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Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer
Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manuf...
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Published in: | AAPS PharmSciTech 2019-07, Vol.20 (7), p.263 |
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creator | Zhou, Deliang Shang, Sherwin Tharp, Ted Jameel, Feroz Sinha, Kushal Nere, Nandkishor K. |
description | Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manufacturing. The steady-state model relies on two critical parameters, namely, the vial heat transfer coefficient,
K
v
, and the cake resistance,
R
p
. The classical gravimetric method used to measure
K
v
is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers. This study proposes a new approach to extract both
K
v
and
R
p
directly from an experimental run (
e.g.
, temperature and Pirani profiles). The new methodology is demonstrated using 5%
w
/
v
mannitol model system. The values of
K
v
obtained using this method are comparable to those measured using the classic gravimetric method. Application of the proposed approach to process scale-up and technology transfer is illustrated using a case study. The new approach makes the steady-state model a simple and reliable tool for model parameterization, thus maximizes its capability and is particularly beneficial for transfer products from lab/pilot to commercial manufacturing. |
doi_str_mv | 10.1208/s12249-019-1478-9 |
format | article |
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K
v
, and the cake resistance,
R
p
. The classical gravimetric method used to measure
K
v
is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers. This study proposes a new approach to extract both
K
v
and
R
p
directly from an experimental run (
e.g.
, temperature and Pirani profiles). The new methodology is demonstrated using 5%
w
/
v
mannitol model system. The values of
K
v
obtained using this method are comparable to those measured using the classic gravimetric method. Application of the proposed approach to process scale-up and technology transfer is illustrated using a case study. The new approach makes the steady-state model a simple and reliable tool for model parameterization, thus maximizes its capability and is particularly beneficial for transfer products from lab/pilot to commercial manufacturing.</description><identifier>EISSN: 1530-9932</identifier><identifier>DOI: 10.1208/s12249-019-1478-9</identifier><identifier>PMID: 31338714</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Biochemistry ; Biomedical and Life Sciences ; Biomedicine ; Biotechnology ; Pharmacology/Toxicology ; Pharmacy ; Research Article</subject><ispartof>AAPS PharmSciTech, 2019-07, Vol.20 (7), p.263</ispartof><rights>American Association of Pharmaceutical Scientists 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-p151t-e1797301e957caca798977115cde39d7a126dd3b7387cb55d964c7f4f7e7f5b83</cites><orcidid>0000-0003-0689-890X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31338714$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Deliang</creatorcontrib><creatorcontrib>Shang, Sherwin</creatorcontrib><creatorcontrib>Tharp, Ted</creatorcontrib><creatorcontrib>Jameel, Feroz</creatorcontrib><creatorcontrib>Sinha, Kushal</creatorcontrib><creatorcontrib>Nere, Nandkishor K.</creatorcontrib><title>Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer</title><title>AAPS PharmSciTech</title><addtitle>AAPS PharmSciTech</addtitle><addtitle>AAPS PharmSciTech</addtitle><description>Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manufacturing. The steady-state model relies on two critical parameters, namely, the vial heat transfer coefficient,
K
v
, and the cake resistance,
R
p
. The classical gravimetric method used to measure
K
v
is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers. This study proposes a new approach to extract both
K
v
and
R
p
directly from an experimental run (
e.g.
, temperature and Pirani profiles). The new methodology is demonstrated using 5%
w
/
v
mannitol model system. The values of
K
v
obtained using this method are comparable to those measured using the classic gravimetric method. Application of the proposed approach to process scale-up and technology transfer is illustrated using a case study. The new approach makes the steady-state model a simple and reliable tool for model parameterization, thus maximizes its capability and is particularly beneficial for transfer products from lab/pilot to commercial manufacturing.</description><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Biotechnology</subject><subject>Pharmacology/Toxicology</subject><subject>Pharmacy</subject><subject>Research Article</subject><issn>1530-9932</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNo1kNtKAzEQhoMgth4ewBvJAxjNJLvN5lLqEVYErZcSssnsdss2WbKtUJ_eLdWrGWY-hn8-Qi6B34Dgxe0AQmSacdAMMlUwfUSmkEvOtJZiQk6HYcW5kKDlCZlIkLJQkE3JV4nfmGzThoaWu9gv2679sZs2BvoaPXb7eR0TfR9bW3VI70e-i_0aw-aafjjbIdv21AZPF-iWIXax2dFFsmGoMZ2T49p2A1781TPy-fiwmD-z8u3pZX5Xsh5y2DAEpZXkgDpXzjqrdKGVAsidR6m9siBm3stKjaFdledezzKn6qxWqOq8KuQZuTrc7bfVGr3pU7u2aWf-_xwBcQCGcRUaTGYVtymMmQxwsxdoDgLNKNDsBRotfwFa-2QS</recordid><startdate>20190723</startdate><enddate>20190723</enddate><creator>Zhou, Deliang</creator><creator>Shang, Sherwin</creator><creator>Tharp, Ted</creator><creator>Jameel, Feroz</creator><creator>Sinha, Kushal</creator><creator>Nere, Nandkishor K.</creator><general>Springer International Publishing</general><scope>NPM</scope><orcidid>https://orcid.org/0000-0003-0689-890X</orcidid></search><sort><creationdate>20190723</creationdate><title>Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer</title><author>Zhou, Deliang ; Shang, Sherwin ; Tharp, Ted ; Jameel, Feroz ; Sinha, Kushal ; Nere, Nandkishor K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p151t-e1797301e957caca798977115cde39d7a126dd3b7387cb55d964c7f4f7e7f5b83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Biotechnology</topic><topic>Pharmacology/Toxicology</topic><topic>Pharmacy</topic><topic>Research Article</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Deliang</creatorcontrib><creatorcontrib>Shang, Sherwin</creatorcontrib><creatorcontrib>Tharp, Ted</creatorcontrib><creatorcontrib>Jameel, Feroz</creatorcontrib><creatorcontrib>Sinha, Kushal</creatorcontrib><creatorcontrib>Nere, Nandkishor K.</creatorcontrib><collection>PubMed</collection><jtitle>AAPS PharmSciTech</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Deliang</au><au>Shang, Sherwin</au><au>Tharp, Ted</au><au>Jameel, Feroz</au><au>Sinha, Kushal</au><au>Nere, Nandkishor K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer</atitle><jtitle>AAPS PharmSciTech</jtitle><stitle>AAPS PharmSciTech</stitle><addtitle>AAPS PharmSciTech</addtitle><date>2019-07-23</date><risdate>2019</risdate><volume>20</volume><issue>7</issue><spage>263</spage><pages>263-</pages><eissn>1530-9932</eissn><abstract>Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manufacturing. The steady-state model relies on two critical parameters, namely, the vial heat transfer coefficient,
K
v
, and the cake resistance,
R
p
. The classical gravimetric method used to measure
K
v
is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers. This study proposes a new approach to extract both
K
v
and
R
p
directly from an experimental run (
e.g.
, temperature and Pirani profiles). The new methodology is demonstrated using 5%
w
/
v
mannitol model system. The values of
K
v
obtained using this method are comparable to those measured using the classic gravimetric method. Application of the proposed approach to process scale-up and technology transfer is illustrated using a case study. The new approach makes the steady-state model a simple and reliable tool for model parameterization, thus maximizes its capability and is particularly beneficial for transfer products from lab/pilot to commercial manufacturing.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>31338714</pmid><doi>10.1208/s12249-019-1478-9</doi><orcidid>https://orcid.org/0000-0003-0689-890X</orcidid></addata></record> |
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issn | 1530-9932 |
language | eng |
recordid | cdi_pubmed_primary_31338714 |
source | Springer Nature |
subjects | Biochemistry Biomedical and Life Sciences Biomedicine Biotechnology Pharmacology/Toxicology Pharmacy Research Article |
title | Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer |
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