Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

Author:

Mock Marissa1ORCID,Jacobitz Alex W.2,Langmead Christopher James1,Sudom Athena3,Yoo Daniel1,Humphreys Sara C.4,Alday Mai1,Alekseychyk Larysa2,Angell Nicolas2,Bi Vivian1,Catterall Hannah1,Chen Chen-Chun1,Chou Hui-Ting3,Conner Kip P.4,Cook Kevin D.4,Correia Ana R.1,Dykstra Andrew2,Ghimire-Rijal Sudipa5,Graham Kevin1,Grandsard Peter1,Huh Joon2,Hui John O.1,Jain Mani1,Jann Victoria1,Jia Lei1,Johnstone Sheree3,Khanal Neelam2,Kolvenbach Carl1,Narhi Linda2,Padaki Rupa2,Pelegri-O’Day Emma M.1,Qi Wei2,Razinkov Vladimir2,Rice Austin J.1,Smith Richard4,Spahr Christopher1,Stevens Jennitte2,Sun Yax1,Thomas Veena A.4,van Driesche Sarah1,Vernon Robert1,Wagner Victoria1,Walker Kenneth W.1,Wei Yangjie2,Winters Dwight1,Yang Melissa1,Campuzano Iain D. G.1

Affiliation:

1. Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA

2. Process Development, Amgen Operations, Thousand Oaks, CA, USA

3. Structural Biology, Amgen Research, South San Francisco, CA, USA

4. Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA

5. Structural Biology, Amgen Research, Thousand Oaks, CA, USA

Funder

no funding

Publisher

Informa UK Limited

Subject

Immunology,Immunology and Allergy

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