Kinetic study of anti-HIV drugs by thermal decomposition analysis: a multilayer artificial neural network propose

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dc.creatorBárbara Darós de Lelis Ferreira
dc.creatorBárbara Caroline Rodrigues de Araujo
dc.creatorRita de Cássia de Oliveira Sebastião
dc.creatorMaria Irene Yoshida
dc.creatorWagner da Nova Mussel
dc.creatorSílvia Ligório Fialho
dc.creatorJamile Barbosa
dc.date.accessioned2023-03-03T19:20:31Z
dc.date.accessioned2025-09-08T23:17:03Z
dc.date.available2023-03-03T19:20:31Z
dc.date.issued2017
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.identifier.doihttps://doi.org/10.1007/s10973-016-5855-2
dc.identifier.issn1588-2926
dc.identifier.urihttps://hdl.handle.net/1843/50653
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Restrito
dc.subjectFarmacocinética
dc.subjectFísico-química
dc.subjectQuímica analítica
dc.subjectAnálise térmica
dc.subjectCalorimetria
dc.subjectRedes neurais (Computação)
dc.subjectHIV (Virus)
dc.subjectMedicamentos
dc.subject.otherEfavirenz
dc.subject.otherLamivudine
dc.subject.otherThermal decomposition analysis
dc.subject.otherArtificial neural network multilayer
dc.titleKinetic study of anti-HIV drugs by thermal decomposition analysis: a multilayer artificial neural network propose
dc.typeArtigo de periódico
local.citation.epage585
local.citation.issue1
local.citation.spage577
local.citation.volume127
local.description.resumoKinetic study by thermal decomposition of antiretroviral drugs, efavirenz (EFV) and lamivudine (3TC), usually present in the HIV cocktail, can be done by individual adjustment of the solid decomposition models. However, in some cases, unacceptable errors are found using this methodology. To circumvent this problem, here is proposed to use a multilayer perceptron neural network, with an appropriate algorithm, which constitutes a linearization of the network by setting weights between the input layer and the intermediate one and the use of kinetic models as activation functions of neurons in the hidden layer. The interconnection weights between that intermediate layer and output layer determine the contribution of each model in the overall fit of the experimental data. Thus, the decomposition is assumed to be a phenomenon that can occur following different kinetic processes. In investigated data, the kinetic thermal decomposition process was best described by R1 and D4 models for all temperatures to EFV and 3TC, respectively. The residual error of adjustment over the network is on average 10³ times lower for EFV and 10² times lower for 3TC compared to the best individual kinetic model. These improvements in physical adjustment allow detailed study of the process and therefore a more accurate calculation of the kinetic parameters such as the activation energy and frequency factor.
local.identifier.orcidhttps://orcid.org/0000-0001-7746-6675
local.identifier.orcidhttps://orcid.org/0000-0002-5158-7783
local.identifier.orcidhttps://orcid.org/0000-0002-6795-9457
local.identifier.orcidhttps://orcid.org/0000-0002-9768-9830
local.identifier.orcidhttps://orcid.org/0000-0001-8068-5211
local.publisher.countryBrasil
local.publisher.departmentICX - DEPARTAMENTO DE QUÍMICA
local.publisher.initialsUFMG
local.url.externahttps://link.springer.com/article/10.1007/s10973-016-5855-2

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