Super LeArner Prediction of NAb Panels (SLAPNAP): a containerized tool for predicting combination monoclonal broadly neutralizing antibody sensitivity | Zendy

Brian D. Williamson | Zendy; Craig A. Magaret | Zendy; Peter B. Gilbert | Zendy; Sohail Nizam | Zendy; Courtney Simmons | Zendy; David Benkeser | Zendy

Open Access

Super LeArner Prediction of NAb Panels (SLAPNAP): a containerized tool for predicting combination monoclonal broadly neutralizing antibody sensitivity

Author(s) -

Brian D. Williamson,

Craig A. Magaret,

Peter B. Gilbert,

Sohail Nizam,

Courtney Simmons,

David Benkeser

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab398

Subject(s) - monoclonal antibody , potency , regimen , monoclonal , antibody , immunology , in vitro , medicine , biology , biochemistry

A single monoclonal broadly neutralizing antibody (bnAb) regimen was recently evaluated in two randomized trials for prevention efficacy against HIV-1 infection. Subsequent trials will evaluate combination bnAb regimens (e.g. cocktails, multi-specific antibodies), which demonstrate higher potency and breadth in vitro compared to single bnAbs. Given the large number of potential regimens, methods for down-selecting these regimens into efficacy trials are of great interest.

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