PURPOSE: Early identification of monoclonal antibody candidates whose development, as high concentration (≥100 mg/mL) drug products, could prove challenging, due to high viscosity, can help define strategies for candidate engineering and selection. METHODS: Concentration dependent viscosities of 11 proprietary mAbs were measured. Sequence and structural features of the variable (Fv) regions were analyzed to understand viscosity behavior of the mAbs. Coarse-grained molecular simulations of two problematic mAbs were compared with that of a well behaved mAb. RESULTS: Net charge, ξ-potential and pI of Fv regions were found to correlate with viscosities of highly concentrated antibody solutions. Negative net charges on the Fv regions of two mAbs with poor viscosity behaviors facilitate attractive self-associations, causing them to diffuse slower than a well-behaved mAb with positive net charge on its Fv region. An empirically derived equation that connects aggregation propensity and pI of the Fv region with high concentration viscosity of the whole mAb was developed. CONCLUSIONS: An Fv region-based qualitative screening profile was devised to flag mAb candidates whose development, as high concentration drug products, could prove challenging. This screen can facilitate developability risk assessment and mitigation strategies for antibody based therapeutics via rapid high throughput material-free screening.
PURPOSE: Early identification of monoclonal antibody candidates whose development, as high concentration (≥100 mg/mL) drug products, could prove challenging, due to high viscosity, can help define strategies for candidate engineering and selection. METHODS: Concentration dependent viscosities of 11 proprietary mAbs were measured. Sequence and structural features of the variable (Fv) regions were analyzed to understand viscosity behavior of the mAbs. Coarse-grained molecular simulations of two problematic mAbs were compared with that of a well behaved mAb. RESULTS: Net charge, ξ-potential and pI of Fv regions were found to correlate with viscosities of highly concentrated antibody solutions. Negative net charges on the Fv regions of two mAbs with poor viscosity behaviors facilitate attractive self-associations, causing them to diffuse slower than a well-behaved mAb with positive net charge on its Fv region. An empirically derived equation that connects aggregation propensity and pI of the Fv region with high concentration viscosity of the whole mAb was developed. CONCLUSIONS: An Fv region-based qualitative screening profile was devised to flag mAb candidates whose development, as high concentration drug products, could prove challenging. This screen can facilitate developability risk assessment and mitigation strategies for antibody based therapeutics via rapid high throughput material-free screening.
Authors: H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne Journal: Nucleic Acids Res Date: 2000-01-01 Impact factor: 16.971
Authors: Jan Jezek; Martin Rides; Barry Derham; Jonathan Moore; Elenora Cerasoli; Robert Simler; Bernardo Perez-Ramirez Journal: Adv Drug Deliv Rev Date: 2011-10 Impact factor: 15.470
Authors: Feng He; Christopher E Woods; Egor Trilisky; Keith M Bower; Jennifer R Litowski; Bruce A Kerwin; Gerald W Becker; Linda O Narhi; Vladimir I Razinkov Journal: J Pharm Sci Date: 2010-11-02 Impact factor: 3.534
Authors: Martin S Neergaard; Devendra S Kalonia; Henrik Parshad; Anders D Nielsen; Eva H Møller; Marco van de Weert Journal: Eur J Pharm Sci Date: 2013-04-26 Impact factor: 4.384
Authors: Neeraj J Agrawal; Bernhard Helk; Sandeep Kumar; Neil Mody; Hasige A Sathish; Hardeep S Samra; Patrick M Buck; Li Li; Bernhardt L Trout Journal: MAbs Date: 2015-09-23 Impact factor: 5.857
Authors: Vikas K Sharma; Thomas W Patapoff; Bruce Kabakoff; Satyan Pai; Eric Hilario; Boyan Zhang; Charlene Li; Oleg Borisov; Robert F Kelley; Ilya Chorny; Joe Z Zhou; Ken A Dill; Trevor E Swartz Journal: Proc Natl Acad Sci U S A Date: 2014-12-15 Impact factor: 11.205
Authors: Pilarin Nichols; Li Li; Sandeep Kumar; Patrick M Buck; Satish K Singh; Sumit Goswami; Bryan Balthazor; Tami R Conley; David Sek; Martin J Allen Journal: MAbs Date: 2015 Impact factor: 5.857
Authors: Yingda Xu; Dongdong Wang; Bruce Mason; Tony Rossomando; Ning Li; Dingjiang Liu; Jason K Cheung; Wei Xu; Smita Raghava; Amit Katiyar; Christine Nowak; Tao Xiang; Diane D Dong; Joanne Sun; Alain Beck; Hongcheng Liu Journal: MAbs Date: 2018-12-17 Impact factor: 5.857
Authors: Adriana-Michelle Wolf Pérez; Pietro Sormanni; Jonathan Sonne Andersen; Laila Ismail Sakhnini; Ileana Rodriguez-Leon; Jais Rose Bjelke; Annette Juhl Gajhede; Leonardo De Maria; Daniel E Otzen; Michele Vendruscolo; Nikolai Lorenzen Journal: MAbs Date: 2019-01-18 Impact factor: 5.857
Authors: Dheeraj S Tomar; Li Li; Matthew P Broulidakis; Nicholas G Luksha; Christopher T Burns; Satish K Singh; Sandeep Kumar Journal: MAbs Date: 2017-01-26 Impact factor: 5.857