Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2005-06

AUTHORS

Robert P. Cogdill, Carl A. Anderson, Miriam Delgado-Lopez, David Molseed, Robert Chisholm, Raymond Bolton, Thorsten Herkert, Ali M. Afnán, James K. Drennen

ABSTRACT

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis. More... »

PAGES

e262-e272

Identifiers

URI

http://scigraph.springernature.com/pub.10.1208/pt060237

DOI

http://dx.doi.org/10.1208/pt060237

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020372426

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16353986


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0301", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Analytical Chemistry", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Feasibility Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Pharmaceutical Preparations", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Spectroscopy, Near-Infrared", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Duquesne University", 
          "id": "https://www.grid.ac/institutes/grid.255272.5", 
          "name": [
            "Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cogdill", 
        "givenName": "Robert P.", 
        "id": "sg:person.0757133350.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757133350.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duquesne University", 
          "id": "https://www.grid.ac/institutes/grid.255272.5", 
          "name": [
            "Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Anderson", 
        "givenName": "Carl A.", 
        "id": "sg:person.01074235575.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074235575.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duquesne University", 
          "id": "https://www.grid.ac/institutes/grid.255272.5", 
          "name": [
            "Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Delgado-Lopez", 
        "givenName": "Miriam", 
        "id": "sg:person.01071143755.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01071143755.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duquesne University", 
          "id": "https://www.grid.ac/institutes/grid.255272.5", 
          "name": [
            "Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Molseed", 
        "givenName": "David", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "AstraZeneca (United Kingdom)", 
          "id": "https://www.grid.ac/institutes/grid.417815.e", 
          "name": [
            "AstraZeneca, SK10 4TF, Macclesfield, Cheshire, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chisholm", 
        "givenName": "Robert", 
        "id": "sg:person.01205372355.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205372355.00"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "AstraZeneca (United Kingdom)", 
          "id": "https://www.grid.ac/institutes/grid.417815.e", 
          "name": [
            "AstraZeneca, SK10 4TF, Macclesfield, Cheshire, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bolton", 
        "givenName": "Raymond", 
        "id": "sg:person.01253505555.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253505555.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "AstraZeneca (Germany)", 
          "id": "https://www.grid.ac/institutes/grid.487186.4", 
          "name": [
            "AstraZeneca GmbH, 68723, Plankstadt, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Herkert", 
        "givenName": "Thorsten", 
        "id": "sg:person.01162063117.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162063117.66"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Center for Drug Evaluation and Research", 
          "id": "https://www.grid.ac/institutes/grid.483500.a", 
          "name": [
            "Center for Drug Evaluation and Research, Office of Pharmaceutical Science, US Food and Drug Administration, 20852, Rockville, MD"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Afn\u00e1n", 
        "givenName": "Ali M.", 
        "id": "sg:person.01125431032.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01125431032.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duquesne University", 
          "id": "https://www.grid.ac/institutes/grid.255272.5", 
          "name": [
            "Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Drennen", 
        "givenName": "James K.", 
        "id": "sg:person.01154472604.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01154472604.86"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1080/05704929608000575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000364202"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0731-7085(95)01562-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000869923"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/05704929608000565", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011946094"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jps.1082", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012261018"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0731-7085(98)00025-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015014438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0731-7085(96)01739-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016306158"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1208/pt060239", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017013992", 
          "https://doi.org/10.1208/pt060239"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1117/12.472074", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019540097"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0731-7085(98)00132-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023329351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1081/pdt-100100536", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023525343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1208/pt060238", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024889847", 
          "https://doi.org/10.1208/pt060238"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jps.2600790717", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032059524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1081/ddc-100101326", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039192864"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/05704929508000906", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048300978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/a1960005x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054964989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/a1960005x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054964989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac00204a009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054980333"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbmel.1961.4322890", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061530414"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1208/pt020421", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064225321", 
          "https://doi.org/10.1208/pt020421"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1208/pt020421", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064225321", 
          "https://doi.org/10.1208/pt020421"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/jnirs.340", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064521200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/jnirs.340", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064521200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/nirn.680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064522971"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1255/nirn.680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064522971"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1366/0003702021955367", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065255880"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1366/0003702021955367", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065255880"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1094/aaccintmethod-39-00.01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1088838172"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2005-06", 
    "datePublishedReg": "2005-06-01", 
    "description": "This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1208/pt060237", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1023420", 
        "issn": [
          "1530-9932"
        ], 
        "name": "AAPS PharmSciTech", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "6"
      }
    ], 
    "name": "Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development", 
    "pagination": "e262-e272", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6111a06965b541d8dd30a4b8db738e6d15c291a4be57dc9ce8162d4c9ce4a16e"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "16353986"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100960111"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1208/pt060237"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1020372426"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1208/pt060237", 
      "https://app.dimensions.ai/details/publication/pub.1020372426"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:34", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000499.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1208/pt060237"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1208/pt060237'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1208/pt060237'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1208/pt060237'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1208/pt060237'


 

This table displays all metadata directly associated to this object as RDF triples.

213 TRIPLES      21 PREDICATES      54 URIs      24 LITERALS      12 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1208/pt060237 schema:about N4ded187a92d540968ff7a9e0b788234d
2 N634e5b03bf2f48f0b37e3efd47f9e9ef
3 N8bfd1491d5fb4d909c456cce054ddb07
4 anzsrc-for:03
5 anzsrc-for:0301
6 schema:author N25fb0a4e3872412c8a2e044f32be19ee
7 schema:citation sg:pub.10.1208/pt020421
8 sg:pub.10.1208/pt060238
9 sg:pub.10.1208/pt060239
10 https://doi.org/10.1002/jps.1082
11 https://doi.org/10.1002/jps.2600790717
12 https://doi.org/10.1016/0731-7085(95)01562-y
13 https://doi.org/10.1016/0731-7085(96)01739-6
14 https://doi.org/10.1016/s0731-7085(98)00025-9
15 https://doi.org/10.1016/s0731-7085(98)00132-0
16 https://doi.org/10.1021/a1960005x
17 https://doi.org/10.1021/ac00204a009
18 https://doi.org/10.1080/05704929508000906
19 https://doi.org/10.1080/05704929608000565
20 https://doi.org/10.1080/05704929608000575
21 https://doi.org/10.1081/ddc-100101326
22 https://doi.org/10.1081/pdt-100100536
23 https://doi.org/10.1094/aaccintmethod-39-00.01
24 https://doi.org/10.1109/tbmel.1961.4322890
25 https://doi.org/10.1117/12.472074
26 https://doi.org/10.1255/jnirs.340
27 https://doi.org/10.1255/nirn.680
28 https://doi.org/10.1366/0003702021955367
29 schema:datePublished 2005-06
30 schema:datePublishedReg 2005-06-01
31 schema:description This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis.
32 schema:genre research_article
33 schema:inLanguage en
34 schema:isAccessibleForFree true
35 schema:isPartOf N00e6c6ef32124a46b6078c47eff9b5c7
36 N4c150223c2ac4b6380d8a589e44d8c23
37 sg:journal.1023420
38 schema:name Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development
39 schema:pagination e262-e272
40 schema:productId N2112e36859ca4df29e7239057ef6a6b6
41 N5c31fce5d1bf430f9b7cf726015b5d34
42 N6264a419d3654cada5f15f6a43827fb6
43 Nc28ffad3beb04097b1ff28e8213ef99e
44 Nf0cae0dc569d4bef95a92f96ef569a31
45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020372426
46 https://doi.org/10.1208/pt060237
47 schema:sdDatePublished 2019-04-10T21:34
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher N05d003a4095b4564b4510ee18c1948a6
50 schema:url http://link.springer.com/10.1208/pt060237
51 sgo:license sg:explorer/license/
52 sgo:sdDataset articles
53 rdf:type schema:ScholarlyArticle
54 N00e6c6ef32124a46b6078c47eff9b5c7 schema:issueNumber 2
55 rdf:type schema:PublicationIssue
56 N05d003a4095b4564b4510ee18c1948a6 schema:name Springer Nature - SN SciGraph project
57 rdf:type schema:Organization
58 N2112e36859ca4df29e7239057ef6a6b6 schema:name readcube_id
59 schema:value 6111a06965b541d8dd30a4b8db738e6d15c291a4be57dc9ce8162d4c9ce4a16e
60 rdf:type schema:PropertyValue
61 N2530cb5853fe4cccbf39820215f1c1f8 schema:affiliation https://www.grid.ac/institutes/grid.255272.5
62 schema:familyName Molseed
63 schema:givenName David
64 rdf:type schema:Person
65 N25fb0a4e3872412c8a2e044f32be19ee rdf:first sg:person.0757133350.48
66 rdf:rest Nb100884adaf84af18fb4c1c6bd5bcf4f
67 N4c150223c2ac4b6380d8a589e44d8c23 schema:volumeNumber 6
68 rdf:type schema:PublicationVolume
69 N4ded187a92d540968ff7a9e0b788234d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
70 schema:name Feasibility Studies
71 rdf:type schema:DefinedTerm
72 N5c31fce5d1bf430f9b7cf726015b5d34 schema:name nlm_unique_id
73 schema:value 100960111
74 rdf:type schema:PropertyValue
75 N6264a419d3654cada5f15f6a43827fb6 schema:name doi
76 schema:value 10.1208/pt060237
77 rdf:type schema:PropertyValue
78 N634e5b03bf2f48f0b37e3efd47f9e9ef schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Spectroscopy, Near-Infrared
80 rdf:type schema:DefinedTerm
81 N792c5bbaf9c34455a011ec554375ef2a rdf:first sg:person.01253505555.08
82 rdf:rest Naeaa712d29b844e29e3158a02e2ea22a
83 N7a2d2ac0bf7045648bd5ac9720a1c7b0 rdf:first sg:person.01205372355.00
84 rdf:rest N792c5bbaf9c34455a011ec554375ef2a
85 N8bfd1491d5fb4d909c456cce054ddb07 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
86 schema:name Pharmaceutical Preparations
87 rdf:type schema:DefinedTerm
88 Na450a21a10f7472fbc8391db46eaa2db rdf:first N2530cb5853fe4cccbf39820215f1c1f8
89 rdf:rest N7a2d2ac0bf7045648bd5ac9720a1c7b0
90 Naa46fd5cebf44508870e76e9a920d15f rdf:first sg:person.01154472604.86
91 rdf:rest rdf:nil
92 Naeaa712d29b844e29e3158a02e2ea22a rdf:first sg:person.01162063117.66
93 rdf:rest Nbb0a10afdf034b7d92eae22c9b960192
94 Nb100884adaf84af18fb4c1c6bd5bcf4f rdf:first sg:person.01074235575.98
95 rdf:rest Ne7c3b68293f94520b0119311989f0f29
96 Nbb0a10afdf034b7d92eae22c9b960192 rdf:first sg:person.01125431032.43
97 rdf:rest Naa46fd5cebf44508870e76e9a920d15f
98 Nc28ffad3beb04097b1ff28e8213ef99e schema:name dimensions_id
99 schema:value pub.1020372426
100 rdf:type schema:PropertyValue
101 Ne7c3b68293f94520b0119311989f0f29 rdf:first sg:person.01071143755.43
102 rdf:rest Na450a21a10f7472fbc8391db46eaa2db
103 Nf0cae0dc569d4bef95a92f96ef569a31 schema:name pubmed_id
104 schema:value 16353986
105 rdf:type schema:PropertyValue
106 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
107 schema:name Chemical Sciences
108 rdf:type schema:DefinedTerm
109 anzsrc-for:0301 schema:inDefinedTermSet anzsrc-for:
110 schema:name Analytical Chemistry
111 rdf:type schema:DefinedTerm
112 sg:journal.1023420 schema:issn 1530-9932
113 schema:name AAPS PharmSciTech
114 rdf:type schema:Periodical
115 sg:person.01071143755.43 schema:affiliation https://www.grid.ac/institutes/grid.255272.5
116 schema:familyName Delgado-Lopez
117 schema:givenName Miriam
118 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01071143755.43
119 rdf:type schema:Person
120 sg:person.01074235575.98 schema:affiliation https://www.grid.ac/institutes/grid.255272.5
121 schema:familyName Anderson
122 schema:givenName Carl A.
123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074235575.98
124 rdf:type schema:Person
125 sg:person.01125431032.43 schema:affiliation https://www.grid.ac/institutes/grid.483500.a
126 schema:familyName Afnán
127 schema:givenName Ali M.
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01125431032.43
129 rdf:type schema:Person
130 sg:person.01154472604.86 schema:affiliation https://www.grid.ac/institutes/grid.255272.5
131 schema:familyName Drennen
132 schema:givenName James K.
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01154472604.86
134 rdf:type schema:Person
135 sg:person.01162063117.66 schema:affiliation https://www.grid.ac/institutes/grid.487186.4
136 schema:familyName Herkert
137 schema:givenName Thorsten
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162063117.66
139 rdf:type schema:Person
140 sg:person.01205372355.00 schema:affiliation https://www.grid.ac/institutes/grid.417815.e
141 schema:familyName Chisholm
142 schema:givenName Robert
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205372355.00
144 rdf:type schema:Person
145 sg:person.01253505555.08 schema:affiliation https://www.grid.ac/institutes/grid.417815.e
146 schema:familyName Bolton
147 schema:givenName Raymond
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253505555.08
149 rdf:type schema:Person
150 sg:person.0757133350.48 schema:affiliation https://www.grid.ac/institutes/grid.255272.5
151 schema:familyName Cogdill
152 schema:givenName Robert P.
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757133350.48
154 rdf:type schema:Person
155 sg:pub.10.1208/pt020421 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064225321
156 https://doi.org/10.1208/pt020421
157 rdf:type schema:CreativeWork
158 sg:pub.10.1208/pt060238 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024889847
159 https://doi.org/10.1208/pt060238
160 rdf:type schema:CreativeWork
161 sg:pub.10.1208/pt060239 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017013992
162 https://doi.org/10.1208/pt060239
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1002/jps.1082 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012261018
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1002/jps.2600790717 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032059524
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1016/0731-7085(95)01562-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1000869923
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1016/0731-7085(96)01739-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016306158
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1016/s0731-7085(98)00025-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015014438
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1016/s0731-7085(98)00132-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023329351
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1021/a1960005x schema:sameAs https://app.dimensions.ai/details/publication/pub.1054964989
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1021/ac00204a009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054980333
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1080/05704929508000906 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048300978
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1080/05704929608000565 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011946094
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1080/05704929608000575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000364202
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1081/ddc-100101326 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039192864
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1081/pdt-100100536 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023525343
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1094/aaccintmethod-39-00.01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1088838172
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1109/tbmel.1961.4322890 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061530414
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1117/12.472074 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019540097
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1255/jnirs.340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064521200
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1255/nirn.680 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064522971
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1366/0003702021955367 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065255880
201 rdf:type schema:CreativeWork
202 https://www.grid.ac/institutes/grid.255272.5 schema:alternateName Duquesne University
203 schema:name Duquesne University Center for Pharmaceutical Technology, 16066, Pittsburgh, PA
204 rdf:type schema:Organization
205 https://www.grid.ac/institutes/grid.417815.e schema:alternateName AstraZeneca (United Kingdom)
206 schema:name AstraZeneca, SK10 4TF, Macclesfield, Cheshire, UK
207 rdf:type schema:Organization
208 https://www.grid.ac/institutes/grid.483500.a schema:alternateName Center for Drug Evaluation and Research
209 schema:name Center for Drug Evaluation and Research, Office of Pharmaceutical Science, US Food and Drug Administration, 20852, Rockville, MD
210 rdf:type schema:Organization
211 https://www.grid.ac/institutes/grid.487186.4 schema:alternateName AstraZeneca (Germany)
212 schema:name AstraZeneca GmbH, 68723, Plankstadt, Germany
213 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...