101
|
Kern C, Schöning V, Chaccour C, Hammann F. Modeling of SARS-CoV-2 Treatment Effects for Informed Drug Repurposing. Front Pharmacol 2021; 12:625678. [PMID: 33776767 PMCID: PMC7988345 DOI: 10.3389/fphar.2021.625678] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 01/21/2021] [Indexed: 12/28/2022] Open
Abstract
Several repurposed drugs are currently under investigation in the fight against coronavirus disease 2019 (COVID-19). Candidates are often selected solely by their effective concentrations in vitro, an approach that has largely not lived up to expectations in COVID-19. Cell lines used in in vitro experiments are not necessarily representative of lung tissue. Yet, even if the proposed mode of action is indeed true, viral dynamics in vivo, host response, and concentration-time profiles must also be considered. Here we address the latter issue and describe a model of human SARS-CoV-2 viral kinetics with acquired immune response to investigate the dynamic impact of timing and dosing regimens of hydroxychloroquine, lopinavir/ritonavir, ivermectin, artemisinin, and nitazoxanide. We observed greatest benefits when treatments were given immediately at the time of diagnosis. Even interventions with minor antiviral effect may reduce host exposure if timed correctly. Ivermectin seems to be at least partially effective: given on positivity, peak viral load dropped by 0.3-0.6 log units and exposure by 8.8-22.3%. The other drugs had little to no appreciable effect. Given how well previous clinical trial results for hydroxychloroquine and lopinavir/ritonavir are explained by the models presented here, similar strategies should be considered in future drug candidate prioritization efforts.
Collapse
Affiliation(s)
- Charlotte Kern
- Clinical Pharmacology and Toxicology, Department of General Internal Medicine, Inselspital (Bern University Hospital), University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Verena Schöning
- Clinical Pharmacology and Toxicology, Department of General Internal Medicine, Inselspital (Bern University Hospital), University of Bern, Bern, Switzerland
| | - Carlos Chaccour
- ISGlobal, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
- Clínica Universidad de Navarra, Pamplona, Spain
- Ifakara Health Institute, Ifakara, Tanzania
| | - Felix Hammann
- Clinical Pharmacology and Toxicology, Department of General Internal Medicine, Inselspital (Bern University Hospital), University of Bern, Bern, Switzerland
| |
Collapse
|
102
|
Perelson AS, Ke R. Mechanistic Modeling of SARS-CoV-2 and Other Infectious Diseases and the Effects of Therapeutics. Clin Pharmacol Ther 2021; 109:829-840. [PMID: 33410134 DOI: 10.1002/cpt.2160] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical, and modeling communities during the early days of the AIDS epidemic. Its successes led to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. We then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID-19) pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein, "Everything should be made as simple as possible, but not simpler," and this idea underlies the modeling we describe below.
Collapse
Affiliation(s)
- Alan S Perelson
- Los Alamos National Laboratory, Theoretical Biology and Biophysics Group, Los Alamos, New Mexico, USA.,New Mexico Consortium, Los Alamos, New Mexico, USA
| | - Ruian Ke
- Los Alamos National Laboratory, Theoretical Biology and Biophysics Group, Los Alamos, New Mexico, USA.,New Mexico Consortium, Los Alamos, New Mexico, USA
| |
Collapse
|
103
|
Friberg LE. Pivotal Role of Translation in Anti‐Infective Development. Clin Pharmacol Ther 2021; 109:856-866. [DOI: 10.1002/cpt.2182] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 01/08/2021] [Indexed: 12/12/2022]
|
104
|
Hache G, Rolain JM, Gautret P, Deharo JC, Brouqui P, Raoult D, Honoré S. Combination of Hydroxychloroquine Plus Azithromycin As Potential Treatment for COVID-19 Patients: Safety Profile, Drug Interactions, and Management of Toxicity. Microb Drug Resist 2021; 27:281-290. [PMID: 33729874 PMCID: PMC7987362 DOI: 10.1089/mdr.2020.0232] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory syndrome coronavirus 2, has recently emerged worldwide. In this context, there is an urgent need to identify safe and effective therapeutic strategies for treatment of such highly contagious disease. We recently reported promising results of combining hydroxychloroquine and azithromycin as an early treatment option. Although ongoing clinical trials are challenging the efficacy of this combination, many clinicians claim the authorization to or have already begun to use it to treat COVID-19 patients worldwide. The aim of this article is to share pharmacology considerations contributing to the rationale of this combination, and to provide safety information to prevent toxicity and drug-drug interactions, based on available evidence.
Collapse
Affiliation(s)
- Guillaume Hache
- Service de Pharmacie, Hôpital de la Timone, APHM, Marseille, France
- Aix Marseille Univ, INSERM, INRAE, C2VN, Marseille, France
| | - Jean Marc Rolain
- IHU-Méditerranée Infection, Marseille, France
- Aix Marseille Univ, IRD, APHM, MEPHI, Marseille, France
| | - Philippe Gautret
- IHU-Méditerranée Infection, Marseille, France
- Aix Marseille Univ, IRD, AP-HM, SSA, VITROME, Marseille, France
| | - Jean-Claude Deharo
- Aix Marseille Univ, INSERM, INRAE, C2VN, Marseille, France
- Service de Cardiologie, Hôpital de la Timone, APHM, Marseille, France
| | - Philippe Brouqui
- IHU-Méditerranée Infection, Marseille, France
- Aix Marseille Univ, IRD, APHM, MEPHI, Marseille, France
| | - Didier Raoult
- IHU-Méditerranée Infection, Marseille, France
- Aix Marseille Univ, IRD, APHM, MEPHI, Marseille, France
| | - Stéphane Honoré
- Service de Pharmacie, Hôpital de la Timone, APHM, Marseille, France
- Aix Marseille Univ, Laboratoire de Pharmacie Clinique, Marseille, France
- Aix-Marseille Univ, CNRS, INP, Inst Neurophysiopathol, Marseille, France
| |
Collapse
|
105
|
Kim KS, Ejima K, Iwanami S, Fujita Y, Ohashi H, Koizumi Y, Asai Y, Nakaoka S, Watashi K, Aihara K, Thompson RN, Ke R, Perelson AS, Iwami S. A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2. PLoS Biol 2021; 19:e3001128. [PMID: 33750978 PMCID: PMC7984623 DOI: 10.1371/journal.pbio.3001128] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 02/01/2021] [Indexed: 12/11/2022] Open
Abstract
The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2-3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.
Collapse
Affiliation(s)
- Kwang Su Kim
- Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan
| | - Keisuke Ejima
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health–Bloomington, Bloomington, Indiana, United States of America
| | - Shoya Iwanami
- Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan
| | - Yasuhisa Fujita
- Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan
| | - Hirofumi Ohashi
- Department of Virology II, National Institute of Infectious Diseases, Tokyo, Japan
| | - Yoshiki Koizumi
- National Center for Global Health and Medicine, Tokyo, Japan
| | - Yusuke Asai
- National Center for Global Health and Medicine, Tokyo, Japan
| | - Shinji Nakaoka
- Faculty of Advanced Life Science, Hokkaido University, Sapporo, Japan
| | - Koichi Watashi
- Department of Virology II, National Institute of Infectious Diseases, Tokyo, Japan
- Department of Applied Biological Science, Tokyo University of Science, Noda, Japan
- Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan
- JST-Mirai, Japan Science and Technology Agency, Saitama, Japan
| | - Kazuyuki Aihara
- International Research Center for Neurointelligence, University of Tokyo Institutes for Advanced Study, University of Tokyo, Tokyo, Japan
| | - Robin N. Thompson
- Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
| | - Ruian Ke
- New Mexico Consortium, Los Alamos, New Mexico, United States of America
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Alan S. Perelson
- New Mexico Consortium, Los Alamos, New Mexico, United States of America
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Shingo Iwami
- Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan
- JST-Mirai, Japan Science and Technology Agency, Saitama, Japan
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- NEXT-Ganken Program, Japanese Foundation for Cancer Research, Tokyo, Japan
- Science Groove, Fukuoka, Japan
| |
Collapse
|
106
|
Czuppon P, Débarre F, Gonçalves A, Tenaillon O, Perelson AS, Guedj J, Blanquart F. Success of prophylactic antiviral therapy for SARS-CoV-2: Predicted critical efficacies and impact of different drug-specific mechanisms of action. PLoS Comput Biol 2021; 17:e1008752. [PMID: 33647008 PMCID: PMC7951973 DOI: 10.1371/journal.pcbi.1008752] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 03/11/2021] [Accepted: 01/31/2021] [Indexed: 02/06/2023] Open
Abstract
Repurposed drugs that are safe and immediately available constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we evaluate the success of prophylactic treatment with different drug types to prevent viral infection. We find that there exists a critical efficacy that a treatment must reach in order to block viral establishment. Treatment by a combination of drugs reduces the critical efficacy, most effectively by the combination of a drug blocking viral entry into cells and a drug increasing viral clearance. Below the critical efficacy, the risk of infection can nonetheless be reduced. Drugs blocking viral entry into cells or enhancing viral clearance reduce the risk of infection more than drugs that reduce viral production in infected cells. The larger the initial inoculum of infectious virus, the less likely is prevention of an infection. In our model, we find that as long as the viral inoculum is smaller than 10 infectious virus particles, viral infection can be prevented almost certainly with drugs of 90% efficacy (or more). Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. The largest delay of viral infection is achieved by drugs reducing viral production in infected cells. A delay of virus infection flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.
Collapse
Affiliation(s)
- Peter Czuppon
- Institute of Ecology and Environmental Sciences of Paris, Sorbonne Université, CNRS, UPEC, IRD, INRAE, Paris, France
- Center for Interdisciplinary Research in Biology, CNRS, Collège de France, PSL Research University, Paris, France
| | - Florence Débarre
- Institute of Ecology and Environmental Sciences of Paris, Sorbonne Université, CNRS, UPEC, IRD, INRAE, Paris, France
| | | | | | - Alan S. Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
- New Mexico Consortium, Los Alamos, New Mexico, United States of America
| | | | - François Blanquart
- Center for Interdisciplinary Research in Biology, CNRS, Collège de France, PSL Research University, Paris, France
- Université de Paris, INSERM, IAME, Paris, France
| |
Collapse
|
107
|
Néant N, Lingas G, Le Hingrat Q, Ghosn J, Engelmann I, Lepiller Q, Gaymard A, Ferré V, Hartard C, Plantier JC, Thibault V, Marlet J, Montes B, Bouiller K, Lescure FX, Timsit JF, Faure E, Poissy J, Chidiac C, Raffi F, Kimmoun A, Etienne M, Richard JC, Tattevin P, Garot D, Le Moing V, Bachelet D, Tardivon C, Duval X, Yazdanpanah Y, Mentré F, Laouénan C, Visseaux B, Guedj J. Modeling SARS-CoV-2 viral kinetics and association with mortality in hospitalized patients from the French COVID cohort. Proc Natl Acad Sci U S A 2021; 118:e2017962118. [PMID: 33536313 PMCID: PMC7929555 DOI: 10.1073/pnas.2017962118] [Citation(s) in RCA: 142] [Impact Index Per Article: 47.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
The characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral kinetics in hospitalized patients and its association with mortality is unknown. We analyzed death and nasopharyngeal viral kinetics in 655 hospitalized patients from the prospective French COVID cohort. The model predicted a median peak viral load that coincided with symptom onset. Patients with age ≥65 y had a smaller loss rate of infected cells, leading to a delayed median time to viral clearance occurring 16 d after symptom onset as compared to 13 d in younger patients (P < 10-4). In multivariate analysis, the risk factors associated with mortality were age ≥65 y, male gender, and presence of chronic pulmonary disease (hazard ratio [HR] > 2.0). Using a joint model, viral dynamics after hospital admission was an independent predictor of mortality (HR = 1.31, P < 10-3). Finally, we used our model to simulate the effects of effective pharmacological interventions on time to viral clearance and mortality. A treatment able to reduce viral production by 90% upon hospital admission would shorten the time to viral clearance by 2.0 and 2.9 d in patients of age <65 y and ≥65 y, respectively. Assuming that the association between viral dynamics and mortality would remain similar to that observed in our population, this could translate into a reduction of mortality from 19 to 14% in patients of age ≥65 y with risk factors. Our results show that viral dynamics is associated with mortality in hospitalized patients. Strategies aiming to reduce viral load could have an effect on mortality rate in this population.
Collapse
Affiliation(s)
- Nadège Néant
- Université de Paris, INSERM, IAME, F-75018 Paris, France;
| | | | - Quentin Le Hingrat
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Laboratoire de Virologie, F-75018 Paris, France
| | - Jade Ghosn
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hopital Bichat, Service de Maladies Infectieuses et Tropicales, F-75018 Paris, France
| | - Ilka Engelmann
- Univ. Lille, Virology Laboratory, EA3610, Institute of Microbiology, Centre Hospitalier-Universitaire de Lille, F-59037 Lille Cedex, France
| | - Quentin Lepiller
- Laboratoire de Virologie, Centre Hospitalier-Universitaire de Besançon, F-25000 Besançon, France
| | - Alexandre Gaymard
- Laboratoire de Virologie, Institut des Agents Infectieux, Hospices Civils de Lyon, Groupement Hospitalier Nord, F-69004 Lyon, France
- Centre National de Référence des Virus Respiratoires, Hospices Civils de Lyon, Groupement Hospitalier Nord, F-69004 Lyon, France
| | - Virginie Ferré
- Service de Virologie, Centre Hospitalier-Universitaire de Nantes, F-44093 Nantes, France
| | - Cédric Hartard
- Laboratoire de Microbiologie, Centre Hospitalier-Universitaire de Nancy, F-54000 Nancy, France
- Université de Lorraine, CNRS, Laboratoire de Chimie Physique et Microbiologie pour les Matériaux et l'Environnement, F-54000 Nancy, France
| | - Jean-Christophe Plantier
- Normandie University, UNIROUEN Rouen, EA2656, Virology, Rouen University Hospital, F-76000 Rouen, France
| | - Vincent Thibault
- Virology, Pontchaillou University Hospital, F-35033 Rennes cedex, France
| | - Julien Marlet
- Laboratoire de Virologie, Centre Hospitalier-Universitaire de Bretonneau, F-37044 Tours, France
- INSERM UMR 1259, Université de Tours, F-37044 Tours, France
| | - Brigitte Montes
- Laboratoire de Virologie, Centre Hospitalier-Universitaire de Montpellier, F-34295 Montpellier, France
| | - Kevin Bouiller
- Infectious and Tropical Disease Department, Besancon University Hospital, F-25000 Besancon, France
- UMR CNRS 6249, Chrono Environnement, University of Bourgogne Franche-Comté, F-25000 Besancon, France
| | - François-Xavier Lescure
- AP-HP, Hopital Bichat, Service de Maladies Infectieuses et Tropicales, F-75018 Paris, France
| | - Jean-François Timsit
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Service de Réanimation Médicale et Infectieuse, F-75018 Paris, France
| | - Emmanuel Faure
- Centre Hospitalier-Universitaire de Lille, Univ. Lille, Infectious Disease Department, CNRS, Inserm, U1019-UMR9017-CIIL, F-59000 Lille, France
| | - Julien Poissy
- Université de Lille, INSERM U1285, Centre Hospitalier-Universitaire de Lille, Pôle de réanimation, CNRS, UMR 8576-UGSF-Unité de Glycobiologie Structurale et Fonctionnelle, F-59000 Lille, France
| | - Christian Chidiac
- Infectious and Tropical Disease Department, Croix-Rousse Hospital, University Hospital of Lyon, F-69004 Lyon, France
| | - François Raffi
- Service de Maladies Infectieuses et Tropicales, Centre Hospitalier-Universitaire de Nantes, F-44093 Nantes, France
- Centre d'Investigation Clinique Unité d'Investigation Clinique 1413 INSERM, Centre Hospitalier-Universitaire de Nantes, F-44093 Nantes, France
| | - Antoine Kimmoun
- Université de Lorraine, Centre Hospitalier Régional Universitaire de Nancy, INSERM U1116, F-CRIN INICRCT, Service de Médecine Intensive et Réanimation Brabois, F-54000 Nancy, France
| | - Manuel Etienne
- Infectious Diseases Department, Rouen University Hospital, F-76000 Rouen, France
| | - Jean-Christophe Richard
- Lyon University, CREATIS, CNRS UMR5220, INSERM U1044, INSA, F-69000 Lyon, France
- Intensive Care Unit, Hospices Civils de Lyon, F-69002 Lyon, France
| | - Pierre Tattevin
- Infectious Diseases and Intensive Care Unit, Pontchaillou University Hospital, F-35000 Rennes, France
| | - Denis Garot
- Centre Hospitalier Régional Universitaire de Tours, Service de Médecine Intensive Réanimation, F-37044 Tours Cedex 9, France
| | - Vincent Le Moing
- Tropical and Infectious Diseases, Saint Eloi Hospital, Université de Montpellier, Medical School, Montpellier University Hospital, F-34295 Montpellier Cedex 5, France
| | - Delphine Bachelet
- AP-HP, Hôpital Bichat, Department of Epidemiology Biostatistics and Clinical Research, F-75018 Paris, France
| | - Coralie Tardivon
- AP-HP, Hôpital Bichat, Department of Epidemiology Biostatistics and Clinical Research, F-75018 Paris, France
| | - Xavier Duval
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Centre d'Investigation Clinique, INSERM CIC-1425, F-75018 Paris, France
| | - Yazdan Yazdanpanah
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hopital Bichat, Service de Maladies Infectieuses et Tropicales, F-75018 Paris, France
| | - France Mentré
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Department of Epidemiology Biostatistics and Clinical Research, F-75018 Paris, France
| | - Cédric Laouénan
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Department of Epidemiology Biostatistics and Clinical Research, F-75018 Paris, France
| | - Benoit Visseaux
- Université de Paris, INSERM, IAME, F-75018 Paris, France
- AP-HP, Hôpital Bichat, Laboratoire de Virologie, F-75018 Paris, France
| | - Jérémie Guedj
- Université de Paris, INSERM, IAME, F-75018 Paris, France
| |
Collapse
|
108
|
Dodds M, Xiong Y, Mouksassi S, Kirkpatrick CM, Hui K, Doyle E, Patel K, Cox E, Wesche D, Brown F, Rayner CR. Model-informed drug repurposing: A pharmacometric approach to novel pathogen preparedness, response and retrospection. Br J Clin Pharmacol 2021; 87:3388-3397. [PMID: 33534138 PMCID: PMC8013376 DOI: 10.1111/bcp.14760] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 01/15/2021] [Accepted: 01/25/2021] [Indexed: 12/11/2022] Open
Abstract
During a pandemic caused by a novel pathogen (NP), drug repurposing offers the potential of a rapid treatment response via a repurposed drug (RD) while more targeted treatments are developed. Five steps of model‐informed drug repurposing (MIDR) are discussed: (i) utilize RD product label and in vitro NP data to determine initial proof of potential, (ii) optimize potential posology using clinical pharmacokinetics (PK) considering both efficacy and safety, (iii) link events in the viral life cycle to RD PK, (iv) link RD PK to clinical and virologic outcomes, and optimize clinical trial design, and (v) assess RD treatment effects from trials using model‐based meta‐analysis. Activities which fall under these five steps are categorized into three stages: what can be accomplished prior to an NP emergence (preparatory stage), during the NP pandemic (responsive stage) and once the crisis has subsided (retrospective stage). MIDR allows for extraction of a greater amount of information from emerging data and integration of disparate data into actionable insight.
Collapse
Affiliation(s)
| | | | | | - Carl M Kirkpatrick
- Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Katrina Hui
- Certara, Princeton, NJ, USA.,Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | | | - Kashyap Patel
- Certara, Princeton, NJ, USA.,Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | | | | | | | - Craig R Rayner
- Certara, Princeton, NJ, USA.,Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia
| |
Collapse
|
109
|
Voutouri C, Nikmaneshi MR, Hardin CC, Patel AB, Verma A, Khandekar MJ, Dutta S, Stylianopoulos T, Munn LL, Jain RK. In silico dynamics of COVID-19 phenotypes for optimizing clinical management. Proc Natl Acad Sci U S A 2021; 118:e2021642118. [PMID: 33402434 PMCID: PMC7826337 DOI: 10.1073/pnas.2021642118] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8+ T cells and sufficient control of the innate immune response. Furthermore, the best treatment-or combination of treatments-depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.
Collapse
Affiliation(s)
- Chrysovalantis Voutouri
- Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus
| | - Mohammad Reza Nikmaneshi
- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, 11155
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - C Corey Hardin
- Department of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Ankit B Patel
- Department of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115
| | - Ashish Verma
- Department of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115
| | - Melin J Khandekar
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Sayon Dutta
- Department of Emergency Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Triantafyllos Stylianopoulos
- Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus;
| | - Lance L Munn
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114;
| | - Rakesh K Jain
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114;
| |
Collapse
|
110
|
Patel K, Dodds M, Gonçalves A, Kamal MA, Rayner CR, Kirkpatrick CM, Smith PF. Using in silico viral kinetic models to guide therapeutic strategies during a pandemic: An example in SARS-CoV-2. Br J Clin Pharmacol 2021; 87:3425-3438. [PMID: 33373059 DOI: 10.1111/bcp.14718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 12/01/2020] [Accepted: 12/13/2020] [Indexed: 12/14/2022] Open
Abstract
AIMS We propose the use of in silico mathematical models to provide insights that optimize therapeutic interventions designed to effectively treat respiratory infection during a pandemic. A modelling and simulation framework is provided using SARS-CoV-2 as an example, considering applications for both treatment and prophylaxis. METHODS A target cell-limited model was used to quantify the viral infection dynamics of SARS-CoV-2 in a pooled population of 105 infected patients. Parameter estimates from the resulting model were used to simulate and compare the impact of various interventions against meaningful viral load endpoints. RESULTS Robust parameter estimates were obtained for the basic reproduction number, viral release rate and infected-cell mortality from the infection model. These estimates were informed by the largest dataset currently available for SARS-CoV-2 viral time course. The utility of this model was demonstrated using simulations, which hypothetically introduced inhibitory or stimulatory drug mechanisms at various target sites within the viral life-cycle. We show that early intervention is crucial to achieving therapeutic benefit when monotherapy is administered. In contrast, combination regimens of two or three drugs may provide improved outcomes if treatment is initiated late. The latter is relevant to SARS-CoV-2, where the period between infection and symptom onset is relatively long. CONCLUSIONS The use of in silico models can provide viral load predictions that can rationalize therapeutic strategies against an emerging viral pathogen.
Collapse
|
111
|
Abuin P, Anderson A, Ferramosca A, Hernandez-Vargas EA, Gonzalez AH. Dynamical characterization of antiviral effects in COVID-19. ANNUAL REVIEWS IN CONTROL 2021; 52:587-601. [PMID: 34093069 PMCID: PMC8162791 DOI: 10.1016/j.arcontrol.2021.05.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/21/2021] [Accepted: 05/01/2021] [Indexed: 05/02/2023]
Abstract
Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. In addition, the virus dynamic in the host - including the time-to-peak and the final monotonically decreasing behavior - is characterized as a function of the time to treatment initiation. Simulation results, based on nine patient data, show the potential clinical benefits of a treatment classification according to patient critical parameters. This study is aimed at paving the way for the different antivirals being developed to tackle SARS-CoV-2.
Collapse
Affiliation(s)
- Pablo Abuin
- Institute of Technological Development for the Chemical Industry (INTEC), CONICET-UNL, Santa Fe, Argentina
| | - Alejandro Anderson
- Institute of Technological Development for the Chemical Industry (INTEC), CONICET-UNL, Santa Fe, Argentina
| | - Antonio Ferramosca
- Department of Management, Information and Production Engineering, University of Bergamo, Via Marconi 5, 24044, Dalmine (BG), Italy
| | | | - Alejandro H Gonzalez
- Institute of Technological Development for the Chemical Industry (INTEC), CONICET-UNL, Santa Fe, Argentina
| |
Collapse
|
112
|
Khamis F, Al Naabi H, Al Lawati A, Ambusaidi Z, Al Sharji M, Al Barwani U, Pandak N, Al Balushi Z, Al Bahrani M, Al Salmi I, Al-Zakwani I. Randomized controlled open label trial on the use of favipiravir combined with inhaled interferon beta-1b in hospitalized patients with moderate to severe COVID-19 pneumonia. Int J Infect Dis 2021; 102:538-543. [PMID: 33181328 PMCID: PMC7833906 DOI: 10.1016/j.ijid.2020.11.008] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 11/03/2020] [Accepted: 11/04/2020] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVE To evaluate the therapeutic effectiveness of favipiravir combined with inhaled interferon beta-1b in adult patients hospitalized with moderate to severe COVID-19 pneumonia. METHODS A randomized, open-label controlled trial of oral favipiravir in adults hospitalized with moderate to severe COVID-19 pneumonia from June 22nd 2020 to August 13th 2020 was conducted. Patients were randomly assigned to receive either a combination of favipiravir with interferon beta-1b by inhalation aerosol or hydroxychloroquine (HCQ). The outcome endpoints included improvement in inflammatory markers, lower length of hospital stay (LOS), discharges and lower overall 14-day mortality. RESULTS A total of 89 patients underwent randomization with 49% (n = 44) assigned to favipiravir and 51% (n = 45) assigned HCQ. The overall mean age was 55 ± 14 years and 58% (n = 52) were males. There were no significant differences in the inflammatory biomarkers at hospital discharge between the two groups; C-reactive protein (p = 0.413), ferritin (p = 0.968), lactate dehydrogenase (p = 0.259) and interleukin 6 (p = 0.410). There were also no significant differences between the two groups with regards to the overall LOS (7 vs 7 days; p = 0.948), transfers to the ICU (18.2% vs 17.8%; p = 0.960), discharges (65.9% vs 68.9%; p = 0.764) and overall mortality (11.4% vs 13.3%; p = 0.778). CONCLUSIONS No differences in clinical outcomes were found between favipiravir plus inhaled interferon beta-1b and hydroxychloroquine in adults hospitalized with moderate to severe COVID-19 pneumonia.
Collapse
Affiliation(s)
- Faryal Khamis
- Infection Diseases Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | - Hanan Al Naabi
- Acute Medicine Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | - Adil Al Lawati
- Acute Medicine Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | - Zaiyana Ambusaidi
- Acute Medicine Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | | | | | - Nenad Pandak
- Infection Diseases Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | - Zakariya Al Balushi
- Infection Diseases Unit, Department of Medicine, Royal Hospital, Muscat, Oman.
| | - Maher Al Bahrani
- Department of Anesthesia and Critical Care, Royal Hospital, Muscat, Oman.
| | - Issa Al Salmi
- Department of Nephrology, Royal Hospital, Muscat, Oman.
| | - Ibrahim Al-Zakwani
- Department of Pharmacology & Clinical Pharmacy, College of Medicine & Clinical Pharmacy, Sultan Qaboos University, Muscat, Oman.
| |
Collapse
|
113
|
Padmanabhan P, Desikan R, Dixit NM. Targeting TMPRSS2 and Cathepsin B/L together may be synergistic against SARS-CoV-2 infection. PLoS Comput Biol 2020; 16:e1008461. [PMID: 33290397 PMCID: PMC7748278 DOI: 10.1371/journal.pcbi.1008461] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/18/2020] [Accepted: 10/22/2020] [Indexed: 12/15/2022] Open
Abstract
The entry of SARS-CoV-2 into target cells requires the activation of its surface spike protein, S, by host proteases. The host serine protease TMPRSS2 and cysteine proteases Cathepsin B/L can activate S, making two independent entry pathways accessible to SARS-CoV-2. Blocking the proteases prevents SARS-CoV-2 entry in vitro. This blockade may be achieved in vivo through 'repurposing' drugs, a potential treatment option for COVID-19 that is now in clinical trials. Here, we found, surprisingly, that drugs targeting the two pathways, although independent, could display strong synergy in blocking virus entry. We predicted this synergy first using a mathematical model of SARS-CoV-2 entry and dynamics in vitro. The model considered the two pathways explicitly, let the entry efficiency through a pathway depend on the corresponding protease expression level, which varied across cells, and let inhibitors compromise the efficiency in a dose-dependent manner. The synergy predicted was novel and arose from effects of the drugs at both the single cell and the cell population levels. Validating our predictions, available in vitro data on SARS-CoV-2 and SARS-CoV entry displayed this synergy. Further, analysing the data using our model, we estimated the relative usage of the two pathways and found it to vary widely across cell lines, suggesting that targeting both pathways in vivo may be important and synergistic given the broad tissue tropism of SARS-CoV-2. Our findings provide insights into SARS-CoV-2 entry into target cells and may help improve the deployability of drug combinations targeting host proteases required for the entry.
Collapse
Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queesnsland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Rajat Desikan
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, India
| | - Narendra M. Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bengaluru, India
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bengaluru, India
| |
Collapse
|
114
|
Xia H, Shi PY. Antagonism of Type I Interferon by Severe Acute Respiratory Syndrome Coronavirus 2. J Interferon Cytokine Res 2020; 40:543-548. [PMID: 33337934 PMCID: PMC7757701 DOI: 10.1089/jir.2020.0214] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2008] [Accepted: 11/14/2009] [Indexed: 12/21/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), warranting urgent study of the molecular mechanisms of SARS-CoV-2 infection and host immune response. Type I interferon (IFN-I) is a key component of host innate immune system responsible for eliminating the virus at the early stage of infection. In contrast, SARS-CoV-2 has evolved multiple strategies to evade innate immune response to facilitate viral replication, transmission, and pathogenesis. This review summarizes the recent progresses on SARS-CoV-2 proteins that antagonize host IFN-I production and/or signaling. These progresses have provided knowledge for new vaccine and antiviral development to prevent and control COVID-19.
Collapse
Affiliation(s)
- Hongjie Xia
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA
| | - Pei-Yong Shi
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA
- Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas, USA
- Sealy Institute for Vaccine Sciences, University of Texas Medical Branch, Galveston, Texas, USA
- Sealy Center for Structural Biology & Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas, USA
| |
Collapse
|
115
|
Sego TJ, Aponte-Serrano JO, Ferrari Gianlupi J, Heaps SR, Breithaupt K, Brusch L, Crawshaw J, Osborne JM, Quardokus EM, Plemper RK, Glazier JA. A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness. PLoS Comput Biol 2020; 16:e1008451. [PMID: 33347439 PMCID: PMC7785254 DOI: 10.1371/journal.pcbi.1008451] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 01/05/2021] [Accepted: 10/20/2020] [Indexed: 12/23/2022] Open
Abstract
Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding disease outcomes and optimizing therapies. Such simulations need to support continuous updating in response to rapid advances in understanding of infection mechanisms, and parallel development of components by multiple groups. We present an open-source platform for multiscale spatiotemporal simulation of an epithelial tissue, viral infection, cellular immune response and tissue damage, specifically designed to be modular and extensible to support continuous updating and parallel development. The base simulation of a simplified patch of epithelial tissue and immune response exhibits distinct patterns of infection dynamics from widespread infection, to recurrence, to clearance. Slower viral internalization and faster immune-cell recruitment slow infection and promote containment. Because antiviral drugs can have side effects and show reduced clinical effectiveness when given later during infection, we studied the effects on progression of treatment potency and time-of-first treatment after infection. In simulations, even a low potency therapy with a drug which reduces the replication rate of viral RNA greatly decreases the total tissue damage and virus burden when given near the beginning of infection. Many combinations of dosage and treatment time lead to stochastic outcomes, with some simulation replicas showing clearance or control (treatment success), while others show rapid infection of all epithelial cells (treatment failure). Thus, while a high potency therapy usually is less effective when given later, treatments at late times are occasionally effective. We illustrate how to extend the platform to model specific virus types (e.g., hepatitis C) and add additional cellular mechanisms (tissue recovery and variable cell susceptibility to infection), using our software modules and publicly-available software repository.
Collapse
Affiliation(s)
- T. J. Sego
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
| | - Josua O. Aponte-Serrano
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
| | - Juliano Ferrari Gianlupi
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
| | - Samuel R. Heaps
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
| | - Kira Breithaupt
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
- Cognitive Science Program, Indiana University, Bloomington, Indiana, United States of America
| | - Lutz Brusch
- Center for Information Services and High Performance Computing (ZIH), Technische Universität, Dresden, Germany
| | - Jessica Crawshaw
- School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia
| | - James M. Osborne
- School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia
| | - Ellen M. Quardokus
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
| | - Richard K. Plemper
- Institute for Biomedical Sciences, Georgia State University, Atlanta, Georgia, United States of America
| | - James A. Glazier
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States of America
- Biocomplexity Institute, Indiana University, Bloomington, Indiana, United States of America
| |
Collapse
|
116
|
Metcalf CJE, Grenfell BT, Graham AL. Disentangling the dynamical underpinnings of differences in SARS-CoV-2 pathology using within-host ecological models. PLoS Pathog 2020; 16:e1009105. [PMID: 33306746 PMCID: PMC7732095 DOI: 10.1371/journal.ppat.1009105] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Health outcomes following infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) are remarkably variable. The way the virus spreads inside hosts, and how this spread interacts with host immunity and physiology, is likely to determine variation in health outcomes. Decades of data and dynamical analyses of how other viruses spread and interact with host cells could shed light on SARS-CoV-2 within-host trajectories. We review how common axes of variation in within-host dynamics and emergent pathology (such as age and sex) might be combined with ecological principles to understand the case of SARS-CoV-2. We highlight pitfalls in application of existing theoretical frameworks relevant to the complexity of the within-host context and frame the discussion in terms of growing knowledge of the biology of SARS-CoV-2. Viewing health outcomes for SARS-CoV-2 through the lens of ecological models underscores the value of repeated measures on individuals, especially since many lines of evidence suggest important contingence on trajectory.
Collapse
Affiliation(s)
- C. Jessica E. Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Princeton School of Public and International Affairs, Princeton University, New Jersey, United States of America
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Princeton School of Public and International Affairs, Princeton University, New Jersey, United States of America
| | - Andrea L. Graham
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| |
Collapse
|
117
|
Pharmacokinetic Basis of the Hydroxychloroquine Response in COVID-19: Implications for Therapy and Prevention. Eur J Drug Metab Pharmacokinet 2020; 45:715-723. [PMID: 32780273 PMCID: PMC7418279 DOI: 10.1007/s13318-020-00640-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND OBJECTIVES Chloroquine/hydroxychloroquine has recently been the subject of intense debate regarding its potential antiviral activity against SARS-Cov-2, the etiologic agent of COVID-19. Some report possible curative effects; others do not. Therefore, the objective of this study was to simulate possible scenarios of response to hydroxychloroquine in COVID-19 patients using mathematical modeling. METHODS To shed some light on this controversial topic, we simulated hydroxychloroquine-based interventions on virus/host cell dynamics using a basic system of previously published differential equations. Mathematical modeling was implemented using Python programming language v 3.7. RESULTS According to mathematical modeling, hydroxychloroquine may have an impact on the amplitude of the viral load peak and viral clearance if the drug is administered early enough (i.e., when the virus is still confined within the pharyngeal cavity). The effects of chloroquine/hydroxychloroquine may be fully explained only when also considering the capacity of this drug to increase the death rate of SARS-CoV-2-infected cells, in this case by enhancing the cell-mediated immune response. CONCLUSIONS These considerations may not only be applied to chloroquine/hydroxychloroquine but may have more general implications for development of anti-COVID-19 combination therapies and prevention strategies through an increased death rate of the infected cells.
Collapse
|
118
|
Dobrovolny HM. Quantifying the effect of remdesivir in rhesus macaques infected with SARS-CoV-2. Virology 2020; 550:61-69. [PMID: 32882638 PMCID: PMC7443325 DOI: 10.1016/j.virol.2020.07.015] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/28/2020] [Accepted: 07/21/2020] [Indexed: 02/08/2023]
Abstract
The world is in the midst of a pandemic caused by a novel coronavirus and is desperately searching for possible treatments. The antiviral remdesivir has shown some effectiveness against SARS-CoV-2 in vitro and in a recent animal study. We use data from a study of remdesivir in rhesus macaques to fit a viral kinetics model in an effort to determine the most appropriate mathematical descripton of the effect of remdesivir. We find statistically significant differences in the viral decay rate and use this to inform a possible mathematical formulation of the effect of remdesivir. Unfortunately, this model formulation suggests that the application of remdesivir will lengthen SARS-CoV-2 infections, putting into question its potential clinical benefit.
Collapse
Affiliation(s)
- Hana M Dobrovolny
- Department of Physics and Astronomy, Texas Christian University, Fort Worth, TX, USA.
| |
Collapse
|
119
|
Heimfarth L, Serafini MR, Martins-Filho PR, Quintans JDSS, Quintans-Júnior LJ. Drug repurposing and cytokine management in response to COVID-19: A review. Int Immunopharmacol 2020; 88:106947. [PMID: 32919216 PMCID: PMC7457938 DOI: 10.1016/j.intimp.2020.106947] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/26/2020] [Accepted: 08/26/2020] [Indexed: 02/07/2023]
Abstract
Coronavirus disease 2019 (COVID-19), the infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an aggressive disease that attacks the respiratory tract and has a higher fatality rate than seasonal influenza. The COVID-19 pandemic is a global health crisis, and no specific therapy or drug has been formally recommended for use against SARS-CoV-2 infection. In this context, it is a rational strategy to investigate the repurposing of existing drugs to use in the treatment of COVID-19 patients. In the meantime, the medical community is trialing several therapies that target various antiviral and immunomodulating mechanisms to use against the infection. There is no doubt that antiviral and supportive treatments are important in the treatment of COVID-19 patients, but anti-inflammatory therapy also plays a pivotal role in the management COVID-19 patients due to its ability to prevent further injury and organ damage or failure. In this review, we identified drugs that could modulate cytokines levels and play a part in the management of COVID-19. Several drugs that possess an anti-inflammatory profile in others illnesses have been studied in respect of their potential utility in the treatment of the hyperinflammation induced by SAR-COV-2 infection. We highlight a number of antivirals, anti-rheumatic, anti-inflammatory, antineoplastic and antiparasitic drugs that have been found to mitigate cytokine production and consequently attenuate the "cytokine storm" induced by SARS-CoV-2. Reduced hyperinflammation can attenuate multiple organ failure, and even reduce the mortality associated with severe COVID-19. In this context, despite their current unproven clinical efficacy in relation to the current pandemic, the repurposing of drugs with anti-inflammatory activity to use in the treatment of COVID-19 has become a topic of great interest.
Collapse
Affiliation(s)
- Luana Heimfarth
- Laboratory of Neuroscience and Pharmacological Assays (LANEF), São Cristóvão, SE 49100-000 Brazil; Graduate Program of Health Sciences (PPGCS), São Cristóvão, SE 49100-000 Brazil.
| | - Mairim Russo Serafini
- Graduate Program of Pharmaceutical Sciences (PPGCF). Federal University of Sergipe (UFS), São Cristóvão, SE 49100-000 Brazil
| | | | - Jullyana de Souza Siqueira Quintans
- Laboratory of Neuroscience and Pharmacological Assays (LANEF), São Cristóvão, SE 49100-000 Brazil; Graduate Program of Health Sciences (PPGCS), São Cristóvão, SE 49100-000 Brazil
| | - Lucindo José Quintans-Júnior
- Laboratory of Neuroscience and Pharmacological Assays (LANEF), São Cristóvão, SE 49100-000 Brazil; Graduate Program of Health Sciences (PPGCS), São Cristóvão, SE 49100-000 Brazil; Graduate Program of Pharmaceutical Sciences (PPGCF). Federal University of Sergipe (UFS), São Cristóvão, SE 49100-000 Brazil
| |
Collapse
|
120
|
Goyal A, Cardozo-Ojeda EF, Schiffer JT. Potency and timing of antiviral therapy as determinants of duration of SARS-CoV-2 shedding and intensity of inflammatory response. SCIENCE ADVANCES 2020; 6:sciadv.abc7112. [PMID: 33097472 DOI: 10.1101/2020.04.10.20061325] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 10/07/2020] [Indexed: 05/27/2023]
Abstract
To affect the COVID-19 pandemic, lifesaving antiviral therapies must be identified. The number of clinical trials that can be performed is limited. We developed mathematical models to project multiple therapeutic approaches. Our models recapitulate off-treatment viral dynamics and predict a three-phase immune response. Simulated treatment with remdesivir, selinexor, neutralizing antibodies, or cellular immunotherapy demonstrates that rapid viral elimination is possible if in vivo potency is sufficiently high. Therapies dosed soon after peak viral load when symptoms develop may decrease shedding duration and immune response intensity but have little effect on viral area under the curve (AUC), which is driven by high early viral loads. Potent therapy dosed before viral peak during presymptomatic infection could lower AUC. Drug resistance may emerge with a moderately potent agent dosed before viral peak. Our results support early treatment for COVID-19 if shedding duration, not AUC, is most predictive of clinical severity.
Collapse
Affiliation(s)
- Ashish Goyal
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - E Fabian Cardozo-Ojeda
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Joshua T Schiffer
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
121
|
Goyal A, Cardozo-Ojeda EF, Schiffer JT. Potency and timing of antiviral therapy as determinants of duration of SARS-CoV-2 shedding and intensity of inflammatory response. SCIENCE ADVANCES 2020; 6:eabc7112. [PMID: 33097472 PMCID: PMC7679107 DOI: 10.1126/sciadv.abc7112] [Citation(s) in RCA: 100] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 10/07/2020] [Indexed: 05/18/2023]
Abstract
To affect the COVID-19 pandemic, lifesaving antiviral therapies must be identified. The number of clinical trials that can be performed is limited. We developed mathematical models to project multiple therapeutic approaches. Our models recapitulate off-treatment viral dynamics and predict a three-phase immune response. Simulated treatment with remdesivir, selinexor, neutralizing antibodies, or cellular immunotherapy demonstrates that rapid viral elimination is possible if in vivo potency is sufficiently high. Therapies dosed soon after peak viral load when symptoms develop may decrease shedding duration and immune response intensity but have little effect on viral area under the curve (AUC), which is driven by high early viral loads. Potent therapy dosed before viral peak during presymptomatic infection could lower AUC. Drug resistance may emerge with a moderately potent agent dosed before viral peak. Our results support early treatment for COVID-19 if shedding duration, not AUC, is most predictive of clinical severity.
Collapse
Affiliation(s)
- Ashish Goyal
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - E Fabian Cardozo-Ojeda
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Joshua T Schiffer
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
122
|
Fain B, Dobrovolny HM. Initial Inoculum and the Severity of COVID-19: A Mathematical Modeling Study of the Dose-Response of SARS-CoV-2 Infections. EPIDEMIOLGIA (BASEL, SWITZERLAND) 2020; 1:5-15. [PMID: 36417207 PMCID: PMC9620883 DOI: 10.3390/epidemiologia1010003] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 09/30/2020] [Accepted: 10/14/2020] [Indexed: 12/14/2022]
Abstract
SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) causes a variety of responses in those who contract the virus, ranging from asymptomatic infections to acute respiratory failure and death. While there are likely multiple mechanisms triggering severe disease, one potential cause of severe disease is the size of the initial inoculum. For other respiratory diseases, larger initial doses lead to more severe outcomes. We investigate whether there is a similar link for SARS-CoV-2 infections using the combination of an agent-based model (ABM) and a partial differential equation model (PDM). We use the model to examine the viral time course for different sizes of initial inocula, generating dose-response curves for peak viral load, time of viral peak, viral growth rate, infection duration, and area under the viral titer curve. We find that large initial inocula lead to short infections, but with higher viral titer peaks; and that smaller initial inocula lower the viral titer peak, but make the infection last longer.
Collapse
|
123
|
Sego TJ, Aponte-Serrano JO, Gianlupi JF, Heaps SR, Breithaupt K, Brusch L, Crawshaw J, Osborne JM, Quardokus EM, Plemper RK, Glazier JA. A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness: A multiscale model of viral infection in epithelial tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.04.27.064139. [PMID: 32511367 PMCID: PMC7263495 DOI: 10.1101/2020.04.27.064139] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding disease outcomes and optimizing therapies. Such simulations need to support continuous updating in response to rapid advances in understanding of infection mechanisms, and parallel development of components by multiple groups. We present an open-source platform for multiscale spatiotemporal simulation of an epithelial tissue, viral infection, cellular immune response and tissue damage, specifically designed to be modular and extensible to support continuous updating and parallel development. The base simulation of a simplified patch of epithelial tissue and immune response exhibits distinct patterns of infection dynamics from widespread infection, to recurrence, to clearance. Slower viral internalization and faster immune-cell recruitment slow infection and promote containment. Because antiviral drugs can have side effects and show reduced clinical effectiveness when given later during infection, we studied the effects on progression of treatment potency and time-of-first treatment after infection. In simulations, even a low potency therapy with a drug which reduces the replication rate of viral RNA greatly decreases the total tissue damage and virus burden when given near the beginning of infection. Many combinations of dosage and treatment time lead to stochastic outcomes, with some simulation replicas showing clearance or control (treatment success), while others show rapid infection of all epithelial cells (treatment failure). Thus, while a high potency therapy usually is less effective when given later, treatments at late times are occasionally effective. We illustrate how to extend the platform to model specific virus types (e.g., hepatitis C) and add additional cellular mechanisms (tissue recovery and variable cell susceptibility to infection), using our software modules and publicly-available software repository.
Collapse
Affiliation(s)
- T J Sego
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - Josua O Aponte-Serrano
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - Juliano Ferrari Gianlupi
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| | - Samuel R Heaps
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Kira Breithaupt
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
| | - Lutz Brusch
- Center for Information Services and High Performance Computing (ZIH), Technische Universität Dresden, Germany
| | - Jessica Crawshaw
- School of Mathematics and Statistics, University of Melbourne, Melbourne, 3010, Australia
| | - James M Osborne
- School of Mathematics and Statistics, University of Melbourne, Melbourne, 3010, Australia
| | - Ellen M Quardokus
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Richard K Plemper
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, USA
| | - James A Glazier
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Biocomplexity Institute, Indiana University, Bloomington, IN, USA
| |
Collapse
|
124
|
Voutouri C, Nikmaneshi MR, Hardin CC, Patel AB, Verma A, Khandekar MJ, Dutta S, Stylianopoulos T, Munn LL, Jain RK. In silico dynamics of COVID-19 phenotypes for optimizing clinical management. RESEARCH SQUARE 2020:rs.3.rs-71086. [PMID: 32908974 PMCID: PMC7480033 DOI: 10.21203/rs.3.rs-71086/v1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the SARS-CoV-2 virus infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of co-morbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age, co-morbidities such as obesity, diabetes, and hypertension, and dysregulated immune response 1,2 . We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8 + T cells and sufficient control of the innate immune response. Furthermore, the best treatment -or combination of treatments - depends on the pre-infection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.
Collapse
|
125
|
Oscanoa TJ, Romero-Ortuno R, Carvajal A, Savarino A. A pharmacological perspective of chloroquine in SARS-CoV-2 infection: An old drug for the fight against a new coronavirus? Int J Antimicrob Agents 2020; 56:106078. [PMID: 32629115 PMCID: PMC7334645 DOI: 10.1016/j.ijantimicag.2020.106078] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 06/24/2020] [Accepted: 06/28/2020] [Indexed: 02/06/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is having serious consequences on health and the economy worldwide. All evidence-based treatment strategies need to be considered to combat this new virus. Drugs need to be considered on scientific grounds of efficacy, safety and cost. Chloroquine (CQ) and hydroxychloroquine (HCQ) are old drugs used in the treatment of malaria. Moreover, their antiviral properties have been previously studied, including against coronaviruses, where evidence of efficacy has been found. In the current race against time triggered by the COVID-19 pandemic, the search for new antivirals is very important. However, consideration should be given to old drugs with known anti-coronavirus activity, such as CQ and HCQ. These could be integrated into current treatment strategies while novel treatments are awaited, also in light of the fact that they display an anticoagulant effect that facilitates the activity of low-molecular-weight heparin, aimed at preventing acute respiratory distress syndrome (ARDS)-associated thrombotic events. The safety of CQ and HCQ has been studied for over 50 years, however recently published data raise concerns for cardiac toxicity of CQ/HCQ in patients with COVID-19. This review also re-examines the real information provided by some of the published alarming reports, although concluding that cardiac toxicity should in any case be stringently monitored in patients receiving CQ/HCQ.
Collapse
Affiliation(s)
- Teodoro J Oscanoa
- Department of Pharmacology, Facultad de Medicina, Universidad Nacional Mayor de San Marcos, Lima, Peru, and Drug Safety Research Center, Facultad de Medicina Humana, Universidad de San Martín de Porres, Hospital Almenara, ESSALUD, Lima, Peru.
| | - Roman Romero-Ortuno
- Discipline of Medical Gerontology, Mercer's Institute for Successful Ageing, St James's Hospital, Dublin, Ireland, and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Alfonso Carvajal
- Centro de Estudios sobre la Seguridad de los Medicamentos (CESME), Universidad de Valladolid, Valladolid, Spain
| | - Andrea Savarino
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| |
Collapse
|
126
|
Rosenbloom DS, Zhao P, Sinha V. Initiation of Antiviral Treatment in SARS-CoV2: Modeling Viral Dynamics and Drug Properties. CPT Pharmacometrics Syst Pharmacol 2020; 9:481-483. [PMID: 32700405 PMCID: PMC7405045 DOI: 10.1002/psp4.12550] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 07/20/2020] [Indexed: 12/30/2022] Open
Affiliation(s)
- Daniel Scholes Rosenbloom
- Quantitative Pharmacology and Pharmacometrics, Pharmacokinetics, Pharmacodynamics, and Drug Metabolism (PPDM), Merck & Co., Inc., Kenilworth, New Jersey, USA
| | - Ping Zhao
- The Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Vikram Sinha
- Quantitative Pharmacology and Pharmacometrics, Pharmacokinetics, Pharmacodynamics, and Drug Metabolism (PPDM), Merck & Co., Inc., Kenilworth, New Jersey, USA
| |
Collapse
|
127
|
Fang FC, Schooley RT. Treatment of COVID-19 - Evidence-Based or Personalized Medicine? Clin Infect Dis 2020; 74:149-151. [PMID: 32667978 PMCID: PMC7454443 DOI: 10.1093/cid/ciaa996] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 07/10/2020] [Indexed: 12/28/2022] Open
Affiliation(s)
- Ferric C Fang
- Departments of Laboratory Medicine and Microbiology, University of Washington School of Medicine, Seattle, Washington, USA
| | - Robert T Schooley
- Division of Infectious Diseases and Global Public Health, Center for Innovative Phage Applications and Therapeutics, University of California, San Diego, San Diego, California, USA
| |
Collapse
|
128
|
Hughes JH, Sweeney K, Ahadieh S, Ouellet D. Predictions of Systemic, Intracellular, and Lung Concentrations of Azithromycin With Different Dosing Regimens Used in COVID-19 Clinical Trials. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2020; 9:435-443. [PMID: 32511867 PMCID: PMC7300789 DOI: 10.1002/psp4.12537] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 05/29/2020] [Indexed: 12/23/2022]
Abstract
Azithromycin (AZ), a broad-spectrum macrolide antibiotic, is being investigated in patients with coronavirus disease 2019 (COVID-19). A population pharmacokinetic model was implemented to predict lung, intracellular poly/mononuclear cell (peripheral blood monocyte (PBM)/polymorphonuclear leukocyte (PML)), and alveolar macrophage (AM) concentrations using published data and compared against preclinical effective concentration 90% (EC90 ) for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). The final model described the data reported in eight publications adequately. Consistent with its known properties, concentrations were higher in AM and PBM/PML, followed by lung tissue, and lowest systemically. Simulated PBM/PML concentrations exceeded EC90 following the first dose and for ~ 14 days following 500 mg q.d. for 3 days or 500 mg q.d. for 1 day/250 mg q.d. on days 2-5, 10 days following a single 1,000 mg dose, and for > 20 days with 500 mg q.d. for 10 days. AM concentrations exceeded the 90% inhibitory concentration for > 20 days for all regimens. These data will better inform optimization of dosing regimens for AZ clinical trials.
Collapse
Affiliation(s)
- Jim H Hughes
- Pfizer Global Research and Development, Groton, Connecticut, USA
| | - Kevin Sweeney
- Pfizer Global Research and Development, Groton, Connecticut, USA
| | - Sima Ahadieh
- Pfizer Global Research and Development, Groton, Connecticut, USA
| | - Daniele Ouellet
- Pfizer Global Research and Development, Groton, Connecticut, USA.,Pfizer Global Research and Development, Collegeville, Pennsylvania, USA
| |
Collapse
|
129
|
Hartman D, Kern S, Brown F, Minton SK, Rayner CR. Time to Step Up: A Call to Action For the Clinical and Quantitative Pharmacology Community to Accelerate Therapeutics for COVID-19. Clin Transl Sci 2020; 13:646-648. [PMID: 32441462 PMCID: PMC7280646 DOI: 10.1111/cts.12824] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 05/11/2020] [Indexed: 12/19/2022] Open
Abstract
The global response to finding therapeutics for coronavirus disease 2019 (COVID‐19) is chaotic even if well intentioned. There is an opportunity, but more importantly, an obligation for the global clinical and quantitative pharmacology community to come together and use our state‐of‐the‐art tools and expertise to help society accelerate therapeutics to fight COVID‐19. This brief commentary is a call to action and highlights how the global pharmacology community should contribute to the COVID‐19 pandemic and prepare for future pandemics.
Collapse
Affiliation(s)
- Dan Hartman
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Steven Kern
- Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Fran Brown
- Certara Inc., Princeton, New Jersey, USA
| | | | | |
Collapse
|