A 1-step Bayesian predictive approach for evaluating in vitro in vivo correlation (IVIVC)
IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a functio...
Saved in:
Published in | Biopharmaceutics & drug disposition Vol. 30; no. 7; pp. 366 - 388 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.10.2009
|
Subjects | |
Online Access | Get full text |
ISSN | 0142-2782 1099-081X 1099-081X |
DOI | 10.1002/bdd.672 |
Cover
Loading…
Abstract | IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled‐release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between‐ and within‐subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, Cmax and Tmax can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. Copyright © 2009 John Wiley & Sons, Ltd. |
---|---|
AbstractList | IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled‐release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between‐ and within‐subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, Cmax and Tmax can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. Copyright © 2009 John Wiley & Sons, Ltd. IVIVC ( in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled‐release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between‐ and within‐subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC , C max and T max can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. Copyright © 2009 John Wiley & Sons, Ltd. IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled-release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between- and within-subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, C(max) and T(max) can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly.IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled-release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between- and within-subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, C(max) and T(max) can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional bioequivalence trials in human subjects. Most current IVIVC methods express the in vivo plasma concentration of a drug formulation as a function of the cumulative in vivo absorption. The absorption is not directly observable, so is estimated by the cumulative dissolution of the drug formulation in in vitro dissolution trials. The calculations conventionally entail the complex and potentially unstable mathematical operations of convolution and deconvolution, or approximations aimed at omitting their need. This paper describes, and illustrates with data on a controlled-release formulation, a Bayesian approach to evaluating IVIVC that does not require convolution, deconvolution or approximation. This approach incorporates between- and within-subject (or replicate) variability without assuming asymptotic normality. The plasma concentration curve is expressed in terms of the in vitro dissolution percentage instead of time, recognizing that this correspondence may be noisy because of the various sources of error. All conventional functions of the concentration curve such as AUC, C(max) and T(max) can be expressed in terms of dissolution percentage, with uncertainties arising from variability in measuring absorption and dissolution accounted for explicitly. |
Author | Fitzpatrick, Shaun Agrawal, Nancy G. B. Goel, Thanh V. Gould, A. Lawrence |
Author_xml | – sequence: 1 givenname: A. Lawrence surname: Gould fullname: Gould, A. Lawrence email: goulda@merck.com organization: Merck Research Laboratories, North Wales, PA 19454, USA – sequence: 2 givenname: Nancy G. B. surname: Agrawal fullname: Agrawal, Nancy G. B. organization: Merck Research Laboratories, North Wales, PA 19454, USA – sequence: 3 givenname: Thanh V. surname: Goel fullname: Goel, Thanh V. organization: Merial Ltd. Duluth GA, 30096, USA – sequence: 4 givenname: Shaun surname: Fitzpatrick fullname: Fitzpatrick, Shaun organization: Merck Research Laboratories, North Wales, PA 19454, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19735073$$D View this record in MEDLINE/PubMed |
BookMark | eNp10VFv0zAQB3BrGtq6gfgGk98AoQyfndTJ49rB6FqxlzFgL9bVdsCQxsFOC_32GNKVB8STLfmn893_Tshh61tLyFNg58AYf7U05nws-QEZAauqjJXw8ZCMGOQ847Lkx-Qkxq-MsTEAHJFjqKQomBQj8umCQhZ729EJbm102NIuWON07zaWYtcFj_oLrX2gdoPNGnvXfqaupRvXBz9cNp5qH4Jt0qNv6fPZ3exu-uIxeVRjE-2T3XlK3r95fTt9my1urmbTi0WmRZHaE8ZUiIbnFk2BUkhd5pVZIucaDJasRhAMRS1LLJEvQeZpQA4wxkIbblGckmdD3dTq97WNvVq5qG3TYGv9OiopclZIBlWSZzu5Xq6sUV1wKwxb9ZBGAtkAdPAxBlsr7fo_Q_UBXaOAqd9pq5S2Smn__Xrv9yX_kS8H-cM1dvs_piaXl4Pe9eHSZn7uNYZvSQlZqA_vrtRkwa8X8_lc3YtfQdSbKg |
CitedBy_id | crossref_primary_10_1002_bimj_201700263 crossref_primary_10_1007_s13346_013_0170_y crossref_primary_10_1208_s12248_016_9880_7 |
Cites_doi | 10.1016/S0939-6411(03)00140-1 10.1111/j.1751-5823.2003.tb00203.x 10.1111/1467-9884.00176 10.1023/A:1011531226478 10.1023/A:1008929526011 10.1016/S0168-3659(03)00033-6 10.1080/10543409708835207 10.1023/A:1020206907668 10.1198/106186004X11435 10.1007/978-1-4684-6036-0_6 10.1007/BF01059546 10.1021/js970155d 10.1002/(SICI)1097-0258(19990730)18:14<1865::AID-SIM223>3.0.CO;2-P 10.1211/002235702847 10.1080/01621459.1996.10476664 10.1021/js9503587 10.1016/j.jpba.2007.05.021 10.1007/978-1-4684-6036-0_5 10.1137/1.9781611971675 10.1023/A:1016020822093 10.1111/1467-9868.00353 10.1007/BF01065657 10.1002/jps.20592 |
ContentType | Journal Article |
Copyright | Copyright © 2009 John Wiley & Sons, Ltd. 2009 John Wiley & Sons, Ltd. |
Copyright_xml | – notice: Copyright © 2009 John Wiley & Sons, Ltd. – notice: 2009 John Wiley & Sons, Ltd. |
DBID | BSCLL AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 |
DOI | 10.1002/bdd.672 |
DatabaseName | Istex CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic |
DatabaseTitleList | CrossRef MEDLINE - Academic MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Pharmacy, Therapeutics, & Pharmacology Mathematics |
EISSN | 1099-081X |
EndPage | 388 |
ExternalDocumentID | 19735073 10_1002_bdd_672 BDD672 ark_67375_WNG_BL2JLKKK_Z |
Genre | article Journal Article |
GroupedDBID | --- .3N .GA .GJ .Y3 05W 0R~ 10A 1L6 1OB 1OC 1ZS 23N 31~ 33P 3SF 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52R 52S 52T 52U 52V 52W 52X 53G 5GY 5RE 5VS 66C 6J9 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A01 A03 AAESR AAEVG AAHHS AANLZ AAONW AASGY AAXRX AAZKR ABCQN ABCUV ABEML ABIJN ABJNI ABPVW ABQWH ABXGK ACAHQ ACBWZ ACCFJ ACCZN ACGFO ACGFS ACGOF ACIWK ACMXC ACPOU ACPRK ACSCC ACXBN ACXQS ADBBV ADBTR ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN ADZOD AEEZP AEGXH AEIGN AEIMD AENEX AEQDE AEUQT AEUYR AFBPY AFFPM AFGKR AFPWT AFRAH AFZJQ AHBTC AHMBA AI. AIACR AIAGR AITYG AIURR AIWBW AJBDE ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN AMBMR AMYDB ASPBG ATUGU AVWKF AZBYB AZFZN AZVAB BAFTC BDRZF BFHJK BHBCM BMXJE BROTX BRXPI BSCLL BY8 C45 CS3 D-6 D-7 D-E D-F DCZOG DPXWK DR2 DRFUL DRMAN DRSTM DU5 EBD EBS EJD EMOBN F00 F01 F04 F5P FEDTE FUBAC G-S G.N GNP GODZA GWYGA H.X HBH HF~ HGLYW HHY HHZ HVGLF HZ~ IX1 J0M JPC KBYEO KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LSO LUTES LW6 LYRES M6Q MEWTI MK4 MRFUL MRMAN MRSTM MSFUL MSMAN MSSTM MXFUL MXMAN MXSTM N04 N05 N9A NF~ NNB O66 O9- OVD P2P P2W P2X P2Z P4B P4D PALCI PQQKQ Q.N Q11 QB0 QRW R.K RIWAO ROL RWI RX1 RYL SAMSI SUPJJ SV3 TEORI UB1 V2E V8K VH1 W8V W99 WBKPD WHWMO WIB WIH WIJ WIK WJL WOHZO WQJ WRC WUP WVDHM WWP WXI WXSBR XG1 XPP XV2 YCJ ZZTAW ~IA ~WT AAHQN AAIPD AAMNL AANHP AAYCA ACRPL ACYXJ ADNMO AFWVQ ALVPJ AAYXX AEYWJ AGHNM AGQPQ AGYGG CITATION AAMMB AEFGJ AGXDD AIDQK AIDYY CGR CUY CVF ECM EIF NPM 7X8 |
ID | FETCH-LOGICAL-c3542-3dd9aad24ead5a737c849dba22c1da80fa130a3f78a8a2b1740992116a5cd2ea3 |
IEDL.DBID | DR2 |
ISSN | 0142-2782 1099-081X |
IngestDate | Fri Sep 05 09:34:56 EDT 2025 Mon Jul 21 05:19:03 EDT 2025 Thu Apr 24 23:06:54 EDT 2025 Tue Jul 01 03:35:34 EDT 2025 Wed Jan 22 16:45:57 EST 2025 Wed Oct 30 09:46:32 EDT 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 7 |
Language | English |
License | http://onlinelibrary.wiley.com/termsAndConditions#vor 2009 John Wiley & Sons, Ltd. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c3542-3dd9aad24ead5a737c849dba22c1da80fa130a3f78a8a2b1740992116a5cd2ea3 |
Notes | istex:A94A5387FFA1EAB9567ED8448BBEC1414B34AF37 ArticleID:BDD672 ark:/67375/WNG-BL2JLKKK-Z ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
PMID | 19735073 |
PQID | 734057019 |
PQPubID | 23479 |
PageCount | 23 |
ParticipantIDs | proquest_miscellaneous_734057019 pubmed_primary_19735073 crossref_citationtrail_10_1002_bdd_672 crossref_primary_10_1002_bdd_672 wiley_primary_10_1002_bdd_672_BDD672 istex_primary_ark_67375_WNG_BL2JLKKK_Z |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | October 2009 |
PublicationDateYYYYMMDD | 2009-10-01 |
PublicationDate_xml | – month: 10 year: 2009 text: October 2009 |
PublicationDecade | 2000 |
PublicationPlace | Chichester, UK |
PublicationPlace_xml | – name: Chichester, UK – name: England |
PublicationTitle | Biopharmaceutics & drug disposition |
PublicationTitleAlternate | Biopharm. Drug Dispos |
PublicationYear | 2009 |
Publisher | John Wiley & Sons, Ltd |
Publisher_xml | – name: John Wiley & Sons, Ltd |
References | Dunne A, Devane J, O'Hara T. The relationship between in vitro drug dissolution and in vivo absorption. J Roy Stat Soc Series D Statistician 1999; 48: 125-133. Polli JE, Crison JR, Amidon GL. Novel approach to the analysis of in vitro-in vivo relationships. J Pharm Sci 1996; 85: 753-760. Langenbucher F. Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: III. Convolution and deconvolution. Eur J Pharm Biopharm 2003; 56: 429-437. Dunne A, O'Hara T, Devane J. Approaches to IVIVR modelling and statistical analysis. Adv Exp Med Biol 1997; 423: 67-86. Lunn DJ, Thomas A, Best NG, Spiegelhalter DJ. WinBUGS-A Bayesian modelling framework: concepts, structure, and extensibility. Stat Comput 2000; 10: 325-337. Gelman A. A Bayesian formulation of exploratory data analysis and goodness-of-fit testing. Int Stat Rev 2002; 71: 369-382. Dunne A, O'Hara T, Devane J. Level A in vitro in vitro correlation: Nonlinear models and statistical methodology. J Pharm Sci 1997; 86: 1245-1249. Gelman A. Exploratory data analysis for complex models. J Comput Graph Stat 2004; 13: 755-779. Gillespie WR, Veng-Pedersen P. A polyexponential deconvolution method. Evaluation of the 'gastrointestinal bioavailability' and mean in vivo dissolution time of some ibuprofen dosage forms. J Pharmacokinet Biopharm 1985; 13: 289-307. Lunn DJ, Best NG, Thomas A, Wakefield J, Spiegelhalter DJ. Bayesian analysis of population pK/pD models: General concepts and software. J Pharmacokinet Pharmacodyn 2002; 29: 271-307. Polli JE, Crison JR, Amidon GL. Novel approach to the analysis of in vitro-in vivo relationships (vol 85, pg 753, 1996). J Pharm Sci 1997; 86: 268. USP Subcommittee on Biopharmaceutics. In-vitro/in-vivo correlation for extended-release oral dosage forms. Pharm Forum 1988; 13: 4161. Buchwald P. Direct, differential-equation-based in-vitro-in-vivo correlation (IVIVC) method. J Pharm Pharmacol 2003; 55: 495-504. Lunn DJ, Wakefield J, Thomas A, Best NG, Spiegelhalter DJ. PKBugs User Guide, version 1.1. 1999. Department of Epidemiology and Public Health, Imperial College School of Medicine: London. Berry MR, Likar MD. Statistical assessment of dissolution and drug release profile similarity using a model-dependent approach. J Pharm Biomed Anal 2007; 45: 194-200. O'Hara T, Hayes S, Davis J, Devane J, Smart T, Dunne A. In vivo-in vitro correlation (IVIVC) modeling incorporating a convolution step. J Pharmacokinet Pharmacodyn 2001; 28: 277-298. European Agency for the Evaluation of Medicinal Products. Note for Guidance on Quality of Modified Release Products: A: Oral Dosage Forms B: Transdermal Dosage Forms Section I (Quality). 1999. European Agency for the Evaluation of Medicinal Products: London. Veng-Pedersen P. An algorithm and computer program for deconvolution in linear pharmacokinetics. J Pharmacokinet Biopharm 1980; 8: 463-481. Mauger DT, Chinchilli VM. In vitro-in vivo relationships for oral extended-release drug products. J Biopharm Stat 1997; 7: 565-578. Gillespie WR. In Vitro-In Vivo Correlations. Plenum Press: New York, 1997; 53-65. Food and Drug Administration. Guidance for Industry. Extended Release Oral Dosage Forms: Development, Evaluation, and Application of In Vitro/In Vivo Correlations. 1997. Food and Drug Administration: Rockville, MD. Wing GM. APprimer on Integral Equations of the First Kind-The Problem of Deconvolution and Unfolding. 1991. Society for Industrial and Applied Mathematics: Philadelphia. Dunne A, O'Hara T, Devane J. A new approach to modelling the relationship between in vitro and in vivo drug dissolution/absorption. Stat Med 1999; 18: 1865-1876. Thomas A, O'Hara B, Ligges U, Sturtz S. Making BUGS open. R News 2006; 6: 12-17. Kortejärvi H, Malkki J, Marvola M, Urtti A, Yliperttula M, Pajunen P. Level A In Vitro-In Vivo correlation (IVIVC) model with Bayesian approach to formulation series. J Pharm Sci 2006; 95: 1595-1605. Wakefield J. The Bayesian analysis of population pharmacokinetic models. J Am Stat Assoc 1996; 91: 62-75. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A. Bayesian measures of model complexity and fit (with discussion). J Roy Stat Soc Series B Methodological 2002; 64: 583-616. Costa FO, Sousa JJS, Pais AACC, Formosinho SJ. Comparison of dissolution profiles of ibuprofen pellets. J Control Rel 2003; 89: 199-212. Langenbucher F, Möller H. Correlation of in vitro drug relationships with in vivo response kinetics. Pharm Ind 1983; 45: 623-628. Sathe PM, Tsong Y, Shah VP. In vitro dissolution profile comparison: Statistics and analysis, model dependent approach. Pharm Res 1996; 13: 1799-1803. 2006; 95 1997; 86 1999; 48 1997 1988; 13 2006; 6 2001; 28 1991 1996; 91 1996; 13 1997; 7 2003; 55 1999 2003; 56 1997; 423 2002; 29 2002; 64 1999; 18 2000; 10 2004; 13 1996; 85 1980; 8 2002; 71 2007; 45 1985; 13 2003; 89 1983; 45 European Agency for the Evaluation of Medicinal Products (e_1_2_1_8_2) 1999 e_1_2_1_22_2 Lunn DJ (e_1_2_1_31_2) 1999 e_1_2_1_23_2 e_1_2_1_20_2 e_1_2_1_21_2 e_1_2_1_27_2 e_1_2_1_24_2 Langenbucher F (e_1_2_1_26_2) 1983; 45 Polli JE (e_1_2_1_6_2) 1997; 86 e_1_2_1_28_2 e_1_2_1_29_2 Thomas A (e_1_2_1_25_2) 2006; 6 e_1_2_1_30_2 USP Subcommittee on Biopharmaceutics (e_1_2_1_7_2) 1988; 13 e_1_2_1_4_2 e_1_2_1_5_2 e_1_2_1_2_2 Food and Drug Administration (e_1_2_1_3_2) 1997 e_1_2_1_11_2 e_1_2_1_12_2 e_1_2_1_10_2 e_1_2_1_15_2 e_1_2_1_16_2 e_1_2_1_13_2 e_1_2_1_14_2 e_1_2_1_19_2 e_1_2_1_17_2 e_1_2_1_9_2 e_1_2_1_18_2 26896256 - AAPS J. 2016 May;18(3):619-34 |
References_xml | – reference: Dunne A, O'Hara T, Devane J. Approaches to IVIVR modelling and statistical analysis. Adv Exp Med Biol 1997; 423: 67-86. – reference: USP Subcommittee on Biopharmaceutics. In-vitro/in-vivo correlation for extended-release oral dosage forms. Pharm Forum 1988; 13: 4161. – reference: Dunne A, O'Hara T, Devane J. A new approach to modelling the relationship between in vitro and in vivo drug dissolution/absorption. Stat Med 1999; 18: 1865-1876. – reference: Kortejärvi H, Malkki J, Marvola M, Urtti A, Yliperttula M, Pajunen P. Level A In Vitro-In Vivo correlation (IVIVC) model with Bayesian approach to formulation series. J Pharm Sci 2006; 95: 1595-1605. – reference: Gillespie WR. In Vitro-In Vivo Correlations. Plenum Press: New York, 1997; 53-65. – reference: O'Hara T, Hayes S, Davis J, Devane J, Smart T, Dunne A. In vivo-in vitro correlation (IVIVC) modeling incorporating a convolution step. J Pharmacokinet Pharmacodyn 2001; 28: 277-298. – reference: Gelman A. A Bayesian formulation of exploratory data analysis and goodness-of-fit testing. Int Stat Rev 2002; 71: 369-382. – reference: Lunn DJ, Thomas A, Best NG, Spiegelhalter DJ. WinBUGS-A Bayesian modelling framework: concepts, structure, and extensibility. Stat Comput 2000; 10: 325-337. – reference: Thomas A, O'Hara B, Ligges U, Sturtz S. Making BUGS open. R News 2006; 6: 12-17. – reference: Sathe PM, Tsong Y, Shah VP. In vitro dissolution profile comparison: Statistics and analysis, model dependent approach. Pharm Res 1996; 13: 1799-1803. – reference: Gillespie WR, Veng-Pedersen P. A polyexponential deconvolution method. Evaluation of the 'gastrointestinal bioavailability' and mean in vivo dissolution time of some ibuprofen dosage forms. J Pharmacokinet Biopharm 1985; 13: 289-307. – reference: Lunn DJ, Best NG, Thomas A, Wakefield J, Spiegelhalter DJ. Bayesian analysis of population pK/pD models: General concepts and software. J Pharmacokinet Pharmacodyn 2002; 29: 271-307. – reference: Lunn DJ, Wakefield J, Thomas A, Best NG, Spiegelhalter DJ. PKBugs User Guide, version 1.1. 1999. Department of Epidemiology and Public Health, Imperial College School of Medicine: London. – reference: Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A. Bayesian measures of model complexity and fit (with discussion). J Roy Stat Soc Series B Methodological 2002; 64: 583-616. – reference: Food and Drug Administration. Guidance for Industry. Extended Release Oral Dosage Forms: Development, Evaluation, and Application of In Vitro/In Vivo Correlations. 1997. Food and Drug Administration: Rockville, MD. – reference: Veng-Pedersen P. An algorithm and computer program for deconvolution in linear pharmacokinetics. J Pharmacokinet Biopharm 1980; 8: 463-481. – reference: Wakefield J. The Bayesian analysis of population pharmacokinetic models. J Am Stat Assoc 1996; 91: 62-75. – reference: Gelman A. Exploratory data analysis for complex models. J Comput Graph Stat 2004; 13: 755-779. – reference: Wing GM. APprimer on Integral Equations of the First Kind-The Problem of Deconvolution and Unfolding. 1991. Society for Industrial and Applied Mathematics: Philadelphia. – reference: Polli JE, Crison JR, Amidon GL. Novel approach to the analysis of in vitro-in vivo relationships. J Pharm Sci 1996; 85: 753-760. – reference: Berry MR, Likar MD. Statistical assessment of dissolution and drug release profile similarity using a model-dependent approach. J Pharm Biomed Anal 2007; 45: 194-200. – reference: Mauger DT, Chinchilli VM. In vitro-in vivo relationships for oral extended-release drug products. J Biopharm Stat 1997; 7: 565-578. – reference: Langenbucher F, Möller H. Correlation of in vitro drug relationships with in vivo response kinetics. Pharm Ind 1983; 45: 623-628. – reference: Dunne A, O'Hara T, Devane J. Level A in vitro in vitro correlation: Nonlinear models and statistical methodology. J Pharm Sci 1997; 86: 1245-1249. – reference: European Agency for the Evaluation of Medicinal Products. Note for Guidance on Quality of Modified Release Products: A: Oral Dosage Forms B: Transdermal Dosage Forms Section I (Quality). 1999. European Agency for the Evaluation of Medicinal Products: London. – reference: Dunne A, Devane J, O'Hara T. The relationship between in vitro drug dissolution and in vivo absorption. J Roy Stat Soc Series D Statistician 1999; 48: 125-133. – reference: Polli JE, Crison JR, Amidon GL. Novel approach to the analysis of in vitro-in vivo relationships (vol 85, pg 753, 1996). J Pharm Sci 1997; 86: 268. – reference: Langenbucher F. Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: III. Convolution and deconvolution. Eur J Pharm Biopharm 2003; 56: 429-437. – reference: Costa FO, Sousa JJS, Pais AACC, Formosinho SJ. Comparison of dissolution profiles of ibuprofen pellets. J Control Rel 2003; 89: 199-212. – reference: Buchwald P. Direct, differential-equation-based in-vitro-in-vivo correlation (IVIVC) method. J Pharm Pharmacol 2003; 55: 495-504. – volume: 56 start-page: 429 year: 2003 end-page: 437 article-title: Handling of computational correlation problems by Microsoft Excel: III. Convolution and deconvolution publication-title: Eur J Pharm Biopharm – volume: 7 start-page: 565 year: 1997 end-page: 578 article-title: relationships for oral extended‐release drug products publication-title: J Biopharm Stat – volume: 13 start-page: 4161 year: 1988 article-title: correlation for extended‐release oral dosage forms publication-title: Pharm Forum – start-page: 53 year: 1997 end-page: 65 – volume: 95 start-page: 1595 year: 2006 end-page: 1605 article-title: Level A correlation (IVIVC) model with Bayesian approach to formulation series publication-title: J Pharm Sci – volume: 423 start-page: 67 year: 1997 end-page: 86 article-title: Approaches to IVIVR modelling and statistical analysis publication-title: Adv Exp Med Biol – volume: 45 start-page: 623 year: 1983 end-page: 628 article-title: Correlation of drug relationships with response kinetics publication-title: Pharm Ind – volume: 71 start-page: 369 year: 2002 end-page: 382 article-title: A Bayesian formulation of exploratory data analysis and goodness‐of‐fit testing publication-title: Int Stat Rev – volume: 13 start-page: 289 year: 1985 end-page: 307 article-title: A polyexponential deconvolution method. Evaluation of the ‘gastrointestinal bioavailability’ and mean dissolution time of some ibuprofen dosage forms publication-title: J Pharmacokinet Biopharm – volume: 48 start-page: 125 year: 1999 end-page: 133 article-title: The relationship between drug dissolution and absorption publication-title: J Roy Stat Soc Series D Statistician – volume: 89 start-page: 199 year: 2003 end-page: 212 article-title: Comparison of dissolution profiles of ibuprofen pellets publication-title: J Control Rel – volume: 85 start-page: 753 year: 1996 end-page: 760 article-title: Novel approach to the analysis of relationships publication-title: J Pharm Sci – volume: 55 start-page: 495 year: 2003 end-page: 504 article-title: Direct, differential‐equation‐based correlation (IVIVC) method publication-title: J Pharm Pharmacol – volume: 28 start-page: 277 year: 2001 end-page: 298 article-title: correlation (IVIVC) modeling incorporating a convolution step publication-title: J Pharmacokinet Pharmacodyn – volume: 91 start-page: 62 year: 1996 end-page: 75 article-title: The Bayesian analysis of population pharmacokinetic models publication-title: J Am Stat Assoc – volume: 45 start-page: 194 year: 2007 end-page: 200 article-title: Statistical assessment of dissolution and drug release profile similarity using a model‐dependent approach publication-title: J Pharm Biomed Anal – volume: 8 start-page: 463 year: 1980 end-page: 481 article-title: An algorithm and computer program for deconvolution in linear pharmacokinetics publication-title: J Pharmacokinet Biopharm – volume: 13 start-page: 755 year: 2004 end-page: 779 article-title: Exploratory data analysis for complex models publication-title: J Comput Graph Stat – volume: 64 start-page: 583 year: 2002 end-page: 616 article-title: Bayesian measures of model complexity and fit (with discussion) publication-title: J Roy Stat Soc Series B Methodological – volume: 13 start-page: 1799 year: 1996 end-page: 1803 article-title: dissolution profile comparison: Statistics and analysis, model dependent approach publication-title: Pharm Res – volume: 86 start-page: 1245 year: 1997 end-page: 1249 article-title: Level A correlation: Nonlinear models and statistical methodology publication-title: J Pharm Sci – year: 1997 – volume: 86 start-page: 268 year: 1997 article-title: Novel approach to the analysis of ‐ relationships (vol 85, pg 753, 1996) publication-title: J Pharm Sci – volume: 10 start-page: 325 year: 2000 end-page: 337 article-title: WinBUGS–A Bayesian modelling framework: concepts, structure, and extensibility publication-title: Stat Comput – volume: 6 start-page: 12 year: 2006 end-page: 17 article-title: Making BUGS open publication-title: R News – year: 1991 – volume: 29 start-page: 271 year: 2002 end-page: 307 article-title: Bayesian analysis of population pK/pD models: General concepts and software publication-title: J Pharmacokinet Pharmacodyn – volume: 18 start-page: 1865 year: 1999 end-page: 1876 article-title: A new approach to modelling the relationship between and drug dissolution/absorption publication-title: Stat Med – year: 1999 – ident: e_1_2_1_10_2 doi: 10.1016/S0939-6411(03)00140-1 – ident: e_1_2_1_28_2 doi: 10.1111/j.1751-5823.2003.tb00203.x – ident: e_1_2_1_14_2 doi: 10.1111/1467-9884.00176 – ident: e_1_2_1_2_2 doi: 10.1023/A:1011531226478 – ident: e_1_2_1_24_2 doi: 10.1023/A:1008929526011 – ident: e_1_2_1_22_2 doi: 10.1016/S0168-3659(03)00033-6 – ident: e_1_2_1_4_2 doi: 10.1080/10543409708835207 – ident: e_1_2_1_19_2 doi: 10.1023/A:1020206907668 – ident: e_1_2_1_29_2 doi: 10.1198/106186004X11435 – ident: e_1_2_1_18_2 doi: 10.1007/978-1-4684-6036-0_6 – ident: e_1_2_1_12_2 doi: 10.1007/BF01059546 – volume-title: Guidance for Industry. Extended Release Oral Dosage Forms: Development, Evaluation, and Application of In Vitro/In Vivo Correlations year: 1997 ident: e_1_2_1_3_2 – ident: e_1_2_1_17_2 doi: 10.1021/js970155d – ident: e_1_2_1_9_2 doi: 10.1002/(SICI)1097-0258(19990730)18:14<1865::AID-SIM223>3.0.CO;2-P – ident: e_1_2_1_11_2 doi: 10.1211/002235702847 – volume: 13 start-page: 4161 year: 1988 ident: e_1_2_1_7_2 article-title: In‐vitro/in‐vivo correlation for extended‐release oral dosage forms publication-title: Pharm Forum – ident: e_1_2_1_20_2 doi: 10.1080/01621459.1996.10476664 – volume: 86 start-page: 268 year: 1997 ident: e_1_2_1_6_2 article-title: Novel approach to the analysis of in vitro‐in vivo relationships (vol 85, pg 753, 1996) publication-title: J Pharm Sci – ident: e_1_2_1_5_2 doi: 10.1021/js9503587 – ident: e_1_2_1_21_2 doi: 10.1016/j.jpba.2007.05.021 – ident: e_1_2_1_16_2 doi: 10.1007/978-1-4684-6036-0_5 – ident: e_1_2_1_13_2 doi: 10.1137/1.9781611971675 – volume-title: Note for Guidance on Quality of Modified Release Products: A: Oral Dosage Forms B: Transdermal Dosage Forms Section I (Quality) year: 1999 ident: e_1_2_1_8_2 – ident: e_1_2_1_23_2 doi: 10.1023/A:1016020822093 – volume-title: PKBugs User Guide year: 1999 ident: e_1_2_1_31_2 – volume: 6 start-page: 12 year: 2006 ident: e_1_2_1_25_2 article-title: Making BUGS open publication-title: R News – ident: e_1_2_1_30_2 doi: 10.1111/1467-9868.00353 – ident: e_1_2_1_15_2 doi: 10.1007/BF01065657 – volume: 45 start-page: 623 year: 1983 ident: e_1_2_1_26_2 article-title: Correlation of in vitro drug relationships with in vivo response kinetics publication-title: Pharm Ind – ident: e_1_2_1_27_2 doi: 10.1002/jps.20592 – reference: 26896256 - AAPS J. 2016 May;18(3):619-34 |
SSID | ssj0006111 |
Score | 1.847842 |
Snippet | IVIVC (in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional... IVIVC ( in vitro in vivo correlation) methods may support approving a change in formulation of a drug using only in vitro dissolution data without additional... |
SourceID | proquest pubmed crossref wiley istex |
SourceType | Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 366 |
SubjectTerms | Absorption Administration, Oral Area Under Curve bioavailability Chemistry, Pharmaceutical - statistics & numerical data Computational Biology - methods Excipients - pharmacokinetics Humans Mathematics pharmacokinetic prediction Solubility Statistics as Topic Therapeutic Equivalency |
Title | A 1-step Bayesian predictive approach for evaluating in vitro in vivo correlation (IVIVC) |
URI | https://api.istex.fr/ark:/67375/WNG-BL2JLKKK-Z/fulltext.pdf https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fbdd.672 https://www.ncbi.nlm.nih.gov/pubmed/19735073 https://www.proquest.com/docview/734057019 |
Volume | 30 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LTxsxELYqeumFPqFpS-VDFLUSGxJ7n0cCTQMBhBAv0YM1tjcIUW2iPFDDqT-hv5Ffwsw6m21aKlWcdqW1d_2Y8Xxez3zDWBW3HGjVIPUSY4zn68R4GmGRJ-PUNIxv0AJTcPL-Qdg58XfPg_PfUn05foj5DzfSjHy9JgUHPdooSUO1tfUwotWXPLUIDh2VxFFhs-kyEebBJ7Fw4bJUc2NWb8EOPaUh_fEQyFzErLnRaT9nF0Vzna_JdX0y1nVz-weT46P684Itz6Ao33Sy85I9SbNXrHbouKyn6_y4DM0arfMaPyxZrqev2bdN3rz7-Qt7NOAtmKYUjMkHQzr3oRWUF2TlHFExLzjFs0t-lfGbq_Gw725u-txQfhDnkcc_7ZzunG59fsNO2l-OtzreLFODZ2SAQyytTQCs8FEuA4hkZGI_sRqEME0LcaMHaCpB9qIYYhAad0EITHHrGUJgrEhBrrClrJ-lbxkniBQLCtC39A6DG7qoJ30JjVCHOm5UWK2YN2VmNOaUTeO7cgTMQuFAKhzICuPzggPH3PF3kVo-8fPnMLwmR7coUGcHX1VrT-zudbtddYHvKiRDofrRmQpkaX8yUpEkxIs4ucJWncSUH0siiWhbVlg1n_d_tUK1trfx8u7_ir1nz_IDrdyf8ANbGg8n6RriorH-mKvAPTOLCgw |
linkProvider | Wiley-Blackwell |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LbxMxEB6h9gAXWt6hPHyoIpC6aWLv89g0lKRJowqlpaIHy49NVRVtojSpCCd-Ar-RX8LMejer8pAQp11pba9f4_lsz3wDsI1bDtRqKvUSY4zn68R4GmGRJ-LUNI1vUAOTc_LRMOye-IdnwVlhVUm-MI4fYnXgRpKRr9ck4HQgvVuxhmprG2GEy-86xfMmoex8qKijwlbLxSLM3U9i7hxmKetukfGWJlqnTv3yJ5h5G7XmaudgA87LCjtrk6vGYq4b5usvXI7_16JNuF-gUbbnps8DuJNmD6F-7OislztsVHlnXe-wOjuuiK6Xj-B8j7V-fPuOTZqytlqm5I_JpjO6-qFFlJV85QyBMStpxbMLdpmxm8v5bOJebibMUIgQZ5TH3vROe6f7bx_DycG70X7XK4I1eEYE2MfC2kQpy32cmoGKRGRiP7FacW5aVsXNsUJtqcQ4ilWsuMaNEGJT3H2GKjCWp0o8gbVskqXPgBFKijn56Fsqw-CeLhoLX6hmqEMdN2tQLwdOmoLJnAJqfJaOg5lL7EiJHVkDtko4deQdvyep5yO_-q5mV2TrFgXy4_C9bA_44aDf78tPWFY5NSRKIF2rqCydLK5lJAj0IlSuwVM3ZaqfJZFAwC1qsJ0P_N9qIdudDj6e_1uy13C3OzoayEFv2N-Ce_n9Vm5e-ALW5rNF-hJh0ly_yuXhJ7qSDiU |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bT9swFD5CIE17GezeMZgfULVJpKR2Ls4jpSuUdlU1AUPswfIlRYgprUqLVp72E_Yb90s4jptmbENCe0qk2Il9fOzzndjnOwBb6HKgVZOpl2itvUAl2lMIizzGU-3rQKMFtsHJn3rRwXFweBqe_pbqy_FDLH642ZmRr9d2go_MYKckDVXG1KIYV9-VIPK59buan0vmqKhed6kI8-gTTl28rK26M694xxCtWJl-_xfKvAtac6vTWoWzor3usMllbTpRNX3zB5Xjf3VoDZ7MsSjZdcrzFJbS7BlU-47MerZNjsrYrKttUiX9kuZ69hy-7pL6rx8_sUcj0pCz1EZjktHYbvzYJZQUbOUEYTEpSMWzc3KRkeuLyXjobq6HRNsEIe5IHnnfPmmf7H14Acetj0d7B948VYOnWYgiZsYkUhoaoGKGMmax5kFilKRU143k_kCirZRsEHPJJVXoBiEyRd8zkqE2NJXsJSxnwyx9DcRiJE5thL6x79Do0cUDFjDpRypS3K9AtRg3oec85jadxjfhGJipQEEKFGQFyKLgyFF3_F2kmg_84rkcX9qTbnEovvT2RaNLD7udTkec4bsKzRA4_-ymiszS4fRKxMxCXgTKFXjlNKb8WBIzhNusAlv5uN_XCtFoNvHy5mHF3sGjfrMluu1eZx0e55tb-dnCt7A8GU_TDcRIE7WZz4ZbqL8M3Q |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+1%E2%80%90step+Bayesian+predictive+approach+for+evaluating+in+vitro+in+vivo+correlation+%28IVIVC%29&rft.jtitle=Biopharmaceutics+%26+drug+disposition&rft.au=Gould%2C+A.+Lawrence&rft.au=Agrawal%2C+Nancy+G.+B.&rft.au=Goel%2C+Thanh+V.&rft.au=Fitzpatrick%2C+Shaun&rft.date=2009-10-01&rft.issn=0142-2782&rft.eissn=1099-081X&rft.volume=30&rft.issue=7&rft.spage=366&rft.epage=388&rft_id=info:doi/10.1002%2Fbdd.672&rft.externalDBID=n%2Fa&rft.externalDocID=10_1002_bdd_672 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0142-2782&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0142-2782&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0142-2782&client=summon |