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dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2023-12-20T20:58:59Z
dc.date.available2023-12-20T20:58:59Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.13067/2889
dc.description.abstractCommonly, it is accepted that oncology treatment would yield outcomes with a certain determinism without any quantitative support or mathematical model that establishes such deter minations. Nowadays, with the advent of nanomedicine, the targeting drug delivery scheme has emerged, whose central objective is the uptake of nanoparticles by tumors. Once they are injected into the bloodstream, it is unclear as to which process governs the directing of nanoparticles towards the desired target, deterministic or stochastic. In any scenario, an optimal outcome, small toxicity and minimal dispersion of drugs is expected. Commonly, it is expected that an important fraction of them can be internalized into tumor. In this manner, due to the fraction of nanoparticles that have failed to uptake, the success of the drug delivery scheme might be at risk. In this paper, a theory based on the sequence electrodynamics–diffusion–Bayes theorem is presented. The Bayesian probability that emerges at the end of the sequence might be telling us that dynamical processes based on the injection of electrically charged nanoparticles might be dictated by stochastic formalism. Thus, rather than expecting a deterministic process, the chain of events would convert the drug delivery scheme to be dependent on a sequence of conditional probabilities.es_PE
dc.formatapplication/pdfes_PE
dc.language.isospaes_PE
dc.publisherMDPIes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_PE
dc.subjectDrug deliveryes_PE
dc.subjectElectrodynamicses_PE
dc.subjectBayeses_PE
dc.subjectNonlinear systemses_PE
dc.titleIs Drug Delivery System a Deterministic or Probabilistic Approach? A Theoretical Model Based on the Sequence: Electrodynamics–Diffusion–Bayeses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journalMathematicses_PE
dc.description.peer-review16es_PE
dc.identifier.doihttps://doi.org/10.3390/math11214528
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.04es_PE
dc.source.issue11es_PE
dc.source.beginpage21es_PE
dc.source.endpage1es_PE


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