A stochastic model of nanoparticle self-assembly on Cayley trees

Mazilu, Irina; Schwen, Eric; Banks, William; Pope, B K; Mazilu, Dan

doi:10.1088/1742-6596/574/1/012086

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…[117] Stochasticity (i.e., "randomness") further drives heterogeneity during nanotherapeutic formation. Nucleation, [118] selfassembly, [119] ligand functionalization, [58,120] drug incorporation and release, [121] and chemical degradation, [97] are all governed by thermodynamic processes that, due to entropy, inherently possess a degree of randomness. As such, most nanotherapeutic formulation procedures will inevitably yield nanoparticles with some degree of heterogeneity, highlighting the need for improved purification methods (see Section 5.3).…”

Section: Insufficiently Controlled Formulation Proceduresmentioning

confidence: 99%

Nanotherapeutic Heterogeneity: Sources, Effects, and Solutions

Morla‐Folch,

Ranzenigo,

Fayad

et al. 2023

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Nanomaterials have revolutionized medicine by enabling control over drugs’ pharmacokinetics, biodistribution, and biocompatibility. However, most nanotherapeutic batches are highly heterogeneous, meaning they comprise nanoparticles that vary in size, shape, charge, composition, and ligand functionalization. Similarly, individual nanotherapeutics often have heterogeneously distributed components, ligands, and charges. This review discusses nanotherapeutic heterogeneity's sources and effects on experimental readouts and therapeutic efficacy. Among other topics, it demonstrates that heterogeneity exists in nearly all nanotherapeutic types, examines how nanotherapeutic heterogeneity arises, and discusses how heterogeneity impacts nanomaterials’ in vitro and in vivo behavior. How nanotherapeutic heterogeneity skews experimental readouts and complicates their optimization and clinical translation is also shown. Lastly, strategies for limiting nanotherapeutic heterogeneity are reviewed and recommendations for developing more reproducible and effective nanotherapeutics provided.

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Section: Insufficiently Controlled Formulation Proceduresmentioning

confidence: 99%

Nanotherapeutic Heterogeneity: Sources, Effects, and Solutions

Morla‐Folch,

Ranzenigo,

Fayad

et al. 2023

Small

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“…In this thesis, we present a few example stochastic models and use them to introduce the basic techniques employed to study complex systems and the methods used to solve them. This thesis provides a broad overview of the recent work completed by our research group [19,20,21,22,23].…”

Section: Introductionmentioning

confidence: 99%

An introduction to stochastic self-assembly: theory, simulation and experimental applications

Schwen

2015

Preprint

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We introduce three stochastic cooperative models for particle deposition and evaporation relevant to ionic self-assembly of nanoparticles with applications in surface fabrication and nanomedicine. We present a method for mapping a stochastic model onto the Ising model, which allows us to use the established results for the Ising model to describe the properties of the system. After completing the mapping process, we investigate the time dependence of particle density using the mean field approximation. We complement this theoretical analysis with Monte Carlo simulations that support our models. These techniques, which can be used separately or in combination, are useful as pedagogical tools because they are tractable mathematically and they apply equally well to many other physical systems with nearest-neighbor interactions including voter and epidemic models.

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A stochastic model of nanoparticle self-assembly on Cayley trees

Cited by 2 publications

References 5 publications

Nanotherapeutic Heterogeneity: Sources, Effects, and Solutions

Nanotherapeutic Heterogeneity: Sources, Effects, and Solutions

An introduction to stochastic self-assembly: theory, simulation and experimental applications

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