Neuro-fuzzy Models as an IVIVR Tool and Their Applicability in Generic Drug Development

The usefulness of neuro-fuzzy (NF) models as an alternative in vitro - in vivo relationship (IVIVR) tool and as a support to quality by design (QbD) in generic drug development is presented. For drugs with complicated pharmacokinetics, immediate release drugs or nasal sprays, suggested level A corre...

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Bibliographic Details
Published in:The AAPS journal 2014-03, Vol.16 (2), p.324-334
Main Authors: Opara, Jerneja, Legen, Igor
Format: Article
Language:English
Subjects:
Area Under Curve
Biochemistry
Biomedical and Life Sciences
Biomedicine
Biotechnology
Drug Design
Drugs, Generic
Fuzzy Logic
Models, Theoretical
Pharmacokinetics
Pharmacology/Toxicology
Pharmacy
Research Article
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Summary:The usefulness of neuro-fuzzy (NF) models as an alternative in vitro - in vivo relationship (IVIVR) tool and as a support to quality by design (QbD) in generic drug development is presented. For drugs with complicated pharmacokinetics, immediate release drugs or nasal sprays, suggested level A correlations are not capable to satisfactorily describe the IVIVR. NF systems were recognized as a reasonable method in comparison to the published approaches for development of IVIVR. Consequently, NF models were built to predict 144 pharmacokinetic (PK) parameter ratios required for demonstration of bioequivalence (BE) for 88 pivotal BE studies. Input parameters of models included dissolution data and their combinations in different media, presence of food, formulation strength, technology type, particle size, and spray pattern for nasal sprays. Ratios of PK parameters C max or AUC were used as output variables. The prediction performance of models resulted in the following values: 79% of models have acceptable external prediction error (PE) below 10%, 13% of models have inconclusive PE between 10 and 20%, and remaining 8% of models show inadequate PE above 20%. Average internal predictability (LE) is 0.3%, and average external predictability of all models results in 7.7%. In average, models have acceptable internal and external predictabilities with PE lower than 10% and are therefore useful for IVIVR needs during formulation development, as a support to QbD and for the prediction of BE study outcome.
ISSN:1550-7416
1550-7416
DOI:10.1208/s12248-014-9569-8