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 op...
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Published in | NPJ digital medicine Vol. 5; no. 1; pp. 83 - 12 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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London
Nature Publishing Group UK
30.06.2022
Nature Publishing Group Nature Portfolio |
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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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AbstractList | 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.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. 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. 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. |
ArticleNumber | 83 |
Author | Blasiak, Agata Allen, David Michael Chan, Conrad En Zuo Wang, Peter Chye, De Hoe Lim, Angeline Pei Chiew Teo, Swee Teng Seah, Shirley Gek Kheng Chng, Wee Joo Ho, Dean Lin, Raymond T. P. Lye, David C. B. Wong, John Eu-Li Hooi, Lissa Chow, Edward Kai-Hua Tan, Yee-Joo Chai, Louis Yi Ann Remus, Alexandria Tan, Gek-Yen Gladys Truong, Anh T. L. Ng, Kim Tien |
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L. organization: The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, The N.1 Institute for Health (N.1), National University of Singapore, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore – sequence: 3 givenname: Alexandria surname: Remus fullname: Remus, Alexandria organization: The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, The N.1 Institute for Health (N.1), National University of Singapore, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore – sequence: 4 givenname: Lissa surname: Hooi fullname: Hooi, Lissa organization: Cancer Science Institute of Singapore, National University of Singapore – sequence: 5 givenname: Shirley Gek Kheng surname: Seah fullname: Seah, Shirley Gek Kheng organization: Defence Medical and Environmental Research Institute, DSO National Laboratories – sequence: 6 givenname: Peter orcidid: 0000-0002-4925-1738 surname: Wang fullname: Wang, Peter organization: The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, The N.1 Institute for Health (N.1), National University of Singapore, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore – sequence: 7 givenname: De Hoe surname: Chye fullname: Chye, De Hoe organization: Defence Medical and Environmental Research Institute, DSO National Laboratories – sequence: 8 givenname: Angeline Pei Chiew surname: Lim fullname: Lim, Angeline Pei Chiew organization: Defence Medical and Environmental Research Institute, DSO National Laboratories – sequence: 9 givenname: Kim Tien surname: Ng fullname: Ng, Kim Tien organization: Defence Medical and Environmental Research Institute, DSO National Laboratories – sequence: 10 givenname: Swee Teng surname: Teo fullname: Teo, Swee Teng organization: Infectious Diseases Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore – sequence: 11 givenname: Yee-Joo orcidid: 0000-0002-2278-4497 surname: Tan fullname: Tan, Yee-Joo organization: Infectious Diseases Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Institute of Molecular and Cell Biology (IMCB), ASTAR – sequence: 12 givenname: David Michael orcidid: 0000-0001-5333-1258 surname: Allen fullname: Allen, David Michael organization: Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Division of Infectious Diseases, National University Hospital – sequence: 13 givenname: Louis Yi Ann surname: Chai fullname: Chai, Louis Yi Ann organization: Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Division of Infectious Diseases, National University Hospital – sequence: 14 givenname: Wee Joo surname: Chng fullname: Chng, Wee Joo organization: Cancer Science Institute of Singapore, National University of Singapore, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Hospital, NUS Centre for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore – sequence: 15 givenname: Raymond T. P. surname: Lin fullname: Lin, Raymond T. P. organization: National Centre for Infectious Diseases (NCID), Jalan Tan Tock Seng, Department of Laboratory Medicine, National University Hospital – sequence: 16 givenname: David C. B. surname: Lye fullname: Lye, David C. B. organization: Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National Centre for Infectious Diseases (NCID), Jalan Tan Tock Seng, Lee Kong Chian School of Medicine, Nanyang Technological University, Department of Infectious Diseases, Tan Tock Seng Hospital – sequence: 17 givenname: John Eu-Li surname: Wong fullname: Wong, John Eu-Li organization: Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Department of Haematology-Oncology, National University Cancer Institute, Singapore, National University Hospital – sequence: 18 givenname: Gek-Yen Gladys surname: Tan fullname: Tan, Gek-Yen Gladys organization: Defence Medical and Environmental Research Institute, DSO National Laboratories – sequence: 19 givenname: Conrad En Zuo surname: Chan fullname: Chan, Conrad En Zuo email: Conrad_EZ_CHAN@ncid.sg organization: Defence Medical and Environmental Research Institute, DSO National Laboratories, National Centre for Infectious Diseases (NCID), Jalan Tan Tock Seng – sequence: 20 givenname: Edward Kai-Hua surname: Chow fullname: Chow, Edward Kai-Hua email: csikce@nus.edu.sg organization: The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, The N.1 Institute for Health (N.1), National University of Singapore, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Cancer Science Institute of Singapore, National University of Singapore, NUS Centre for Cancer Research (N2CR), Yong Loo Lin School of Medicine, National University of Singapore – sequence: 21 givenname: Dean surname: Ho fullname: Ho, Dean email: biedh@nus.edu.sg organization: The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, The N.1 Institute for Health (N.1), National University of Singapore, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore |
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Snippet | IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against... Abstract IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies... |
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SubjectTerms | 631/114 692/699/255/2514 Artificial intelligence Biomedicine Biotechnology Combination therapy Coronaviruses COVID-19 Digital technology Drug efficacy Emergency preparedness Medicine Medicine & Public Health Pandemics Severe acute respiratory syndrome coronavirus 2 |
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Title | The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens |
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