A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes
[Display omitted] In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described...
Gespeichert in:
| Veröffentlicht in: | International journal of pharmaceutics 2018-10, Vol.549 (1-2), p.415-435 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 435 |
|---|---|
| container_issue | 1-2 |
| container_start_page | 415 |
| container_title | International journal of pharmaceutics |
| container_volume | 549 |
| creator | Van Snick, Bernd Dhondt, Jens Pandelaere, Kenny Bertels, Johny Mertens, Roel Klingeleers, Didier Di Pretoro, Giustino Remon, Jean Paul Vervaet, Chris De Beer, Thomas Vanhoorne, Valérie |
| description | [Display omitted]
In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors. |
| doi_str_mv | 10.1016/j.ijpharm.2018.08.014 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2089858388</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0378517318305763</els_id><sourcerecordid>2089858388</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-a71cccc1b1ffe3222def5e10828bc7e883353ea5566c8d77b13740c00f31e8e93</originalsourceid><addsrcrecordid>eNqFkc9u3CAQxlHVqtls-witOPbiDWNsQ05RFDV_pEi5pGeEYZyyso0DeKN9krxucXeTa9BIDNJvvo_RR8gPYBtg0JxtN247_dVh2JQM5IblguoTWYEUvOCVaD6TFeNCFjUIfkJOY9wyxpoS-FdywhmAlBxW5PWSDnOf3E4HpxPSoF_okJv86ukU_IQh7anVSbc6Ik2edtq43qUFtmF-WiA7m0Qt7rD304Bjonq0FEfd9kjdWMTMG5-B6J5G6jv6_9_a4JycyTY27OnkXyyGRcxgjBi_kS-d7iN-P95r8uf69-PVbXH_cHN3dXlfmIpDKrQAkw-00HXIy7K02NUITJayNQLzjrzmqOu6aYy0QrTARcUMYx0HlHjO1-TXQTc7P88YkxpcNNj3ekQ_R1UyeS5rybPSmtQH1AQfY8BOTcENOuwVMLVkorbqmIlaMlEsF1R57ufRYm4HtO9TbyFk4OIAYF505zCoaByOBq0LaJKy3n1g8Q-yD6RB</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2089858388</pqid></control><display><type>article</type><title>A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><creator>Van Snick, Bernd ; Dhondt, Jens ; Pandelaere, Kenny ; Bertels, Johny ; Mertens, Roel ; Klingeleers, Didier ; Di Pretoro, Giustino ; Remon, Jean Paul ; Vervaet, Chris ; De Beer, Thomas ; Vanhoorne, Valérie</creator><creatorcontrib>Van Snick, Bernd ; Dhondt, Jens ; Pandelaere, Kenny ; Bertels, Johny ; Mertens, Roel ; Klingeleers, Didier ; Di Pretoro, Giustino ; Remon, Jean Paul ; Vervaet, Chris ; De Beer, Thomas ; Vanhoorne, Valérie</creatorcontrib><description>[Display omitted]
In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors.</description><identifier>ISSN: 0378-5173</identifier><identifier>EISSN: 1873-3476</identifier><identifier>DOI: 10.1016/j.ijpharm.2018.08.014</identifier><identifier>PMID: 30118831</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Computer Simulation ; Continuous direct compression ; Databases, Chemical ; Excipients - chemistry ; Friction ; In silico design ; Material characterization ; Models, Chemical ; Models, Statistical ; Multivariate Analysis ; Multivariate data analysis ; Particle Size ; Permeability ; Pharmaceutical drug product development ; Pharmaceutical Preparations - chemistry ; Porosity ; Powders ; Principal Component Analysis ; Technology, Pharmaceutical - methods ; Water - chemistry ; Wettability</subject><ispartof>International journal of pharmaceutics, 2018-10, Vol.549 (1-2), p.415-435</ispartof><rights>2018 Elsevier B.V.</rights><rights>Copyright © 2018 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-a71cccc1b1ffe3222def5e10828bc7e883353ea5566c8d77b13740c00f31e8e93</citedby><cites>FETCH-LOGICAL-c431t-a71cccc1b1ffe3222def5e10828bc7e883353ea5566c8d77b13740c00f31e8e93</cites><orcidid>0000-0001-7313-418X ; 0000-0003-4249-3408</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0378517318305763$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30118831$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Van Snick, Bernd</creatorcontrib><creatorcontrib>Dhondt, Jens</creatorcontrib><creatorcontrib>Pandelaere, Kenny</creatorcontrib><creatorcontrib>Bertels, Johny</creatorcontrib><creatorcontrib>Mertens, Roel</creatorcontrib><creatorcontrib>Klingeleers, Didier</creatorcontrib><creatorcontrib>Di Pretoro, Giustino</creatorcontrib><creatorcontrib>Remon, Jean Paul</creatorcontrib><creatorcontrib>Vervaet, Chris</creatorcontrib><creatorcontrib>De Beer, Thomas</creatorcontrib><creatorcontrib>Vanhoorne, Valérie</creatorcontrib><title>A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes</title><title>International journal of pharmaceutics</title><addtitle>Int J Pharm</addtitle><description>[Display omitted]
In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors.</description><subject>Computer Simulation</subject><subject>Continuous direct compression</subject><subject>Databases, Chemical</subject><subject>Excipients - chemistry</subject><subject>Friction</subject><subject>In silico design</subject><subject>Material characterization</subject><subject>Models, Chemical</subject><subject>Models, Statistical</subject><subject>Multivariate Analysis</subject><subject>Multivariate data analysis</subject><subject>Particle Size</subject><subject>Permeability</subject><subject>Pharmaceutical drug product development</subject><subject>Pharmaceutical Preparations - chemistry</subject><subject>Porosity</subject><subject>Powders</subject><subject>Principal Component Analysis</subject><subject>Technology, Pharmaceutical - methods</subject><subject>Water - chemistry</subject><subject>Wettability</subject><issn>0378-5173</issn><issn>1873-3476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc9u3CAQxlHVqtls-witOPbiDWNsQ05RFDV_pEi5pGeEYZyyso0DeKN9krxucXeTa9BIDNJvvo_RR8gPYBtg0JxtN247_dVh2JQM5IblguoTWYEUvOCVaD6TFeNCFjUIfkJOY9wyxpoS-FdywhmAlBxW5PWSDnOf3E4HpxPSoF_okJv86ukU_IQh7anVSbc6Ik2edtq43qUFtmF-WiA7m0Qt7rD304Bjonq0FEfd9kjdWMTMG5-B6J5G6jv6_9_a4JycyTY27OnkXyyGRcxgjBi_kS-d7iN-P95r8uf69-PVbXH_cHN3dXlfmIpDKrQAkw-00HXIy7K02NUITJayNQLzjrzmqOu6aYy0QrTARcUMYx0HlHjO1-TXQTc7P88YkxpcNNj3ekQ_R1UyeS5rybPSmtQH1AQfY8BOTcENOuwVMLVkorbqmIlaMlEsF1R57ufRYm4HtO9TbyFk4OIAYF505zCoaByOBq0LaJKy3n1g8Q-yD6RB</recordid><startdate>20181005</startdate><enddate>20181005</enddate><creator>Van Snick, Bernd</creator><creator>Dhondt, Jens</creator><creator>Pandelaere, Kenny</creator><creator>Bertels, Johny</creator><creator>Mertens, Roel</creator><creator>Klingeleers, Didier</creator><creator>Di Pretoro, Giustino</creator><creator>Remon, Jean Paul</creator><creator>Vervaet, Chris</creator><creator>De Beer, Thomas</creator><creator>Vanhoorne, Valérie</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><orcidid>https://orcid.org/0000-0001-7313-418X</orcidid><orcidid>https://orcid.org/0000-0003-4249-3408</orcidid></search><sort><creationdate>20181005</creationdate><title>A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes</title><author>Van Snick, Bernd ; Dhondt, Jens ; Pandelaere, Kenny ; Bertels, Johny ; Mertens, Roel ; Klingeleers, Didier ; Di Pretoro, Giustino ; Remon, Jean Paul ; Vervaet, Chris ; De Beer, Thomas ; Vanhoorne, Valérie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-a71cccc1b1ffe3222def5e10828bc7e883353ea5566c8d77b13740c00f31e8e93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Computer Simulation</topic><topic>Continuous direct compression</topic><topic>Databases, Chemical</topic><topic>Excipients - chemistry</topic><topic>Friction</topic><topic>In silico design</topic><topic>Material characterization</topic><topic>Models, Chemical</topic><topic>Models, Statistical</topic><topic>Multivariate Analysis</topic><topic>Multivariate data analysis</topic><topic>Particle Size</topic><topic>Permeability</topic><topic>Pharmaceutical drug product development</topic><topic>Pharmaceutical Preparations - chemistry</topic><topic>Porosity</topic><topic>Powders</topic><topic>Principal Component Analysis</topic><topic>Technology, Pharmaceutical - methods</topic><topic>Water - chemistry</topic><topic>Wettability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Van Snick, Bernd</creatorcontrib><creatorcontrib>Dhondt, Jens</creatorcontrib><creatorcontrib>Pandelaere, Kenny</creatorcontrib><creatorcontrib>Bertels, Johny</creatorcontrib><creatorcontrib>Mertens, Roel</creatorcontrib><creatorcontrib>Klingeleers, Didier</creatorcontrib><creatorcontrib>Di Pretoro, Giustino</creatorcontrib><creatorcontrib>Remon, Jean Paul</creatorcontrib><creatorcontrib>Vervaet, Chris</creatorcontrib><creatorcontrib>De Beer, Thomas</creatorcontrib><creatorcontrib>Vanhoorne, Valérie</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>Van Snick, Bernd</au><au>Dhondt, Jens</au><au>Pandelaere, Kenny</au><au>Bertels, Johny</au><au>Mertens, Roel</au><au>Klingeleers, Didier</au><au>Di Pretoro, Giustino</au><au>Remon, Jean Paul</au><au>Vervaet, Chris</au><au>De Beer, Thomas</au><au>Vanhoorne, Valérie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes</atitle><jtitle>International journal of pharmaceutics</jtitle><addtitle>Int J Pharm</addtitle><date>2018-10-05</date><risdate>2018</risdate><volume>549</volume><issue>1-2</issue><spage>415</spage><epage>435</epage><pages>415-435</pages><issn>0378-5173</issn><eissn>1873-3476</eissn><abstract>[Display omitted]
In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>30118831</pmid><doi>10.1016/j.ijpharm.2018.08.014</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0001-7313-418X</orcidid><orcidid>https://orcid.org/0000-0003-4249-3408</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0378-5173 |
| ispartof | International journal of pharmaceutics, 2018-10, Vol.549 (1-2), p.415-435 |
| issn | 0378-5173 1873-3476 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2089858388 |
| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Computer Simulation Continuous direct compression Databases, Chemical Excipients - chemistry Friction In silico design Material characterization Models, Chemical Models, Statistical Multivariate Analysis Multivariate data analysis Particle Size Permeability Pharmaceutical drug product development Pharmaceutical Preparations - chemistry Porosity Powders Principal Component Analysis Technology, Pharmaceutical - methods Water - chemistry Wettability |
| title | A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T18%3A12%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20multivariate%20raw%20material%20property%20database%20to%20facilitate%20drug%20product%20development%20and%20enable%20in-silico%20design%20of%20pharmaceutical%20dry%20powder%20processes&rft.jtitle=International%20journal%20of%20pharmaceutics&rft.au=Van%20Snick,%20Bernd&rft.date=2018-10-05&rft.volume=549&rft.issue=1-2&rft.spage=415&rft.epage=435&rft.pages=415-435&rft.issn=0378-5173&rft.eissn=1873-3476&rft_id=info:doi/10.1016/j.ijpharm.2018.08.014&rft_dat=%3Cproquest_cross%3E2089858388%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2089858388&rft_id=info:pmid/30118831&rft_els_id=S0378517318305763&rfr_iscdi=true |