Modeling HIV Dynamics Under Combination Therapy with Inducers and Antibodies
A mathematical model is proposed to simulate the “shock-kill” strategy where broadly neutralizing antibodies (bNAbs) are injected with a combination of HIV latency activators to reduce persistent HIV reservoirs. The basic reproductive ratio of virus is computed to extrapolate how the combinational t...
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| Veröffentlicht in: | Bulletin of mathematical biology 2019-07, Vol.81 (7), p.2625-2648 |
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| creator | Yan, Chao Wang, Wendi |
| description | A mathematical model is proposed to simulate the “shock-kill” strategy where broadly neutralizing antibodies (bNAbs) are injected with a combination of HIV latency activators to reduce persistent HIV reservoirs. The basic reproductive ratio of virus is computed to extrapolate how the combinational therapy of inducers and antibodies affects the persistence of HIV infection. Numerical simulations demonstrate that a proper combination of inducers and bNAbs can drive the basic reproductive ratio below unity. Interestingly, it is found that a longer dosage interval leads to the higher HIV survival opportunity and a smaller dosage interval is preferred, which is fundamental to design an optimal therapeutic scheme. Further simulations reveal the conditions under which the joint therapy of inducer and antibodies induces a large extension of viral rebound time, which highlights the mechanism of delayed viral rebound from the experiment (Halper-Stromberg et al. in Cell 158:989–999,
2014
). Optimal time for cessation of treatment is also analyzed to aid practical applications. |
| doi_str_mv | 10.1007/s11538-019-00621-0 |
| format | Article |
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2014
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2014
). Optimal time for cessation of treatment is also analyzed to aid practical applications.</description><subject>Anti-HIV Agents - administration & dosage</subject><subject>Antibodies</subject><subject>Antibodies, Neutralizing - administration & dosage</subject><subject>Antiretroviral Therapy, Highly Active</subject><subject>Basic Reproduction Number</subject><subject>Cell Biology</subject><subject>Combined Modality Therapy</subject><subject>Computer Simulation</subject><subject>Dosage</subject><subject>HIV</subject><subject>HIV Antibodies - administration & dosage</subject><subject>HIV Infections - drug therapy</subject><subject>HIV Infections - immunology</subject><subject>HIV Infections - therapy</subject><subject>HIV-1 - drug effects</subject><subject>HIV-1 - immunology</subject><subject>HIV-1 - physiology</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Immunoglobulins</subject><subject>Latency</subject><subject>Life Sciences</subject><subject>Mathematical and Computational Biology</subject><subject>Mathematical Concepts</subject><subject>Mathematical models</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Models, Biological</subject><subject>T-Lymphocytes - drug effects</subject><subject>T-Lymphocytes - immunology</subject><subject>T-Lymphocytes - virology</subject><subject>Therapy</subject><subject>Virus Latency - drug effects</subject><subject>Virus Latency - immunology</subject><subject>Viruses</subject><issn>0092-8240</issn><issn>1522-9602</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEFPIyEYQMlGo93qH_BgSLx4mfUDBhiOpruuTWq8WK-EAqOYDlNhJqb_fum2u5t42BMH3vfgewhdEPhGAORNJoSzpgKiKgBBSQVf0IRwSislgB6hCYCiVUNrOEVfc36DMqSYOkGnjBBBOFcTtHjonV-H-ILv58_4-zaaLtiMl9H5hGd9twrRDKGP-OnVJ7PZ4o8wvOJ5dKP1KWMTHb6NQ1j1Lvh8ho5bs87-_HBO0fLux9Psvlo8_pzPbheVZZIPVU1MLRlxlLtaEMtr2aq2YUpwVfZQTNoahFQrZ1onPfXOq5oy0QirqKWsYVN0vfduUv8--jzoLmTr12sTfT9mTSnjILgkUNCrT-hbP6ZYflcoTqWE4i0U3VM29Tkn3-pNCp1JW01A71rrfWtdWuvfrfVOfXlQj6vOu78jf-IWgO2BXK7ii0__3v6P9hdjf4bx</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Yan, Chao</creator><creator>Wang, Wendi</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SS</scope><scope>7TK</scope><scope>JQ2</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-4741-7789</orcidid></search><sort><creationdate>20190701</creationdate><title>Modeling HIV Dynamics Under Combination Therapy with Inducers and Antibodies</title><author>Yan, Chao ; Wang, Wendi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-41a4731d25d461c547f9f839659006937c40679bdafd7e2ede9423686c92c2383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Anti-HIV Agents - administration & dosage</topic><topic>Antibodies</topic><topic>Antibodies, Neutralizing - administration & dosage</topic><topic>Antiretroviral Therapy, Highly Active</topic><topic>Basic Reproduction Number</topic><topic>Cell Biology</topic><topic>Combined Modality Therapy</topic><topic>Computer Simulation</topic><topic>Dosage</topic><topic>HIV</topic><topic>HIV Antibodies - administration & dosage</topic><topic>HIV Infections - drug therapy</topic><topic>HIV Infections - immunology</topic><topic>HIV Infections - therapy</topic><topic>HIV-1 - drug effects</topic><topic>HIV-1 - immunology</topic><topic>HIV-1 - physiology</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>Immunoglobulins</topic><topic>Latency</topic><topic>Life Sciences</topic><topic>Mathematical and Computational Biology</topic><topic>Mathematical Concepts</topic><topic>Mathematical models</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Models, Biological</topic><topic>T-Lymphocytes - drug effects</topic><topic>T-Lymphocytes - immunology</topic><topic>T-Lymphocytes - virology</topic><topic>Therapy</topic><topic>Virus Latency - drug effects</topic><topic>Virus Latency - immunology</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yan, Chao</creatorcontrib><creatorcontrib>Wang, Wendi</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Bulletin of mathematical biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yan, Chao</au><au>Wang, Wendi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling HIV Dynamics Under Combination Therapy with Inducers and Antibodies</atitle><jtitle>Bulletin of mathematical biology</jtitle><stitle>Bull Math Biol</stitle><addtitle>Bull Math Biol</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>81</volume><issue>7</issue><spage>2625</spage><epage>2648</epage><pages>2625-2648</pages><issn>0092-8240</issn><eissn>1522-9602</eissn><abstract>A mathematical model is proposed to simulate the “shock-kill” strategy where broadly neutralizing antibodies (bNAbs) are injected with a combination of HIV latency activators to reduce persistent HIV reservoirs. 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2014
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| subjects | Anti-HIV Agents - administration & dosage Antibodies Antibodies, Neutralizing - administration & dosage Antiretroviral Therapy, Highly Active Basic Reproduction Number Cell Biology Combined Modality Therapy Computer Simulation Dosage HIV HIV Antibodies - administration & dosage HIV Infections - drug therapy HIV Infections - immunology HIV Infections - therapy HIV-1 - drug effects HIV-1 - immunology HIV-1 - physiology Human immunodeficiency virus Humans Immunoglobulins Latency Life Sciences Mathematical and Computational Biology Mathematical Concepts Mathematical models Mathematics Mathematics and Statistics Models, Biological T-Lymphocytes - drug effects T-Lymphocytes - immunology T-Lymphocytes - virology Therapy Virus Latency - drug effects Virus Latency - immunology Viruses |
| title | Modeling HIV Dynamics Under Combination Therapy with Inducers and Antibodies |
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