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Table of contents
1 TOWARDS A REVERSE ENGINEERING APPROACH
1.1 Introduction
1.2 Research challenges in chemical product design
1.3 State-of-the-art of controlled release technologies
1.3.1 Carriers developed for controlled release
1.3.2 General analysis of release mechanisms
1.4 Current tools for prediction of controlled release
1.5 Empirical and semi/empirical mathematical models
1.5.1 Peppas equation
1.5.2 Hopfenberg model
1.5.3 Cooney model
1.5.4 Artificial neural networks
1.6 Mechanistic realistic theories
1.6.1 Theories based on Fick’s law of diffusion
1.6.2 Theories considering polymer swelling
1.6.3 Theories considering polymer swelling and drug dissolution
1.6.4 Theories considering polymer erosion/degradation
1.7 A reverse engineering methodology
1.7.1 Motivation
1.7.2 A proposed reverse engineering framework
2 MODELING
2.1 Introduction
2.1.1 Choice of a system model for ab-initio modeling
2.1.2 Objectives
2.2 Diffusion in highly concentrated emulsion systems
2.3 Theoretical estimation of mass transfer parameters
2.3.1 Permeability of surfactant layer
2.3.2 Interfacial mass transfer coefficient
2.3.3 Diffusion coefficient in liquids
2.3.4 Partition coefficient for a solute between two liquid phases
2.4 Computer-aided molecular design (CAMD) techniques
2.4.1 UNIQUAC Functional-group Activity Coefficients (UNIFAC) model
2.4.2 Modified UNIFAC (Dortmund) model
2.4.3 Revision and Extension 6 of Modified UNIFAC (Dortmund) model
2.4.4 Flash algorithm to predict L-L equilibrium
2.4.5 Atomic and Bond Contributions of van der Waals volume (VABC)
2.4.6 Estimation of liquid mixture viscosity by UNIFAC-VISCO
2.4.7 Estimation of liquid molar volume at the normal boiling point by Tyn and Callus Method
2.4.8 Estimation of critical volume by Joback Method
2.5 Mass transfer model conception
3 SIMULATION
3.1 Introduction
3.2 Logical Architecture Diagram
3.3 Cartography of materials
3.3.1 Active ingredient
3.3.2 Dispersed phase
3.3.3 Continuous phase
3.3.4 Surfactants
3.4 Objetives of a sensitivity analysis
3.4.1 Preparation of Virtual Design of Experiments (VDOE)
3.4.2 Preliminar analysis of VDOE : 64 case studies
3.4.3 Main effects and interaction plots of VDOE : 300 case studies
3.5 Conclusions of sensitivity analysis
4 EXPERIMENTAL VALIDATIONS
4.1 Introduction
4.2 Predicted and experimental distribution coefficients
4.2.1 Comparison of UNIFAC methods
4.2.2 Effect of salt content and blank/dilution media
4.2.3 Effect of material of the cartography and dispersed phase volume
4.2.4 Conclusions
4.3 Predicted and experimental mixture viscosities
4.3.1 Conclusions
4.4 Predicted and experimental release experiments
4.4.1 Preparation and characterization of emulsions
4.4.2 Experimental tests of controlled release
4.4.3 Comparison of predicted and experimental diffusion coefficients
4.4.4 Analysis of storage moduli
4.4.5 Model limitations and possible useful extensions
4.4.6 Screening of most accurate predicted scenarios
4.4.7 Principal component analysis
5 FINAL CONCLUSIONS
5.1 Summary of results and conclusions
5.2 Implications to future research
References
