First-in-Human Study to Evaluate Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of a Rapidly Developed SARS-CoV-2 Therapeutic Antibody, AOD01, in Healthy Adults.

INTRODUCTION: AOD01 is a novel, fully human immunoglobulin (Ig) G1 neutralizing monoclonal antibody that was developed as a therapeutic against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). This first-in-human study assessed safety, tolerability, pharmacokinetics (PK), and pharmacodynamics of AOD01 in healthy volunteers. METHODS: Intravenous doses of AOD01 were evaluated in escalating cohorts [four single-dose cohorts (2, 5, 10, and 20 mg/kg) and one two-dose cohort (two doses of 20 mg/kg, 24 h apart)]. RESULTS: Twenty-three subjects were randomized to receive AOD01 or a placebo in blinded fashion. A total of 34 treatment-emergent adverse events (TEAEs) were reported; all were mild in severity. Related events (headache and diarrhea) were reported in one subject each. No event of infusion reactions, serious adverse event (SAE), or discontinuation due to AE were reported. The changes in laboratory parameters, vital signs, and electrocardiograms were minimal. Dose-related exposure was seen from doses 2 to 20 mg/kg as confirmed by Cmax and AUC0-tlast. The median Tmax was 1.5-3 h. Clearance was dose independent. Study results revealed long half-lives (163-465 h). Antidrug antibodies (ADA) to AOD01 were not detected among subjects, except in one subject of the two-dose cohort on day 92. Sustained ex vivo neutralization of SARS-CoV-2 was recorded until day 29 with single doses from 2 to 20 mg/kg and until day 43 with two doses of 20 mg/kg. CONCLUSIONS: AOD01 was safe and well tolerated, demonstrated dose-related PK, non-immunogenic status, and sustained ex vivo neutralization of SARS-CoV-2 after single intravenous dose ranging from 2 to 20 mg/kg and two doses of 20 mg/kg and show good potential for treatment of SARS-CoV-2 infection. (Health Sciences Authority identifier number CTA2000119).

IDentif.AI-Omicron: Harnessing an AI-Derived and Disease-Agnostic Platform to Pinpoint Combinatorial Therapies for Clinically Actionable Anti-SARS-CoV-2 Intervention.

Nanomedicine-based and unmodified drug interventions to address COVID-19 have evolved over the course of the pandemic as more information is gleaned and virus variants continue to emerge. For example, some early therapies (e.g., antibodies) have experienced markedly decreased efficacy. Due to a growing concern of future drug resistant variants, current drug development strategies are seeking to find effective drug combinations. In this study, we used IDentif.AI, an artificial intelligence-derived platform, to investigate the drug-drug and drug-dose interaction space of six promising experimental or currently deployed therapies at various concentrations: EIDD-1931, YH-53, nirmatrelvir, AT-511, favipiravir, and auranofin. The drugs were tested in vitro against a live B.1.1.529 (Omicron) virus first in monotherapy and then in 50 strategic combinations designed to interrogate the interaction space of 729 possible combinations. Key findings and interactions were then further explored and validated in an additional experimental round using an expanded concentration range. Overall, we found that few of the tested drugs showed moderate efficacy as monotherapies in the actionable concentration range, but combinatorial drug testing revealed significant dose-dependent drug-drug interactions, specifically between EIDD-1931 and YH-53, as well as nirmatrelvir and YH-53. Checkerboard validation analysis confirmed these synergistic interactions and also identified an interaction between EIDD-1931 and favipiravir in an expanded range. Based on the platform nature of IDentif.AI, these findings may support further explorations of the dose-dependent drug interactions between different drug classes in further pre-clinical and clinical trials as possible combinatorial therapies consisting of unmodified and nanomedicine-enabled drugs, to combat current and future COVID-19 strains and other emerging pathogens.

The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.

IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against COVID-19 by pairing a prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus and Vero E6 assay with a quadratic optimization workflow. A starting pool of 12 candidate drugs developed in collaboration with a community of infectious disease clinicians was first narrowed down to a six-drug pool and then interrogated in 50 combination regimens at three dosing levels per drug, representing 729 possible combinations. IDentif.AI-x revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived, and pinpointed a number of clinically actionable drug interactions, which were further reconfirmed in SARS-CoV-2 variants B.1.351 (Beta) and B.1.617.2 (Delta). IDentif.AI-x prioritized promising drug combinations for clinical translation and can be immediately adjusted and re-executed with a new pool of promising therapies in an actionable path towards rapidly optimizing combination therapy following pandemic emergence.

The Cellular Characterization of SARS-CoV-2 Spike Protein in Virus-Infected Cells Using the Receptor Binding Domain Binding Specific Human Monoclonal Antibodies.

A human monoclonal antibody panel (PD4, PD5, PD7, SC23, and SC29) was isolated from the B cells of convalescent patients and used to examine the S protein in SARS-CoV-2-infected cells. While all five antibodies bound conformational-specific epitopes within SARS-CoV-2 spike (S) protein, only PD5, PD7, and SC23 were able to bind to the receptor binding domain (RBD). Immunofluorescence microscopy was used to examine the S protein RBD in cells infected with the Singapore isolates SARS-CoV-2/0334 and SARS-CoV-2/1302. The RBD-binders exhibited a distinct cytoplasmic staining pattern that was primarily localized within the Golgi complex and was distinct from the diffuse cytoplasmic staining pattern exhibited by the non-RBD-binders (PD4 and SC29). These data indicated that the S protein adopted a conformation in the Golgi complex that enabled the RBD recognition by the RBD-binders. The RBD-binders also recognized the uncleaved S protein, indicating that S protein cleavage was not required for RBD recognition. Electron microscopy indicated high levels of cell-associated virus particles, and multiple cycle virus infection using RBD-binder staining provided evidence for direct cell-to-cell transmission for both isolates. Although similar levels of RBD-binder staining were demonstrated for each isolate, SARS-CoV-2/1302 exhibited slower rates of cell-to-cell transmission. These data suggest that a conformational change in the S protein occurs during its transit through the Golgi complex that enables RBD recognition by the RBD-binders and suggests that these antibodies can be used to monitor S protein RBD formation during the early stages of infection. IMPORTANCE The SARS-CoV-2 spike (S) protein receptor binding domain (RBD) mediates the attachment of SARS-CoV-2 to the host cell. This interaction plays an essential role in initiating virus infection, and the S protein RBD is therefore a focus of therapeutic and vaccine interventions. However, new virus variants have emerged with altered biological properties in the RBD that can potentially negate these interventions. Therefore, an improved understanding of the biological properties of the RBD in virus-infected cells may offer future therapeutic strategies to mitigate SARS- CoV-2 infection. We used physiologically relevant antibodies that were isolated from the B cells of convalescent COVID-19 patients to monitor the RBD in cells infected with SARS-CoV-2 clinical isolates. These immunological reagents specifically recognize the correctly folded RBD and were used to monitor the appearance of the RBD in SARS-CoV-2-infected cells and identified the site where the RBD first appears.

The Fc-mediated effector functions of a potent SARS-CoV-2 neutralizing antibody, SC31, isolated from an early convalescent COVID-19 patient, are essential for the optimal therapeutic efficacy of the antibody.

Although SARS-CoV-2-neutralizing antibodies are promising therapeutics against COVID-19, little is known about their mechanism(s) of action or effective dosing windows. We report the generation and development of SC31, a potent SARS-CoV-2 neutralizing antibody, isolated from a convalescent patient. Antibody-mediated neutralization occurs via an epitope within the receptor-binding domain of the SARS-CoV-2 Spike protein. SC31 exhibited potent anti-SARS-CoV-2 activities in multiple animal models. In SARS-CoV-2 infected K18-human ACE2 transgenic mice, treatment with SC31 greatly reduced viral loads and attenuated pro-inflammatory responses linked to the severity of COVID-19. Importantly, a comparison of the efficacies of SC31 and its Fc-null LALA variant revealed that the optimal therapeutic efficacy of SC31 requires Fc-mediated effector functions that promote IFNγ-driven anti-viral immune responses, in addition to its neutralization ability. A dose-dependent efficacy of SC31 was observed down to 5mg/kg when administered before viral-induced lung inflammatory responses. In addition, antibody-dependent enhancement was not observed even when infected mice were treated with SC31 at sub-therapeutic doses. In SARS-CoV-2-infected hamsters, SC31 treatment significantly prevented weight loss, reduced viral loads, and attenuated the histopathology of the lungs. In rhesus macaques, the therapeutic potential of SC31 was evidenced through the reduction of viral loads in both upper and lower respiratory tracts to undetectable levels. Together, the results of our preclinical studies demonstrated the therapeutic efficacy of SC31 in three different models and its potential as a COVID-19 therapeutic candidate.

IDentif.AI: Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) with digital drug development.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to multiple drug repurposing clinical trials that have yielded largely uncertain outcomes. To overcome this challenge, we used IDentif.AI, a platform that pairs experimental validation with artificial intelligence (AI) and digital drug development to rapidly pinpoint unpredictable drug interactions and optimize infectious disease combination therapy design with clinically relevant dosages. IDentif.AI was paired with a 12-drug candidate therapy set representing over 530,000 drug combinations against the SARS-CoV-2 live virus collected from a patient sample. IDentif.AI pinpointed the optimal combination as remdesivir, ritonavir, and lopinavir, which was experimentally validated to mediate a 6.5-fold enhanced efficacy over remdesivir alone. Additionally, it showed hydroxychloroquine and azithromycin to be relatively ineffective. The study was completed within 2 weeks, with a three-order of magnitude reduction in the number of tests needed. IDentif.AI independently mirrored clinical trial outcomes to date without any data from these trials. The robustness of this digital drug development approach paired with in vitro experimentation and AI-driven optimization suggests that IDentif.AI may be clinically actionable toward current and future outbreaks.