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

Grant number:20/05556-0
Support Opportunities:Regular Research Grants
Start date: September 01, 2020
End date: February 28, 2023
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
Principal Investigator:Diego Samuel Rodrigues
Grantee:Diego Samuel Rodrigues
Host Institution: Faculdade de Tecnologia (FT). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil
City of the host institution:Limeira
Associated researchers: Anibal Thiago Bezerra ; José Ricardo de Arruda Miranda ; Verónica Andrea González-López
Associated research grant(s):24/21475-1 - 16th Dynamical Systems Applied on Biology and Natural Sciences - DSABNS 2025, AR.EXT

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)

Articles published in Agência FAPESP Newsletter about the research grant:
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Scientific publications
(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)
BEZERRA, ANIBAL THIAGO; PINTO, LEONARDO ANTONIO; RODRIGUES, DIEGO SAMUEL; BITTENCOURT, GABRIELA NOGUEIRA; DE ARRUDA MANCERA, PAULO FERNANDO; DE ARRUDA MIRANDA, JOSE RICARDO. Classification of gastric emptying and orocaecal transit through artificial neural networks. Mathematical Biosciences and Engineering, v. 18, n. 6, p. 9511-9524, . (20/05556-0)