The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens
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Abstract
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.
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SciScore for 10.1101/2021.06.23.21259321: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Cell Line Authentication not detected. Table 2: Resources
Experimental Models: Cell Lines Sentences Resources 2 x 104 Vero E6 cells were added into each well with and without SARS-CoV-2 (100 TCID50) to test viral CPE inhibition and cytotoxicity effects, respectively. Vero E6suggested: None%Cytotoxicity in the validation experimental step was calculated in THLE-2 human liver and AC16 human cardiomyocyte cell lines. AC16suggested: NoneSoftware and Algorithms Sentences Resources The analysis was performed in MATLAB R2020a (Mathworks, Inc.) (Blasiak et al., 2021). MATLABsuggested:…SciScore for 10.1101/2021.06.23.21259321: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Cell Line Authentication not detected. Table 2: Resources
Experimental Models: Cell Lines Sentences Resources 2 x 104 Vero E6 cells were added into each well with and without SARS-CoV-2 (100 TCID50) to test viral CPE inhibition and cytotoxicity effects, respectively. Vero E6suggested: None%Cytotoxicity in the validation experimental step was calculated in THLE-2 human liver and AC16 human cardiomyocyte cell lines. AC16suggested: NoneSoftware and Algorithms Sentences Resources The analysis was performed in MATLAB R2020a (Mathworks, Inc.) (Blasiak et al., 2021). MATLABsuggested: (MATLAB, RRID:SCR_001622)GraphPad Prism 9 software (GraphPad Software) was used to plot D-R curves and derive EC50 of %Inhibition and CC50 of %Cytotoxicity of the validation set treatments (monotherapies and combinations). GraphPadsuggested: (GraphPad Prism, RRID:SCR_002798)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations of the study: It is important to note that this study was conducted in an in vitro live virus model, and the subsequent preclinical and clinical dose optimization and evaluation will be needed. This study evaluated a pre-specified drug pool, and further studies with additional drug candidates are warranted. Developing a set of drug selection criteria such as drug class, administration route, prior evidence of interaction with other drugs, clinical relevance and accessibility may streamline the development of the drug pool. While the current study did not examine the immunomodulatory effects of the anti-inflammatories (SN-38, BRT), future work using applicable assays towards combination therapy development with immunomodulators is warranted as IDentif.AI 2.0 can be implemented in virtually all assays, provided quantifiable efficacy and toxicity readouts are available. Including immunomodulation will potentially create viable therapeutic options for severe patients as shown by recent clinical progress (Group et al., 2021). The IDentif.AI 2.0 workflow has some technical limitations, nonetheless, it is developed for rapid optimization and clinical actionability, and complementary strategies can be integrated to address them. First, the IDentif.AI interaction space interrogation assumes a quadratic relationship with the efficacy/cytotoxicity responses. The optimized combinations presented here are largely limited to two-drug combinations, rapidly identifying the most s...
Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04575597 Recruiting Efficacy and Safety of Molnupiravir (MK-4482) in Non-Hospita… Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
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Results from scite Reference Check: We found no unreliable references.
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