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Background: BBV152 is a whole-virion inactivated SARS-CoV-2 vaccine that has been deployed in India. The results of the phase 3 trial have shown clinical efficacy of BBV152. We aimed to evaluate the effectiveness of BBV152 against symptomatic RT-PCR-confirmed SARS-CoV-2 infection., Methods: We conducted a test-negative, case-control study among employees of the All India Institute of Medical Sciences (a tertiary care hospital in New Delhi, India), who had symptoms suggestive of COVID-19 and had an RT-PCR test for SARS-CoV-2 during the peak of the second wave of the COVID-19 pandemic in India between April 15 and May 15, 2021. Cases (test-positives) and controls (test-negatives) were matched (1:1) on the basis of age and gender. The odds of vaccination with BBV152 were compared between cases and controls and adjusted for level of occupational exposure (to COVID-19), previous SARS-CoV-2 infection, and calendar time, using conditional logistic regression. The primary outcome was effectiveness of two doses of BBV152 (with the second dose received at least 14 days before testing) in reducing the odds of symptomatic RT-PCR-confirmed SARS-CoV-2 infection, expressed as (1 - odds ratio) × 100%., Findings: Between April 15 and May 15, 2021, 3732 individuals had an RT-PCR test. Of these, 2714 symptomatic employees had data on vaccination status, and 1068 matched case-control pairs were available for analysis. The adjusted effectiveness of BBV152 against symptomatic COVID-19 after two doses administered at least 14 days before testing was 50% (95% CI 33-62; p<0·0001). The adjusted effectiveness of two doses administered at least 28 days before testing was 46% (95% CI 22-62) and administered at least 42 days before testing was 57% (21-76). After excluding participants with previous SARS-CoV-2 infections, the adjusted effectiveness of two doses administered at least 14 days before testing was 47% (95% CI 29-61)., Interpretation: This study shows the effectiveness of two doses of BBV152 against symptomatic COVID-19 in the context of a huge surge in cases, presumably dominated by the potentially immune-evasive delta (B.1.617.2) variant of SARS-CoV-2. Our findings support the ongoing roll-out of this vaccine to help control the spread of SARS-CoV-2, while continuing the emphasis on adherence to non-pharmacological measures., Funding: None., Translation: For the Hindi translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as well as the discovery of multiple vaccines. During an urgent crisis, rapidly identifying potential new treatments requires global and cross-discipline cooperation, together with an enhanced open-access research model to distribute new ideas and leads. Herein, we introduce an application of a deep neural network based drug screening method, validating it using a docking algorithm on approved drugs for drug repurposing efforts, and extending the screen to a large library of 750,000 compounds for de novo drug discovery effort. The results of large library screens are incorporated into an open-access web interface to allow researchers from diverse fields to target molecules of interest. Our combined approach allows for both the identification of existing drugs that may be able to be repurposed and de novo design of ACE2-regulatory compounds. Through these efforts we demonstrate the utility of a new machine learning algorithm for drug discovery, SSnet, that can function as a tool to triage large molecular libraries to identify classes of molecules with possible efficacy.