IntroductionSince the outbreak of the COVID-19 pandemic, extensive efforts including vaccine and drug development have been accentuated to address the emergence of SARS-CoV-2 variants. The rising variants and subvariants made early discoveries in effective treatment strategies less relevant and potent. For instance, multiple therapeutics like Evusheld are no longer effective against current variants and therefore have their emergency use authorizations (EUA), a regulatory mechanism allowing emergency use of medical products, revoked until further notice. Similarly, sotrovimab (STV), a human neutralizing monoclonal antibody (MAB), received EUA in May 2021 and was later granted authorization for COVID-19 treatment in Singapore. However, mutations presented in XBB, a subvariant of Omicron, substantially reduced the potency of STV at the currently approved dose.MethodsTo retain STV as a part of the treatment strategy for COVID-19 infected patients, it is important to carefully design and prioritize drugs that may further enhance the potency of STV when paired in combinations. In this study, IDentif.AI, an artificial intelligence (AI)-derived drug combination optimization platform, was harnessed to rapidly pinpoint STV-based combinations that may substantially improve the efficacy and potency of STV against XBB, which was predominantly spreading worldwide in 2023.ResultsIDentif.AI-pinpointed STV/EIDD-1931 and STV/GS-441524 combinations were able to interact synergistically to enhance efficacy against XBB and importantly, substantially reduce STV's in vitro EC50 (half maximal effective concentration) by up to 7-fold.DiscussionThis optimization platform represents a strategic approach to rapidly repurpose existing or previously failed therapeutics and subsequently restore their efficacy against a disease indication by pairing them with the correct drugs in combinations.

Antimicrobial resistance (AMR) is an emerging threat to global public health. Specifically, Acinetobacter baumannii (A. baumannii), one of the main pathogens driving the rise of nosocomial infections, is a Gram-negative bacillus that displays intrinsic resistance mechanisms and can also develop resistance by acquiring AMR genes from other bacteria. More importantly, it is resistant to nearly 90% of standard of care (SOC) antimicrobial treatments, resulting in unsatisfactory clinical outcomes and a high infection-associated mortality rate of over 30%. Currently, there is a growing challenge to sustainably develop novel antimicrobials in this ever-expanding arms race against AMR. Therefore, a sustainable workflow that properly manages healthcare resources to ultra-rapidly design optimal drug combinations for effective treatment is needed. In this study, the IDentif.AI-AMR platform was harnessed to pinpoint effective regimens against four A. baumannii clinical isolates from a pool of nine US FDA-approved drugs. Notably, IDentif.AI-pinpointed ampicillin-sulbactam/cefiderocol and cefiderocol/polymyxin B/rifampicin combinations were able to achieve 93.89 ± 5.95% and 92.23 ± 11.89% inhibition against the bacteria, respectively, and they may diversify the reservoir of treatment options for the indication. In addition, polymyxin B in combination with rifampicin exhibited broadly applicable efficacy and strong synergy across all tested clinical isolates, representing a potential treatment strategy for A. baumannii. IDentif.AI-pinpointed combinations may potentially serve as alternative treatment strategies for A. baumannii.

Recombinant SARS-CoV-2 S protein expression was examined in Vero cells by imaging using the human monoclonal antibody panel (PD4, PD5, sc23, and sc29). The PD4 and sc29 antibodies recognised conformational specific epitopes in the S2 protein subunit at the Endoplasmic reticulum and Golgi complex. While PD5 and sc23 detected conformationally specific epitopes in the S1 protein subunit at the Golgi complex, only PD5 recognised the receptor binding domain (RBD). A comparison of the staining patterns of PD5 with non-conformationally specific antibodies that recognises the S1 subunit and RBD suggested the PD5 recognised a conformational structure within the S1 protein subunit. Our data suggests the antibody binding epitopes recognised by the human monoclonal antibodies formed at different locations in the secretory pathway during S protein transport, but a conformational change in the S1 protein subunit at the Golgi complex formed antibody binding epitopes that are recognised by virus neutralising antibodies.

Journal of Medical VirologyVolume 95, Issue 9 e29074 LETTER TO THE EDITOR Neutralization escape of emerging subvariants XBB.1.5/1.9.1 and XBB.2.3 from current therapeutic monoclonal antibodies De Hoe Chye, De Hoe Chye DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, SingaporeSearch for more papers by this authorCharmaine W. Y. Chew, Charmaine W. Y. Chew National Centre for Infectious Diseases, Singapore, SingaporeSearch for more papers by this authorHe Ping Yeo, He Ping Yeo National Centre for Infectious Diseases, Singapore, SingaporeSearch for more papers by this authorPaul A. Tambyah, Paul A. Tambyah Department of Medicine, Infectious Diseases Translational Research Program, Division of Infectious Diseases, National University Hospital, National University of Singapore, Singapore, SingaporeSearch for more papers by this authorBarnaby E. Young, Barnaby E. Young National Centre for Infectious Diseases, Singapore, Singapore Tan Tock Seng Hospital, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorGladys G. Y. Tan, Gladys G. Y. Tan DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, SingaporeSearch for more papers by this authorBoon Huan Tan, Boon Huan Tan DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorShawn Vasoo, Shawn Vasoo National Centre for Infectious Diseases, Singapore, Singapore Tan Tock Seng Hospital, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorConrad E. Z. Chan, Corresponding Author Conrad E. Z. Chan [email protected] orcid.org/0000-0001-5730-7095 DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, Singapore National Centre for Infectious Diseases, Singapore, Singapore Correspondence Conrad E. Z. Chan, Infectious Disease Research Laboratory, National Centre for Infectious Diseases, 16 Jalan Tan Tock Seng, Singapore 308442, Singapore. Email: [email protected]Search for more papers by this author De Hoe Chye, De Hoe Chye DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, SingaporeSearch for more papers by this authorCharmaine W. Y. Chew, Charmaine W. Y. Chew National Centre for Infectious Diseases, Singapore, SingaporeSearch for more papers by this authorHe Ping Yeo, He Ping Yeo National Centre for Infectious Diseases, Singapore, SingaporeSearch for more papers by this authorPaul A. Tambyah, Paul A. Tambyah Department of Medicine, Infectious Diseases Translational Research Program, Division of Infectious Diseases, National University Hospital, National University of Singapore, Singapore, SingaporeSearch for more papers by this authorBarnaby E. Young, Barnaby E. Young National Centre for Infectious Diseases, Singapore, Singapore Tan Tock Seng Hospital, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorGladys G. Y. Tan, Gladys G. Y. Tan DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, SingaporeSearch for more papers by this authorBoon Huan Tan, Boon Huan Tan DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorShawn Vasoo, Shawn Vasoo National Centre for Infectious Diseases, Singapore, Singapore Tan Tock Seng Hospital, Singapore, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, SingaporeSearch for more papers by this authorConrad E. Z. Chan, Corresponding Author Conrad E. Z. Chan [email protected] orcid.org/0000-0001-5730-7095 DSO National Laboratories, Defence Medical and Environmental Research Institute, Singapore, Singapore National Centre for Infectious Diseases, Singapore, Singapore Correspondence Conrad E. Z. Chan, Infectious Disease Research Laboratory, National Centre for Infectious Diseases, 16 Jalan Tan Tock Seng, Singapore 308442, Singapore. Email: [email protected]Search for more papers by this author First published: 04 September 2023 https://doi.org/10.1002/jmv.29074Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. REFERENCES 1Gupta A, Gonzalez-Rojas Y, Juarez E, et al. Early treatment for Covid-19 with SARS-CoV-2 neutralizing antibody sotrovimab. N Engl J Med. 2021; 385(21): 1941-1950. 2Levin MJ, Ustianowski A, De Wit S, et al. Intramuscular AZD7442 (tixagevimab-cilgavimab) for prevention of Covid-19. N Engl J Med. 2022; 386(23): 2188-2200. 3Imai M, Ito M, Kiso M, et al. Efficacy of antiviral agents against omicron subvariants BQ.1.1 and XBB. N Engl J Med. 2023; 388(1): 89-91. 4Yamasoba D, Uriu K, Plianchaisuk A, et al. Virological characteristics of the SARS-CoV-2 omicron XBB.1.16 variant. Lancet Infect Dis. 2023; 23(6): 655-656. 5Touret F, Giraud E, Bourret J, et al. Enhanced neutralization escape to therapeutic monoclonal antibodies by SARS-CoV-2 omicron sub-lineages. iScience. 2023; 26(4):106413. 6Chan CEZ, Seah SGK, Chye DH, et al. 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. PLoS One. 2021; 16(6):e0253487. 7Gangavarapu K, Latif AA, Mullen JL, et al. Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations. Nat Methods. 2023; 20(4): 512-522. 8Freed NE, Vlková M, Faisal MB, Silander OK. Rapid and inexpensive whole-genome sequencing of SARS-CoV-2 using 1200 bp tiled amplicons and Oxford nanopore rapid barcoding. Biol Methods Protoc. 2020; 5(1):bpaa014. 9Moya J, Temech M, Parra S, et al. Safety, virology, pharmacokinetics, and clinical experience of high-dose intravenous sotrovimab for the treatment of mild to moderate COVID-19: an open-label clinical trial. Open Forum Infect Dis. 2023; 10(7):ofad344. Volume95, Issue9September 2023e29074 ReferencesRelatedInformation

Serological testing of Singaporeans who received childhood smallpox vaccination found anti-vaccinia IgG binding and neutralizing activity indicating long-term humoral immunity. There was correlation between IgG and neutralizing titers indicating IgG could be used as a surrogate marker for humoral immunity. In 2019, Singapore experienced a case of imported monkeypox. As with smallpox, disease can be prevented through vaccination, which was mandatory for Singaporean infants until 1981. However, the degree of residual immunity in older vaccinated Singaporeans remains unknown. Sera from individuals born 1946-1984 were therefore tested and those born prior to 1981 were found to have higher anti-vaccinia IgG and neutralizing activity titers. This suggests that protective humoral immunity remains, which could reduce disease severity in an orthopoxvirus outbreak. Correlation between IgG and neutralizing titers was observed indicating that serology could be used as a surrogate marker for immunity.

Tuberculosis (TB) is an airborne disease caused by Mycobacterium tuberculosis (Mtb). Whilst a functional role for humoral immunity in Mtb protection remains poorly defined, previous studies have suggested that antibodies can contribute towards host defense. Thus, identifying the critical components in the antibody repertoires from immune, chronically exposed, healthy individuals represents an approach for identifying new determinants for natural protection. In this study, we performed a thorough analysis of the IgG/IgA memory B cell repertoire from occupationally exposed, immune volunteers. We detail the identification and selection of a human monoclonal antibody that exhibits protective activity in vivo and show that it targets a virulence factor LpqH. Intriguingly, protection in both human ex vivo and murine challenge experiments was isotype dependent, with most robust protection being mediated via IgG2 and IgA. These data have important implications for our understanding of natural mucosal immunity for Mtb and highlight a new target for future vaccine development.

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. 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)]. 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. 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).

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 localised 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 recognised 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 was demonstrated for each isolate, the 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 COVID19 patients to monitor the RBD in cells infected with SARS CoV-2 clinical isolates. These immunological reagents specifically recognise 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 RDB first appears.

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.

Hepatitis B Virus (HBV) is a hepadnavirus that is the principal pathogen underlying viral liver disease in human populations. In this study, we describe the isolation and characterization of a fully human monoclonal antibody for HBV. This HuMab was isolated by a combinatorial screen of the memory B-cell repertoire from an acute/recovered HBV-infected patient. Lead candidate selection was based upon strong binding and neutralizing activity for live HBV. We provide a detailed biochemical/biophysical, and subclass characterization of its specificity and affinity against all of the principal HBV genotypes combined with a functional analysis of its in vitro activity. We also demonstrate its potential as a prophylaxis/therapy in vivo using human liver chimeric mouse models for HBV infection. These data have important implications for our understanding of natural human immunity to HBV and suggest that this potentially represents a new antibody-based anti-viral candidate for prophylaxis and/or therapy for HBV infection.

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.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is initiated by binding of the viral Spike protein to host receptor angiotensin-converting enzyme 2 (ACE2), followed by fusion of viral and host membranes. Although antibodies that block this interaction are in emergency use as early coronavirus disease 2019 (COVID-19) therapies, the precise determinants of neutralization potency remain unknown. We discovered a series of antibodies that potently block ACE2 binding but exhibit divergent neutralization efficacy against the live virus. Strikingly, these neutralizing antibodies can inhibit or enhance Spike-mediated membrane fusion and formation of syncytia, which are associated with chronic tissue damage in individuals with COVID-19. As revealed by cryoelectron microscopy, multiple structures of Spike-antibody complexes have distinct binding modes that not only block ACE2 binding but also alter the Spike protein conformational cycle triggered by ACE2 binding. We show that stabilization of different Spike conformations leads to modulation of Spike-mediated membrane fusion with profound implications for COVID-19 pathology and immunity.

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.

Objectives: We aimed to harness IDentif.AI 2.0, a clinically actionable AI platform to rapidly pinpoint and prioritize optimal combination therapy regimens against COVID-19. Methods: A pool of starting candidate therapies was developed in collaboration with a community of infectious disease clinicians and included EIDD-1931 (metabolite of EIDD-2801), baricitinib, ebselen, selinexor, masitinib, nafamostat mesylate, telaprevir (VX-950), SN-38 (metabolite of irinotecan), imatinib mesylate, remdesivir, lopinavir, and ritonavir. Following the initial drug pool assessment, a focused, 6-drug pool was interrogated at 3 dosing levels per drug representing nearly 10,000 possible combination regimens. IDentif.AI 2.0 paired prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus (propagated, original strain and B.1.351 variant) and Vero E6 assay with a quadratic optimization workflow. Results: Within 3 weeks, IDentif.AI 2.0 realized a list of combination regimens, ranked by efficacy, for clinical go/no-go regimen recommendations. IDentif.AI 2.0 revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived. Conclusions: IDentif.AI 2.0 rapidly revealed promising drug combinations for a clinical translation. It pinpointed dose-dependent drug synergy behavior to play a role in trial design and realizing positive treatment outcomes. IDentif.AI 2.0 represents an actionable path towards rapidly optimizing combination therapy following pandemic emergence.

ABSTRACT The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) has led to the rapid initiation of urgently needed clinical trials of repurposed drug combinations and monotherapies. These regimens were primarily relying on mechanism-of-action based selection of drugs, many of which have yielded positive in vitro but largely negative clinical outcomes. To overcome this challenge, we report the use of IDentif.AI, a platform that rapidly optimizes infectious disease (ID) combination therapy design using artificial intelligence (AI). In this study, IDentif.AI was implemented on a 12-drug candidate therapy search set representing over 530,000 possible drug combinations. IDentif.AI demonstrated that the optimal combination therapy against SARS-CoV-2 was comprised of remdesivir, ritonavir, and lopinavir, which mediated a 6.5-fold improvement in efficacy over remdesivir alone. Additionally, IDentif.AI showed hydroxychloroquine and azithromycin to be relatively ineffective. The identification of a clinically actionable optimal drug combination was completed within two weeks, with a 3-order of magnitude reduction in the number of tests typically needed. IDentif.AI analysis was also able to independently confirm clinical trial outcomes to date without requiring any data from these trials. The robustness of the IDentif.AI platform suggests that it may be applicable towards rapid development of optimal drug regimens to address current and future outbreaks.

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.

Our understanding of the conformational and electrostatic determinants that underlie targeting of human leukocyte antigens (HLA) by anti-HLA alloantibodies is principally based upon in silico modelling. Here we provide a biochemical/biophysical and functional characterization of a human monoclonal alloantibody specific for a common HLA type, HLA-A*11:01. We present a 2.4 Å resolution map of the binding interface of this antibody on HLA-A*11:01 and compare the structural determinants with those utilized by T-cell receptor (TCR), killer-cell immunoglobulin-like receptor (KIR) and CD8 on the same molecule. These data provide a mechanistic insight into the paratope−epitope relationship between an alloantibody and its target HLA molecule in a biological context where other immune receptors are concomitantly engaged. This has important implications for our interpretation of serologic binding patterns of anti-HLA antibodies in sensitized individuals and thus, for the biology of human alloresponses.

Targeting model antigens (Ags) to Clec9A on DC has been shown to induce, not only cytotoxic T cells, but also high levels of Ab. In fact, Ab responses against immunogenic Ag were effectively generated even in the absence of DC-activating adjuvants. Here we tested if targeting weakly immunogenic putative subunit vaccine Ags to Clec9A could enhance Ab responses to a level likely to be protective. The proposed "universal" influenza Ag, M2e and the enterovirus 71 Ag, SP70 were linked to anti-Clec9A Abs and injected into mice. Targeting these Ags to Clec9A greatly increased Ab titres. For optimal responses, a DC-activating adjuvant was required. For optimal responses, a boost injection was also needed, but the high Ab titres against the targeting construct blocked Clec9A-targeted boosting. Heterologous prime-boost strategies avoiding cross-reactivity between the priming and boosting targeting constructs overcame this limitation. In addition, targeting small amounts of Ag to Clec9A served as an efficient priming for a conventional boost with higher levels of untargeted Ag. Using this Clec9A-targeted priming, conventional boosting strategy, M2e immunisation protected mice from infection with lethal doses of influenza H1N1 virus.

Epstein-Barr virus (EBV) is a common gammaherpesvirus associated with various human malignancies. Antibodies with T cell receptor-like specificities (TCR-like mAbs) provide a means to target intracellular tumor- or virus-associated antigens by recognising their processed peptides presented on major histocompatibility complex (MHC) class I (pMHC) complexes. These antibodies are however thought to be relevant only for a single HLA allele. Here, we show that HLA-A*02:01-restricted EBV antigenic peptides EBNA1562-570, LMP1125-133 and LMP2A426-434 display binding degeneracy towards HLA-A*02 allelic microvariants, and that these pMHC complexes are recognised by anti-EBV TCR-like mAbs E1, L1 and L2 raised in the context of HLA-A*02:01. These antibodies bound endogenously derived pMHC targets on EBV-transformed human B lymphoblastoid cell lines expressing A*02:01, A*02:03, A*02:06 and A*02:07 alleles. More importantly, these TCR-like mAbs mediated both complement-dependent and antibody-dependent cellular cytotoxicity of these cell lines in vitro. This finding suggests the utility of TCR-like mAbs against target cells of closely related HLA subtypes, and the potential applicability of similar reagents within populations of diverse HLA-A*02 alleles.