Computational modeling of pharmacokinetic profiles: bayesian parameter estimation and artificial neural networks

• Grant number: 20/05556-0
• Support type: Regular Research Grants
• Duration: September 01, 2020 - August 31, 2022
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal researcher: Diego Samuel Rodrigues
• Grantee: Diego Samuel Rodrigues
• Home Institution: Faculdade de Tecnologia (FT). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil
• Assoc. researchers: Anibal Thiago Bezerra ; José Ricardo de Arruda Miranda ; Verónica Andrea González-López

Abstract

This research project is on the development and implementation of computational models for processes of drug biodistribution, aimed at the pharmacokinetics of magnetic nanoparticles, but also on processes of delayed stomach emptying. Its novel aspects include: 1) development of computational models that will provide a novel quantitative description of experimental pharmacokinetic profiles; 2) development of an in silico technology for virtual experimentation of several set-ups; 3) advances on uncertainty modeling (Bayesian statistics) and on classification problems (Artificial Neural Networks). Although the project has a theoretical-computational character, all the aspects previously described will be performed with a basis on in vivo experimental data by means of an interdisciplinarity approach in computer science, statistics, pharmacology and physics. Besides funding research advances in those areas, the project will also contribute to the initiation and training of new researchers, especially undergraduate and graduate students. (AU)