Impact of Data Base Structure in a Successful In Vitro-In Vivo Correlation for Pharmaceutical Products

Journal Title: The AAPS Journal - Year 2015, Vol 17, Issue 1

Abstract

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.

Authors and Affiliations

B. Roudier, B. Davit, H. Schütz, J-M. Cardot

Keywords

Related Articles

Statistical Power Calculations for Mixed Pharmacokinetic Study Designs Using a Population Approach

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculat...

Accelerating Drug Development Using Biomarkers: A Case Study with Sitagliptin, A Novel DPP4 Inhibitor for Type 2 Diabetes

The leveraged use of biomarkers presents an opportunity in understanding target engagement and disease impact while accelerating drug development. For effective integration in drug development, it is essential for biomar...

Deorphanization of Novel Peptides and Their Receptors

Peptide hormones and neuropeptides play important roles in endocrine and neural signaling, often using G protein-coupled receptor (GPCR)-mediated signaling pathways. However, the rate of novel peptide discovery has slowe...

Concepts and Challenges in Quantitative Pharmacology and Model-Based Drug Development

Model-based drug development (MBDD) has been recognized as a concept to improve the efficiency of drug development. The acceptance of MBDD from regulatory agencies, industry, and academia has been growing, yet today&#x02...

Modelling and PBPK Simulation in Drug Discovery

Physiologically based pharmacokinetic (PBPK) models are composed of a series of differential equations and have been implemented in a number of commercial software packages. These models require species-specific and comp...

Download PDF file
  • EP ID EP680890
  • DOI  10.1208/s12248-014-9680-x
  • Views 42
  • Downloads 0

How To Cite

B. Roudier, B. Davit, H. Schütz, J-M. Cardot (2015). Impact of Data Base Structure in a Successful In Vitro-In Vivo Correlation for Pharmaceutical Products. The AAPS Journal, 17(1), -. https://europub.co.uk/articles/-A-680890