Models to inform neutralizing antibody therapy strategies during pandemics: the case of SARS-CoV-2

Author:

Guttieres Donovan1,Sinskey Anthony J12,Springs Stacy L1

Affiliation:

1. Center for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

2. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Abstract

Abstract Background Neutralizing antibodies (nAbs) against SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) can play an important role in reducing impacts of the COVID-19 pandemic, complementing ongoing public health efforts such as diagnostics and vaccination. Rapidly designing, manufacturing and distributing nAbs requires significant planning across the product value chain and an understanding of the opportunities, challenges and risks throughout. Methods A systems framework comprised of four critical components is presented to aid in developing effective end-to-end nAbs strategies in the context of a pandemic: (1) product design and optimization, (2) epidemiology, (3) demand and (4) supply. Quantitative models are used to estimate product demand using available epidemiological data, simulate biomanufacturing operations from typical bioprocess parameters and calculate antibody production costs to meet clinical needs under various realistic scenarios. Results In a US-based case study during the 9-month period from March 15 to December 15, 2020, the projected number of SARS-CoV-2 infections was 15.73 million. The estimated product volume needed to meet therapeutic demand for the maximum number of clinically eligible patients ranged between 6.3 and 31.5 tons for 0.5 and 2.5 g dose sizes, respectively. The relative production scale and cost needed to meet demand are calculated for different centralized and distributed manufacturing scenarios. Conclusions Meeting demand for anti-SARS-CoV-2 nAbs requires significant manufacturing capacity and planning for appropriate administration in clinical settings. MIT Center for Biomedical Innovation’s data-driven tools presented can help inform time-critical decisions by providing insight into important operational and policy considerations for making nAbs broadly accessible, while considering time and resource constraints.

Funder

MIT-IBM Watson AI Lab

Publisher

Oxford University Press (OUP)

Subject

Immunology,Immunology and Allergy

Reference70 articles.

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