Impact of data base structure in a successful in vitro-in vivo correlation for pharmaceutical products.
The in vitro-in vivo correlation (IVIVC) (Food and Drug Administration 1997) aims to predict performances in vivo of a pharmaceutical formulation based on its in vitro characteristics. It is a complex process that (i) incorporates in a gradual and incremental way a large amount of information and (ii) requires information from different properties (formulation, analytical, clinical) and associated dedicated treatments (statistics, modeling, simulation). These results in many studies that are initiated and integrated into the specifications (quality target product profile, QTPP). This latter defines the appropriate experimental designs (quality by design, QbD) (Food and Drug Administration 2011, 2012) whose main objectives are determination (i) of key factors of development and manufacturing (critical process parameters, CPPs) and (ii) of critical points of physicochemical nature relating to active ingredients (API) and critical quality attribute (CQA) which may have implications in terms of efficiency, safety, and inoffensiveness for the patient, due to their non-inclusion. These processes generate a very large amount of data that is necessary to structure. In this context, the storage of information in a database (DB) and the management of this database (database management system, DBMS) become an important issue for the management of projects and IVIVC and more generally for development of new pharmaceutical forms. This article describes the implementation of a prototype object-oriented database (OODB) considered as a tool, which is helpful for decision taking, responding in a structured and consistent way to the issues of project management of IVIVC (including bioequivalence and bioavailability) (Food and Drug Administration 2003) necessary for the implementation of QTPP.
ESIEE Cités Descartes/BP 99, 93162, Noisy Le Grand Cedex, Paris, France, roudierb@esiee.fr.
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D001682:Biological Availability; D002626:Chemistry, Pharmaceutical / Q000379:methods; D016208:Databases, Factual; D015195:Drug Design; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000008:administration & dosage* / Q000737:chemistry / Q000378:metabolism; D012107:Research Design; D013810:Therapeutic Equivalency; D014481:United States; D014486:United States Food and Drug Administration
D004364:Pharmaceutical Preparations