek A, Deane CM, Xu J. Ablooper: fast accurate antibody CDR loop structure prediction with accuracy estimation. Bioinformatics. 2022;38:1877–80. PMID: 35099535. doi:10.1093/bioinformatics/btac016.