Yunda Huang1,2, Yuanyuan Zhang1, Robert Bailer3, Nicole Grunenberg1, Lindsay N Carpp1, Kelly Seaton4, Kenneth H Mayer5,6, Julie Ledgerwood3, Lawrence Corey1, John Mascola3, David Montefiori4, Peter B Gilbert1,7. 1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA. 2. Department of Global Health, University of Washington, Seattle, WA. 3. Vaccine Research Center, National Institute of Allergy and Infectious Diseases, Bethesda, MD. 4. Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC. 5. The Fenway Institute, Fenway Health, Boston, MA. 6. Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; and. 7. Department of Biostatistics, University of Washington, Seattle, WA.
Abstract
BACKGROUND: VRC01 is a human IgG1 broadly neutralizing antibody (bnAb) that binds to the HIV-1 envelope glycoprotein. It is being evaluated in two ongoing Phase 2b trials, the first efficacy assessment of a passively-administered bnAb for HIV-1 prevention. HVTN 104 was a phase 1 trial of VRC01. SETTING: We measured serum concentrations and serum neutralization of VRC01 in 1079 longitudinal samples collected after passive administration of VRC01 in 84 HVTN 104 participants. As assays for measuring VRC01 serum neutralization titers are resource-intensive, we investigated approaches to predicting such titers. METHODS: Serum concentration was measured using an anti-idiotypic ELISA assay. Serum neutralization ID50 titers and in vitro neutralization potency IC50 of the VRC01 clinical lot were measured against Env-pseudoviruses. Three approaches were used to predict serum neutralization ID50 titers based on (1) observed serum concentration divided by IC50, (2) pharmacokinetics model-predicted serum concentration divided by IC50, and (3) joint modeling of the longitudinal serum concentrations and ID50 titers. RESULTS: All 3 approaches yielded satisfactory prediction of neutralization titers against viruses of varied sensitivities; the median fold differences (FDs) of observed-over-predicted ID50 titers were between 0.95 and 1.37. Approach 3 generally performed the best with fold differences between 0.95 and 0.99 and <82% mean squared prediction error relative to approach 1. Similar results were obtained for ID80 titers. CONCLUSION: VRC01 serum neutralization could be accurately predicted, especially when using pharmacokinetics models. The proposed prediction approaches could potentially save significant resources for the characterization of serum neutralization of VRC01, including for other bnAbs and bnAb combinations.
BACKGROUND: VRC01 is a human IgG1 broadly neutralizing antibody (bnAb) that binds to the HIV-1 envelope glycoprotein. It is being evaluated in two ongoing Phase 2b trials, the first efficacy assessment of a passively-administered bnAb for HIV-1 prevention. HVTN 104 was a phase 1 trial of VRC01. SETTING: We measured serum concentrations and serum neutralization of VRC01 in 1079 longitudinal samples collected after passive administration of VRC01 in 84 HVTN 104 participants. As assays for measuring VRC01 serum neutralization titers are resource-intensive, we investigated approaches to predicting such titers. METHODS: Serum concentration was measured using an anti-idiotypic ELISA assay. Serum neutralization ID50 titers and in vitro neutralization potency IC50 of the VRC01 clinical lot were measured against Env-pseudoviruses. Three approaches were used to predict serum neutralization ID50 titers based on (1) observed serum concentration divided by IC50, (2) pharmacokinetics model-predicted serum concentration divided by IC50, and (3) joint modeling of the longitudinal serum concentrations and ID50 titers. RESULTS: All 3 approaches yielded satisfactory prediction of neutralization titers against viruses of varied sensitivities; the median fold differences (FDs) of observed-over-predicted ID50 titers were between 0.95 and 1.37. Approach 3 generally performed the best with fold differences between 0.95 and 0.99 and <82% mean squared prediction error relative to approach 1. Similar results were obtained for ID80 titers. CONCLUSION: VRC01 serum neutralization could be accurately predicted, especially when using pharmacokinetics models. The proposed prediction approaches could potentially save significant resources for the characterization of serum neutralization of VRC01, including for other bnAbs and bnAb combinations.
Authors: Allan deCamp; Peter Hraber; Robert T Bailer; Michael S Seaman; Christina Ochsenbauer; John Kappes; Raphael Gottardo; Paul Edlefsen; Steve Self; Haili Tang; Kelli Greene; Hongmei Gao; Xiaoju Daniell; Marcella Sarzotti-Kelsoe; Miroslaw K Gorny; Susan Zolla-Pazner; Celia C LaBranche; John R Mascola; Bette T Korber; David C Montefiori Journal: J Virol Date: 2013-12-18 Impact factor: 5.103
Authors: Yunda Huang; Lily Zhang; Julie Ledgerwood; Nicole Grunenberg; Robert Bailer; Abby Isaacs; Kelly Seaton; Kenneth H Mayer; Edmund Capparelli; Larry Corey; Peter B Gilbert Journal: MAbs Date: 2017-04-03 Impact factor: 5.857
Authors: Marcella Sarzotti-Kelsoe; Robert T Bailer; Ellen Turk; Chen-li Lin; Miroslawa Bilska; Kelli M Greene; Hongmei Gao; Christopher A Todd; Daniel A Ozaki; Michael S Seaman; John R Mascola; David C Montefiori Journal: J Immunol Methods Date: 2013-12-01 Impact factor: 2.303
Authors: J E Ledgerwood; E E Coates; G Yamshchikov; J G Saunders; L Holman; M E Enama; A DeZure; R M Lynch; I Gordon; S Plummer; C S Hendel; A Pegu; M Conan-Cibotti; S Sitar; R T Bailer; S Narpala; A McDermott; M Louder; S O'Dell; S Mohan; J P Pandey; R M Schwartz; Z Hu; R A Koup; E Capparelli; J R Mascola; B S Graham Journal: Clin Exp Immunol Date: 2015-09-24 Impact factor: 4.330
Authors: Amarendra Pegu; Bhavesh Borate; Yunda Huang; Matthias G Pauthner; Ann J Hessell; Boris Julg; Nicole A Doria-Rose; Stephen D Schmidt; Lindsay N Carpp; Michelle D Cully; Xuejun Chen; George M Shaw; Dan H Barouch; Nancy L Haigwood; Lawrence Corey; Dennis R Burton; Mario Roederer; Peter B Gilbert; John R Mascola; Ying Huang Journal: Cell Host Microbe Date: 2019-09-11 Impact factor: 21.023
Authors: Kenneth H Mayer; Kelly E Seaton; Yunda Huang; Nicole Grunenberg; Abby Isaacs; Mary Allen; Julie E Ledgerwood; Ian Frank; Magdalena E Sobieszczyk; Lindsey R Baden; Benigno Rodriguez; Hong Van Tieu; Georgia D Tomaras; Aaron Deal; Derrick Goodman; Robert T Bailer; Guido Ferrari; Ryan Jensen; John Hural; Barney S Graham; John R Mascola; Lawrence Corey; David C Montefiori Journal: PLoS Med Date: 2017-11-14 Impact factor: 11.069
Authors: Peter B Gilbert; Michal Juraska; Allan C deCamp; Shelly Karuna; Srilatha Edupuganti; Nyaradzo Mgodi; Deborah J Donnell; Carter Bentley; Nirupama Sista; Philip Andrew; Abby Isaacs; Yunda Huang; Lily Zhang; Edmund Capparelli; Nidhi Kochar; Jing Wang; Susan H Eshleman; Kenneth H Mayer; Craig A Magaret; John Hural; James G Kublin; Glenda Gray; David C Montefiori; Margarita M Gomez; David N Burns; Julie McElrath; Julie Ledgerwood; Barney S Graham; John R Mascola; Myron Cohen; Lawrence Corey Journal: Stat Commun Infect Dis Date: 2017-06-06
Authors: Yunda Huang; Lily Zhang; Amanda Eaton; Nonhlanhla N Mkhize; Lindsay N Carpp; Erika Rudnicki; Allan DeCamp; Michal Juraska; April Randhawa; Adrian McDermott; Julie Ledgerwood; Philip Andrew; Shelly Karuna; Srilatha Edupuganti; Nyaradzo Mgodi; Myron Cohen; Lawrence Corey; John Mascola; Peter B Gilbert; Lynn Morris; David C Montefiori Journal: Hum Vaccin Immunother Date: 2021-07-02 Impact factor: 4.526