Multiscale in silico lung modeling strategies for aerosol inhalation therapy and drug delivery
Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering rea...
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| Published in | Current opinion in biomedical engineering Vol. 11; pp. 130 - 136 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Elsevier Inc
01.09.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2468-4511 2468-4511 |
| DOI | 10.1016/j.cobme.2019.11.003 |
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| Abstract | Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of ‘brute force’ simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent in silico studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such in silico strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations. |
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| AbstractList | Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of ‘brute force’ simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent
in silico
studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such
in silico
strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations. Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of ‘brute force’ simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent in silico studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such in silico strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations. Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of 'brute force' simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations. Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of 'brute force' simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent in silico studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such in silico strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations.Inhalation therapy is a hallmark of modern respiratory medicine. Over recent years, computational fluid-particle dynamics (CFPD) simulations of respiratory airflows and aerosol deposition in the lungs have rapidly developed into an increasingly mature research field in the biomedical engineering realm, owing, among others, to tremendous advances in computational capabilities and available resources. Despite such progress, the intrinsic anatomical and physiological complexity of the lungs prevents the straightforward implementation of 'brute force' simulation strategies applied across the entire pulmonary tract. Here, we discuss how knowledge gathered from recent in silico studies can be purposefully leveraged to design efficient hybrid multiscale lung models and explore quantitatively via computational fluid-particle dynamics inhalation therapy outcomes. In contrast to the efforts geared toward patient-specific applications, we argue instead that such in silico strategies hold tremendous promise for broad inter-subject variability studies that can help foster the development of clinically efficient inhalation therapies across large human patient populations. |
| Author | Kassinos, Stavros C. Koullapis, Pantelis Ollson, Bo Sznitman, Josué |
| AuthorAffiliation | 3 Department of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa 32000, Israel 1 Computational Sciences Laboratory (UCY-CompSci), Department of Mechanical and Manufacturing Engineering, University of Cyprus, Kallipoleos Avenue 75, Nicosia 1678, Cyprus 2 Emmace Consulting AB, SE223 63 Lund, Sweden |
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| Author_xml | – sequence: 1 givenname: Pantelis surname: Koullapis fullname: Koullapis, Pantelis organization: Computational Sciences Laboratory (UCY-CompSci), Department of Mechanical and Manufacturing Engineering, University of Cyprus, Kallipoleos Avenue 75, Nicosia 1678, Cyprus – sequence: 2 givenname: Bo orcidid: 0000-0003-4042-3086 surname: Ollson fullname: Ollson, Bo organization: Emmace Consulting AB, SE223 63 Lund, Sweden – sequence: 3 givenname: Stavros C. surname: Kassinos fullname: Kassinos, Stavros C. organization: Computational Sciences Laboratory (UCY-CompSci), Department of Mechanical and Manufacturing Engineering, University of Cyprus, Kallipoleos Avenue 75, Nicosia 1678, Cyprus – sequence: 4 givenname: Josué surname: Sznitman fullname: Sznitman, Josué email: sznitman@bm.technion.ac.il organization: Department of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa 32000, Israel |
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| Title | Multiscale in silico lung modeling strategies for aerosol inhalation therapy and drug delivery |
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