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During a new pandemic such as COVID-19, there is a need to develop drug treatments as quickly as possible. However, a new disease means that limited information would be available. With paucity of data, the objective was to predict the likely efficacy and required human dose of neutralizing monoclonal antibodies (mAb) for treatment of COVID-19. The use of pharmacokinetic-pharmacodynamic modeling and simulation is presented as the ideal platform to incorporate any available information and identify the efficacious human dose. Methods Candidate selection and effective therapeutic dose were supported by expanding two innovative, open-science initiatives1,2. The first approach used a physiologically-based pharmacokinetic (PBPK) model, incorporating various physicochemical drug properties to predict mAb clearance and tissue distribution. The PBPK model was then used to estimate mAb exposures to maintain concentrations above the IC90 of in vitro neutralization in lung interstitial fluid for up to 4 weeks in 90% of patients. The second approach used a target cell-limited SARS-CoV-2 viral dynamic model developed from literature.3 This method evaluated viral clearance as a function of mAb dose and lung concentration by including: • uninfected target cell population • free virus and subsequent viral replication • free virus elimination (host immune system) • infected target cell death • in vitro neutralization data Results The PBPK modeling approach determined that a clinical dose of 175 - 500 mg was expected to maintain target mAb lung concentrations for over 28 days in 90% of patients. The viral dynamic model predicted a 700 mg dose would achieve maximum viral elimination. Clinical trial results later confirmed the accuracy of model predictions for PK, viral clearance and ultimately the authorized dose of 700 mg bamlanivimab. Conclusions The accelerated selection of bamlanivimab as the first neutralizing mAb drug candidate to enter clinical evaluation and accurate prediction of the maximum therapeutic dose for treatment of COVID-19 in the absence of data from animal model of disease was supported by a pharmacokinetic-pharmacodynamic modeling and simulation framework. References: 1. Jones et al. CPT:PSP 2019; 8(10): 738-47 2. Shah and Betts. MAbs 2013; 5(2): 297-305 3. Kim KS et al. medRxiv; 27 Mar 2020