Advances in nanomedicine, coupled with novel methods of creating advanced materials at the nanoscale, have opened new perspectives for the development of healthcare and medical products. Special ...attention must be paid toward safe design approaches for nanomaterial‐based products. Recently, artificial intelligence (AI) and machine learning (ML) gifted the computational tool for enhancing and improving the simulation and modeling process for nanotoxicology and nanotherapeutics. In particular, the correlation of in vitro generated pharmacokinetics and pharmacodynamics to in vivo application scenarios is an important step toward the development of safe nanomedicinal products. This review portrays how in vitro and in vivo datasets are used in in silico models to unlock and empower nanomedicine. Physiologically based pharmacokinetic (PBPK) modeling and absorption, distribution, metabolism, and excretion (ADME)‐based in silico methods along with dosimetry models as a focus area for nanomedicine are mainly described. The computational OMICS, colloidal particle determination, and algorithms to establish dosimetry for inhalation toxicology, and quantitative structure–activity relationships at nanoscale (nano‐QSAR) are revisited. The challenges and opportunities facing the blind spots in nanotoxicology in this computationally dominated era are highlighted as the future to accelerate nanomedicine clinical translation.
Artificial intelligence and machine learning in computational nanomedicine are making great strides in nanoparticle‐modified theranostics design and development. The quantitative structure–activity relationships at nanoscale, physiologically based pharmacokinetic, absorption, distribution, metabolism, and excretion, and dosimetry‐based advanced computational models further help in understanding the in vitro physiological and pharmacokinetics and correlate the data with in vivo scenario. This review focuses on recent advances in computational modeling unlocking and empowering nanotoxicology.
: There is growing emphasis on the development of bioinspired and biohybrid micro/nanorobots for the targeted drug delivery (TDD). Particularly, stimuli-responsive materials and magnetically ...triggered systems, identified as the most promising materials and design paradigms. Despite the advances made in fabrication and control, there remains a significant gap in clinical translation.
: This review discusses the opportunities and challenges about micro/nanorobotics for the TDD as evolutionary evidence in bio-nanotechnology, material science, biohybrid robotics, and many more. Important consideration in context with the material's compatibility/immunogenicity, ethics, and security risk are reported based on the development in artificial intelligence (AI)/machine learning described in literature. The versatility and sophistication of biohybrid components design are being presented, highlighting stimuli-responsive biosystems as smart mechanisms and on-board sensing and control elements.
: Focusing on key issues for high controllability at micro- and nano-scale systems in TDD, biohybrid integration strategies, and bioinspired key competences shall be adopted. The promising outlook portraying the commercialization potential and economic viability of micro/nanorobotics will benefit to clinical translation.
More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, ...the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.
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•Established the relationship between personalized medicine and toxicology.•Outlined the importance of artificial intelligence in the current clinical decision-making process.•Overview of the various bottlenecks in artificial intelligence applications.•Provided a roadmap to future researchers on integrating precision medicine, toxicology and artificial intelligence.
Nanotoxicology and nanosafety has been a topic of intensive research for about more than 20 years. Nearly 10 000 research papers have been published on the topic, yet there exists a gap in terms of ...understanding and ways to harmonize nanorisk assessment. In this review, we revisit critically ignored parameters of nanoscale materials (e.g. band gap factor, phase instability and silver leaching problem, defect and instability plasmonic versus inorganic particles) versus their biological counterparts (cell batch-to-batch heterogeneity, biological barrier model design, cellular functional characteristics) which yield variability and nonuniformity in results. We also emphasize system biology approaches to integrate the high throughput screening methods coupled with in vivo and in silico modeling to ensure quality in nanosafety research. We emphasize and highlight the recommendation regarding bridging the mechanistic gaps in fundamental research and predictive biological response in nanotoxicology. The research community has to develop visions to predict the unforeseen problems that do not exist yet in context with nanotoxicity and public health hazards due to the burgeoning use of nanomaterial in consumer's product.
•In E172 pigments, nanoparticles were detectable by SAXS and TEM.•Nanoparticle number exceeded 50% for six of seven pigments.•Pigments are not toxic to human intestinal cells in vitro.•Black pigments ...were challenging due to magnetic properties and agglomeration.
Iron oxides used as food colorants are listed in the European Union with the number E172. However, there are no specifications concerning the fraction of nanoparticles in these pigments.
Here, seven E172 products were thoroughly characterized. Samples of all colors were analyzed with a broad spectrum of methods to assess their physico-chemical properties. Small-Angle X-ray Scattering (SAXS), Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM), zeta-potential, Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), X-ray diffraction (XRD), Brunauer-Emmett-Teller analysis (BET), Asymmetric Flow Field-Flow Fractionation (AF4) and in vitro cell viability measurements were used.
Nanoparticles were detected in all E172 samples by TEM or SAXS measurements. Quantitative results from both methods were comparable. Five pigments were evaluated by TEM, of which four had a size median below 100 nm, while SAXS showed a size median below 100 nm for six evaluated pigments. Therefore, consumers may be exposed to iron oxide nanoparticles through the consumption of food pigments.
Development and market introduction of new nanomaterials trigger the need for an adequate risk assessment of such products alongside suitable risk communication measures. Current application of ...classical and new nanomaterials is analyzed in context of regulatory requirements and standardization for chemicals, food and consumer products. The challenges of nanomaterial characterization as the main bottleneck of risk assessment and regulation are presented. In some areas, e.g., quantification of nanomaterials within complex matrices, the establishment and adaptation of analytical techniques such as laser ablation inductively coupled plasma mass spectrometry and others are potentially suited to meet the requirements. As an example, we here provide an approach for the reliable characterization of human exposure to nanomaterials resulting from food packaging. Furthermore, results of nanomaterial toxicity and ecotoxicity testing are discussed, with concluding key criteria such as solubility and fiber rigidity as important parameters to be considered in material development and regulation. Although an analysis of the public opinion has revealed a distinguished rating depending on the particular field of application, a rather positive perception of nanotechnology could be ascertained for the German public in general. An improvement of material characterization in both toxicological testing as well as end-product control was concluded as being the main obstacle to ensure not only safe use of materials, but also wide acceptance of this and any novel technology in the general public.
The correlation between altered extracellular pH and various pathological conditions, including cancer, inflammation and metabolic disorders, is well known. Bulk pH measurements cannot report the ...extracellular pH value at the cell surface. However, there is a limited number of suitable tools for measuring the extracellular pH of cells with high spatial resolution, and none of them are commonly used in laboratories around the world. In this study, a versatile ratiometric nanosensor for the measurement of extracellular pH was developed. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with the pH-inert reference dye Nile red and is surface functionalized with a pH-responsive fluorescein dye. Equipped with a targeting moiety, the nanosensor can adhere to cell membranes, allowing direct measurement of extracellular pH at the cell surface. The nanosensor exhibits a sensitive ratiometric pH response within the range of 5.5-9.0, with a calculated pKa of 7.47. This range optimally covers the extracellular pH (pH
) of most healthy cells and cells in which the pH
is abnormal, such as cancer cells. In combination with the nanosensors ability to target cell membranes, its high robustness, reversibility and its biocompatibility, the pH
nanosensor proves to be well suited for in-situ measurement of extracellular pH, even over extended time periods. This pH nanosensor has the potential to advance biomedical research by improving our understanding of cellular microenvironments, where extracellular pH plays an important role.
Various biological processes involve the translocation of macromolecules across nanopores; these pores are basically protein channels embedded in membranes. Understanding the mechanism of ...translocation is crucial to a range of technological applications, including DNA sequencing, single molecule detection, and controlled drug delivery. In this spirit, numerous efforts have been made to develop polymer translocation-based sequencing devices, these efforts include findings and insights from theoretical modeling, simulations, and experimental studies. As much as the past and ongoing studies have added to the knowledge, the practical realization of low-cost, high-throughput sequencing devices, however, has still not been realized. There are challenges, the foremost of which is controlling the speed of translocation at the single monomer level, which remain to be addressed in order to use polymer translocation-based methods for sensing applications. In this article, we review the recent studies aimed at developing control over the dynamics of polymer translocation through nanopores.
Materials at the nanoscale exhibit specific physicochemical interactions with their environment. Therefore, evaluating their toxic potential is a primary requirement for regulatory purposes and for ...the safer development of nanomedicines. In this review, to aid the understanding of nano–bio interactions from environmental and health and safety perspectives, the potential, reality, challenges, and future advances that artificial intelligence (AI) and machine learning (ML) present are described. Herein, AI and ML algorithms that assist in the reporting of the minimum information required for biomaterial characterization and aid in the development and establishment of standard operating procedures are focused. ML tools and ab initio simulations adopted to improve the reproducibility of data for robust quantitative comparisons and to facilitate in silico modeling and meta‐analyses leading to a substantial contribution to safe‐by‐design development in nanotoxicology/nanomedicine are mainly focused. In addition, future opportunities and challenges in the application of ML in nanoinformatics, which is particularly well‐suited for the clinical translation of nanotherapeutics, are highlighted. This comprehensive review is believed that it will promote an unprecedented involvement of AI research in improvements in the field of nanotoxicology and nanomedicine.
Machine learning (ML) tools in computational nanotoxicology are adopted to improve the reproducibility of the data for robust quantitative comparisons and to facilitate in silico modeling and meta‐analyses leading to a substantial contribution in nanotoxicology/nanomedicine. Herein, the potential, reality, challenges, and future advances that artificial intelligence (AI) and ML present in advanced material design and toxicity predictions are described.
A medical-toxicological view of tattooing Laux, Peter, PhD; Tralau, Tewes, PhD; Tentschert, Jutta, PhD ...
The Lancet (British edition),
01/2016, Letnik:
387, Številka:
10016
Journal Article
Recenzirano
Summary Long perceived as a form of exotic self-expression in some social fringe groups, tattoos have left their maverick image behind and become mainstream, particularly for young people. ...Historically, tattoo-related health and safety regulations have focused on rules of hygiene and prevention of infections. Meanwhile, the increasing popularity of tattooing has led to the development of many new colours, allowing tattoos to be more spectacular than ever before. However, little is known about the toxicological risks of the ingredients used. For risk assessment, safe intradermal application of these pigments needs data for toxicity and biokinetics and increased knowledge about the removal of tattoos. Other concerns are the potential for phototoxicity, substance migration, and the possible metabolic conversion of tattoo ink ingredients into toxic substances. Similar considerations apply to cleavage products that are formed during laser-assisted tattoo removal. In this Review, we summarise the issues of concern, putting them into context, and provide perspectives for the assessment of the acute and chronic health effects associated with tattooing.
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