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Immune‐viral dynamics modeling for SARS‐CoV‐2 drug development
Coronavirus disease 2019 (COVID‐19) global pandemic is caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS‐CoV‐2 is critical for development of eff...
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Published in: | Clinical and Translational Science 2021-11, Vol.14 (6), p.2348-2359 |
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description | Coronavirus disease 2019 (COVID‐19) global pandemic is caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS‐CoV‐2 is critical for development of effective treatments. An Immune‐Viral Dynamics Model (IVDM) is developed to describe SARS‐CoV‐2 viral dynamics and COVID‐19 disease progression. A dataset of 60 individual patients with COVID‐19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS‐CoV‐2, viral‐induced cell death, and time‐dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed‐effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell‐based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose‐efficacy response analysis for COVID‐19 drug development. |
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Understanding viral dynamics of SARS‐CoV‐2 is critical for development of effective treatments. An Immune‐Viral Dynamics Model (IVDM) is developed to describe SARS‐CoV‐2 viral dynamics and COVID‐19 disease progression. A dataset of 60 individual patients with COVID‐19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS‐CoV‐2, viral‐induced cell death, and time‐dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed‐effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell‐based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose‐efficacy response analysis for COVID‐19 drug development.</description><identifier>ISSN: 1752-8054</identifier><identifier>EISSN: 1752-8062</identifier><identifier>DOI: 10.1111/cts.13099</identifier><identifier>PMID: 34121337</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>Adaptive immunity ; Antiviral Agents - pharmacology ; Antiviral Agents - therapeutic use ; Apoptosis ; Cell death ; Cell Death - drug effects ; Cell Death - immunology ; Coronaviruses ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - immunology ; COVID-19 - virology ; COVID-19 Drug Treatment ; Datasets ; Datasets as Topic ; Disease transmission ; Dose-Response Relationship, Drug ; Drug development ; Drug Development - methods ; Host Microbial Interactions - drug effects ; Host Microbial Interactions - immunology ; Humans ; Immune response ; Infections ; Models, Biological ; Nonlinear Dynamics ; Pandemics ; Pharmacodynamics ; Pharmacokinetics ; SARS-CoV-2 - drug effects ; SARS-CoV-2 - immunology ; Severe acute respiratory syndrome coronavirus 2 ; Severity of Illness Index ; Simulation ; Standard deviation ; Treatment Outcome ; Viral infections ; Viral Load ; Viruses</subject><ispartof>Clinical and Translational Science, 2021-11, Vol.14 (6), p.2348-2359</ispartof><rights>2021 Merck Sharp & Dohme Corp. published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics</rights><rights>2021 Merck Sharp & Dohme Corp. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.</rights><rights>2021. This work is published under http://creativecommons.org/licenses/by-nd/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). 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Understanding viral dynamics of SARS‐CoV‐2 is critical for development of effective treatments. An Immune‐Viral Dynamics Model (IVDM) is developed to describe SARS‐CoV‐2 viral dynamics and COVID‐19 disease progression. A dataset of 60 individual patients with COVID‐19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS‐CoV‐2, viral‐induced cell death, and time‐dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed‐effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell‐based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. 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Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cao, Youfang</au><au>Gao, Wei</au><au>Caro, Luzelena</au><au>Stone, Julie A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Immune‐viral dynamics modeling for SARS‐CoV‐2 drug development</atitle><jtitle>Clinical and Translational Science</jtitle><addtitle>Clin Transl Sci</addtitle><date>2021-11</date><risdate>2021</risdate><volume>14</volume><issue>6</issue><spage>2348</spage><epage>2359</epage><pages>2348-2359</pages><issn>1752-8054</issn><eissn>1752-8062</eissn><abstract>Coronavirus disease 2019 (COVID‐19) global pandemic is caused by severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) viral infection, which can lead to pneumonia, lung injury, and death in susceptible populations. Understanding viral dynamics of SARS‐CoV‐2 is critical for development of effective treatments. An Immune‐Viral Dynamics Model (IVDM) is developed to describe SARS‐CoV‐2 viral dynamics and COVID‐19 disease progression. A dataset of 60 individual patients with COVID‐19 with clinical viral load (VL) and reported disease severity were assembled from literature. Viral infection and replication mechanisms of SARS‐CoV‐2, viral‐induced cell death, and time‐dependent immune response are incorporated in the model to describe the dynamics of viruses and immune response. Disease severity are tested as a covariate to model parameters. The IVDM was fitted to the data and parameters were estimated using the nonlinear mixed‐effect model. The model can adequately describe individual viral dynamics profiles, with disease severity identified as a covariate on infected cell death rate. The modeling suggested that it takes about 32.6 days to reach 50% of maximum cell‐based immunity. Simulations based on virtual populations suggested a typical mild case reaches VL limit of detection (LOD) by 13 days with no treatment, a moderate case by 17 days, and a severe case by 41 days. Simulations were used to explore hypothetical treatments with different initiation time, disease severity, and drug effects to demonstrate the usefulness of such modeling in informing decisions. Overall, the IVDM modeling and simulation platform enables simulations for viral dynamics and treatment efficacy and can be used to aid in clinical pharmacokinetic/pharmacodynamic (PK/PD) and dose‐efficacy response analysis for COVID‐19 drug development.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>34121337</pmid><doi>10.1111/cts.13099</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adaptive immunity Antiviral Agents - pharmacology Antiviral Agents - therapeutic use Apoptosis Cell death Cell Death - drug effects Cell Death - immunology Coronaviruses COVID-19 COVID-19 - diagnosis COVID-19 - immunology COVID-19 - virology COVID-19 Drug Treatment Datasets Datasets as Topic Disease transmission Dose-Response Relationship, Drug Drug development Drug Development - methods Host Microbial Interactions - drug effects Host Microbial Interactions - immunology Humans Immune response Infections Models, Biological Nonlinear Dynamics Pandemics Pharmacodynamics Pharmacokinetics SARS-CoV-2 - drug effects SARS-CoV-2 - immunology Severe acute respiratory syndrome coronavirus 2 Severity of Illness Index Simulation Standard deviation Treatment Outcome Viral infections Viral Load Viruses |
title | Immune‐viral dynamics modeling for SARS‐CoV‐2 drug development |
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