Meta-analysis of material properties influencing nanoparticle plasma pharmacokinetics
[Display omitted] Thorough characterization of the plasma pharmacokinetics (PK) is a critical step in clinical development of novel therapeutics and is routinely performed for small molecules and biologics. However, there is a paucity of even basic characterization of PK for nanoparticle-based drug...
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Veröffentlicht in: | International journal of pharmaceutics 2023-05, Vol.639, p.122951-122951, Article 122951 |
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container_title | International journal of pharmaceutics |
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creator | Macedo, Briana Patel, Manthan Zaleski, Michael H. Mody, Parth Ma, Xiaonan Mei, Patrick Myerson, Jacob W. Brenner, Jacob S. Glassman, Patrick M. |
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Thorough characterization of the plasma pharmacokinetics (PK) is a critical step in clinical development of novel therapeutics and is routinely performed for small molecules and biologics. However, there is a paucity of even basic characterization of PK for nanoparticle-based drug delivery systems. This has led to untested generalizations about how nanoparticle properties govern PK. Here, we present a meta-analysis of 100 nanoparticle formulations following IV administration in mice to identify any correlations between four PK parameters derived by non-compartmental analysis (NCA) and four cardinal properties of nanoparticles: PEGylation, zeta potential, size, and material. There was a statistically significant difference between the PK of particles stratified by nanoparticle properties. However, single linear regression between these properties and PK parameters showed poor predictability (r2 0.38, except for t1/2). This suggests that no single nanoparticle property alone is even moderately predictive of PK, while the combination of multiple nanoparticle features does provide moderate predictive power. Improved reporting of nanoparticle properties will enable more accurate comparison between nanoformulations and will enhance our ability to predict in vivo behavior and design optimal nanoparticles. |
doi_str_mv | 10.1016/j.ijpharm.2023.122951 |
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Thorough characterization of the plasma pharmacokinetics (PK) is a critical step in clinical development of novel therapeutics and is routinely performed for small molecules and biologics. However, there is a paucity of even basic characterization of PK for nanoparticle-based drug delivery systems. This has led to untested generalizations about how nanoparticle properties govern PK. Here, we present a meta-analysis of 100 nanoparticle formulations following IV administration in mice to identify any correlations between four PK parameters derived by non-compartmental analysis (NCA) and four cardinal properties of nanoparticles: PEGylation, zeta potential, size, and material. There was a statistically significant difference between the PK of particles stratified by nanoparticle properties. However, single linear regression between these properties and PK parameters showed poor predictability (r2 < 0.10 for all analyses), while multivariate regressions showed improved predictability (r2 > 0.38, except for t1/2). This suggests that no single nanoparticle property alone is even moderately predictive of PK, while the combination of multiple nanoparticle features does provide moderate predictive power. Improved reporting of nanoparticle properties will enable more accurate comparison between nanoformulations and will enhance our ability to predict in vivo behavior and design optimal nanoparticles.</description><identifier>ISSN: 0378-5173</identifier><identifier>EISSN: 1873-3476</identifier><identifier>DOI: 10.1016/j.ijpharm.2023.122951</identifier><identifier>PMID: 37059242</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Animals ; Drug Compounding ; Meta-analysis ; Mice ; Nanoparticles ; Non-compartmental analysis ; Pharmacokinetics</subject><ispartof>International journal of pharmaceutics, 2023-05, Vol.639, p.122951-122951, Article 122951</ispartof><rights>2023 Elsevier B.V.</rights><rights>Copyright © 2023 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-dd4f573940669539d2e6016b75180b0f2b52b214261597f65b56f7c8ce653a53</citedby><cites>FETCH-LOGICAL-c365t-dd4f573940669539d2e6016b75180b0f2b52b214261597f65b56f7c8ce653a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ijpharm.2023.122951$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37059242$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Macedo, Briana</creatorcontrib><creatorcontrib>Patel, Manthan</creatorcontrib><creatorcontrib>Zaleski, Michael H.</creatorcontrib><creatorcontrib>Mody, Parth</creatorcontrib><creatorcontrib>Ma, Xiaonan</creatorcontrib><creatorcontrib>Mei, Patrick</creatorcontrib><creatorcontrib>Myerson, Jacob W.</creatorcontrib><creatorcontrib>Brenner, Jacob S.</creatorcontrib><creatorcontrib>Glassman, Patrick M.</creatorcontrib><title>Meta-analysis of material properties influencing nanoparticle plasma pharmacokinetics</title><title>International journal of pharmaceutics</title><addtitle>Int J Pharm</addtitle><description>[Display omitted]
Thorough characterization of the plasma pharmacokinetics (PK) is a critical step in clinical development of novel therapeutics and is routinely performed for small molecules and biologics. However, there is a paucity of even basic characterization of PK for nanoparticle-based drug delivery systems. This has led to untested generalizations about how nanoparticle properties govern PK. Here, we present a meta-analysis of 100 nanoparticle formulations following IV administration in mice to identify any correlations between four PK parameters derived by non-compartmental analysis (NCA) and four cardinal properties of nanoparticles: PEGylation, zeta potential, size, and material. There was a statistically significant difference between the PK of particles stratified by nanoparticle properties. However, single linear regression between these properties and PK parameters showed poor predictability (r2 < 0.10 for all analyses), while multivariate regressions showed improved predictability (r2 > 0.38, except for t1/2). This suggests that no single nanoparticle property alone is even moderately predictive of PK, while the combination of multiple nanoparticle features does provide moderate predictive power. Improved reporting of nanoparticle properties will enable more accurate comparison between nanoformulations and will enhance our ability to predict in vivo behavior and design optimal nanoparticles.</description><subject>Animals</subject><subject>Drug Compounding</subject><subject>Meta-analysis</subject><subject>Mice</subject><subject>Nanoparticles</subject><subject>Non-compartmental analysis</subject><subject>Pharmacokinetics</subject><issn>0378-5173</issn><issn>1873-3476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkMtOwzAQRS0EoqXwCaAs2ST4EdvJCiHESypiU9aW40zAIS_sBKl_j0sKW1YjzdyZe-cgdE5wQjARV3Vi6-FduzahmLKEUJpzcoCWJJMsZqkUh2iJmcxiTiRboBPva4yxoIQdowWTmOc0pUv0-gyjjnWnm623PuqrqNUjOKubaHD9AG604CPbVc0EnbHdW9Tprh906JsGoqHRvtXRTxBt-g_bQRj4U3RU6cbD2b6u0Ob-bnP7GK9fHp5ub9axYYKPcVmmFZcsT7EQOWd5SUGE3wrJSYYLXNGC04KSlArCc1kJXnBRSZMZEJxpzlbocj4bon5O4EfVWm-gaXQH_eQVzTDJZc5SHKR8lhrXe--gUoOzrXZbRbDaAVW12gNVO6BqBhr2LvYWU9FC-bf1SzAIrmcBhD-_LDjljQ2ooLQOzKjK3v5j8Q1PmIno</recordid><startdate>20230525</startdate><enddate>20230525</enddate><creator>Macedo, Briana</creator><creator>Patel, Manthan</creator><creator>Zaleski, Michael H.</creator><creator>Mody, Parth</creator><creator>Ma, Xiaonan</creator><creator>Mei, Patrick</creator><creator>Myerson, Jacob W.</creator><creator>Brenner, Jacob S.</creator><creator>Glassman, Patrick M.</creator><general>Elsevier 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>7X8</scope></search><sort><creationdate>20230525</creationdate><title>Meta-analysis of material properties influencing nanoparticle plasma pharmacokinetics</title><author>Macedo, Briana ; Patel, Manthan ; Zaleski, Michael H. ; Mody, Parth ; Ma, Xiaonan ; Mei, Patrick ; Myerson, Jacob W. ; Brenner, Jacob S. ; Glassman, Patrick M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-dd4f573940669539d2e6016b75180b0f2b52b214261597f65b56f7c8ce653a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Animals</topic><topic>Drug Compounding</topic><topic>Meta-analysis</topic><topic>Mice</topic><topic>Nanoparticles</topic><topic>Non-compartmental analysis</topic><topic>Pharmacokinetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Macedo, Briana</creatorcontrib><creatorcontrib>Patel, Manthan</creatorcontrib><creatorcontrib>Zaleski, Michael H.</creatorcontrib><creatorcontrib>Mody, Parth</creatorcontrib><creatorcontrib>Ma, Xiaonan</creatorcontrib><creatorcontrib>Mei, Patrick</creatorcontrib><creatorcontrib>Myerson, Jacob W.</creatorcontrib><creatorcontrib>Brenner, Jacob S.</creatorcontrib><creatorcontrib>Glassman, Patrick M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of pharmaceutics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Macedo, Briana</au><au>Patel, Manthan</au><au>Zaleski, Michael H.</au><au>Mody, Parth</au><au>Ma, Xiaonan</au><au>Mei, Patrick</au><au>Myerson, Jacob W.</au><au>Brenner, Jacob S.</au><au>Glassman, Patrick M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Meta-analysis of material properties influencing nanoparticle plasma pharmacokinetics</atitle><jtitle>International journal of pharmaceutics</jtitle><addtitle>Int J Pharm</addtitle><date>2023-05-25</date><risdate>2023</risdate><volume>639</volume><spage>122951</spage><epage>122951</epage><pages>122951-122951</pages><artnum>122951</artnum><issn>0378-5173</issn><eissn>1873-3476</eissn><abstract>[Display omitted]
Thorough characterization of the plasma pharmacokinetics (PK) is a critical step in clinical development of novel therapeutics and is routinely performed for small molecules and biologics. However, there is a paucity of even basic characterization of PK for nanoparticle-based drug delivery systems. This has led to untested generalizations about how nanoparticle properties govern PK. Here, we present a meta-analysis of 100 nanoparticle formulations following IV administration in mice to identify any correlations between four PK parameters derived by non-compartmental analysis (NCA) and four cardinal properties of nanoparticles: PEGylation, zeta potential, size, and material. There was a statistically significant difference between the PK of particles stratified by nanoparticle properties. However, single linear regression between these properties and PK parameters showed poor predictability (r2 < 0.10 for all analyses), while multivariate regressions showed improved predictability (r2 > 0.38, except for t1/2). This suggests that no single nanoparticle property alone is even moderately predictive of PK, while the combination of multiple nanoparticle features does provide moderate predictive power. Improved reporting of nanoparticle properties will enable more accurate comparison between nanoformulations and will enhance our ability to predict in vivo behavior and design optimal nanoparticles.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>37059242</pmid><doi>10.1016/j.ijpharm.2023.122951</doi><tpages>1</tpages></addata></record> |
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subjects | Animals Drug Compounding Meta-analysis Mice Nanoparticles Non-compartmental analysis Pharmacokinetics |
title | Meta-analysis of material properties influencing nanoparticle plasma pharmacokinetics |
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