Dose Dependencies and Biocompatibility of Renal Clearable Gold Nanoparticles: From Mice to Non‐human Primates

Xu, Jing; Yu, Mengxiao; Peng, Chuanqi; Carter, Phoebe; Tian, Jia; Ning, Xuhui; Zhou, Qinhan; Tu, Qiu; Zhang, Greg; Dao, Anthony; Jiang, Xuewu; Kapur, Payal; Hsieh, Jer‐Tsong; Zhao, Xudong; Liu, Pengyu; Zheng, Jie

doi:10.1002/ange.201710584

Cited by 19 publications

(9 citation statements)

References 45 publications

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“…Increasing the Mn-doping concentration reduces the distribution half-life time and improves the elimination half-life time. Clearance (CL) 37-39 is a parameter used to measure the efficiency of the body toward eliminating particles through excretory or metabolic pathways. CL for Mn 0.32 Fe 2.68 O 4 , Mn 0.37 Fe 2.63 O 4 , Mn 0.75 Fe 2.25 O 4 , MnFe 2 O 4 , Mn 1.23 Fe 1.77 O 4 and Mn 1.57 Fe 1.43 O 4 nanoparticles were found to be 1, 0.67, 0.42, 0.48, 0.41 and 0.26 mL/h, respectively.…”

Section: Resultsmentioning

confidence: 99%

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy

Miao¹,

Xie²,

Zhang³

et al. 2019

Theranostics

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The development of a highly efficient, low-toxicity, ultrasmall ferrite nanoparticle-based T 1 contrast agent for high-resolution magnetic resonance imaging (MRI) is highly desirable. However, the correlations between the chemical compositions, in vitro T 1 relaxivities, in vivo nano-bio interactions and toxicities remain unclear, which has been a challenge in optimizing the in vivo T 1 contrast efficacy. Methods : Ultrasmall (3 nm) manganese ferrite nanoparticles (Mn x Fe 3-x O 4 ) with different doping concentrations of the manganese ions (x = 0.32, 0.37, 0.75, 1, 1.23 and 1.57) were used as a model system to investigate the composition-dependence of the in vivo T 1 contrast efficacy. The efficacy of liver-specific contrast-enhanced MRI was assessed through systematic multiple factor analysis, which included the in vitro T 1 relaxivity, in vivo MRI contrast enhancement, pharmacokinetic profiles (blood half-life time, biodistribution) and biosafety evaluations ( in vitro cytotoxicity testing, in vivo blood routine examination, in vivo blood biochemistry testing and H&E staining to examine the liver). Results : With increasing Mn doping, the T 1 relaxivities initially increased to their highest value of 10.35 mM -1 s -1 , which was obtained for Mn 0.75 Fe 2.25 O 4 , and then the values decreased to 7.64 m M -1 s -1 , which was obtained for the Mn 1.57 Fe 1.43 O 4 nanoparticles. Nearly linear increases in the in vivo MRI signals (ΔSNR) and biodistributions (accumulation in the liver) of the Mn x Fe 3-x O 4 nanoparticles were observed for increasing levels of Mn doping. However, both the in vitro and in vivo biosafety evaluations suggested that Mn x Fe 3-x O 4 nanoparticles with high Mn-doping levels (x > 1) can induce significant toxicity. Conclusion : The systematic multiple factor assessment indicated that the Mn x Fe 3-x O 4 (x = 0.75-1) nanoparticles were the optimal T 1 contrast agents with higher in vivo efficacies for liver-specific MRI than those of the other compositions of the Mn ...

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Section: Resultsmentioning

confidence: 99%

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy

Miao¹,

Xie²,

Zhang³

et al. 2019

Theranostics

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“…Anatomical differences in the relative number of nephrons per gram of kidney tissue are higher in small animals than in humans 88. There have been no noteworthy species differences reported in the vascular architecture and immunological function of the kidneys related to the elimination (renal excretion) of nanomaterials 89.…”

Section: Extrapolating Nanomaterials Pharmacokinetics From Preclinicalmentioning

confidence: 98%

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

Valic¹,

Zheng²

2019

Theranostics

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A critical step in the translational science of nanomaterials from preclinical animal studies to humans is the comprehensive investigation of their disposition (or ADME) and pharmacokinetic behaviours. Disposition and pharmacokinetic data are ideally collected in different animal species (rodent and nonrodent), at different dose levels, and following multiple administrations. These data are used to assess the systemic exposure and effect to nanomaterials, primary determinants of their potential toxicity and therapeutic efficacy. At toxic doses in animal models, pharmacokinetic (termed toxicokinetic) data are related to toxicologic findings that inform the design of nonclinical toxicity studies and contribute to the determination of the maximum recommended starting dose in clinical phase 1 trials. Nanomaterials present a unique challenge for disposition and pharmacokinetic investigations owing to their prolonged circulation times, nonlinear pharmacokinetic profiles, and their extensive distribution into tissues. Predictive relationships between nanomaterial physicochemical properties and behaviours in vivo are lacking and are confounded by anatomical, physiological, and immunological differences amongst preclinical animal models and humans. These challenges are poorly understood and frequently overlooked by investigators, leading to inaccurate assumptions of disposition, pharmacokinetic, and toxicokinetics profiles across species that can have profoundly detrimental impacts for nonclinical toxicity studies and clinical phase 1 trials. Herein are highlighted two research tools for analysing and interpreting disposition and pharmacokinetic data from multiple species and for extrapolating this data accurately in humans. Empirical methodologies and mechanistic mathematical modelling approaches are discussed with emphasis placed on important considerations and caveats for representing nanomaterials, such as the importance of integrating physiological variables associated with the mononuclear phagocyte system (MPS) into extrapolation methods for nanomaterials. The application of these tools will be examined in recent examples of investigational and clinically approved nanomaterials. Finally, strategies for applying these extrapolation tools in a complementary manner to perform dose predictions and in silico toxicity assessments in humans will be explained. A greater familiarity with the available tools and prior experiences of extrapolating nanomaterial disposition and pharmacokinetics from preclinical animal models to humans will hopefully result in a more straightforward roadmap for the clinical translation of promising nanomaterials.

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“…For example, monkey dose can be obtained from mouse dose by dividing the no-observed-adverse-effect-level of mice by 4. 212 In Ovo Assessment of the Toxicity of AuNPs Studies using chicken embryo as a model of toxicity. Chicken embryo has a rapid growth rate and is independent of the mother.…”

Section: Determination Of the In Vivo Toxicity Of Aunpsmentioning

confidence: 99%

Toxicological Behavior of Gold Nanoparticles on Various Models: Influence of Physicochemical Properties and Other Factors

et al. 2019

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Potential applications of gold nanoparticles in biomedicine have increasingly been reported on account of the ease of synthesis, bioinert characteristics, optical properties, chemical stability, high biocompatibility, and specificity. The safety of these particles remains a great concern, as there are differences among toxicity study protocols used. This article focuses on integrating results of research on the toxicological behavior of gold nanoparticles. This can be influenced by the physicochemical properties, including size, shape, surface charge, and other factors, such as methods used in the synthesis of gold nanoparticles, models used, dose, in vivo route of administration, and interference of gold nanoparticles with in vitro toxicity assay systems. Several researchers have reported toxicological studies with regard to gold nanoparticles, using various in vitro, in vivo, and in ovo models. The conflicting results concerning the toxicity of gold nanoparticles should thus be addressed to justify the safe use of gold nanoparticles in biomedicine.

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Dose Dependencies and Biocompatibility of Renal Clearable Gold Nanoparticles: From Mice to Non‐human Primates

Cited by 19 publications

References 45 publications

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

Toxicological Behavior of Gold Nanoparticles on Various Models: Influence of Physicochemical Properties and Other Factors

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Dose Dependencies and Biocompatibility of Renal Clearable Gold Nanoparticles: From Mice to Non‐human Primates

Cited by 19 publications

References 45 publications

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T1 Contrast Efficacy

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T1 Contrast Efficacy

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

Toxicological Behavior of Gold Nanoparticles on Various Models: Influence of Physicochemical Properties and Other Factors

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Product

Resources

About

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy

Composition-Tunable Ultrasmall Manganese Ferrite Nanoparticles: Insights into their In Vivo T₁ Contrast Efficacy