Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design to Toxicity Prediction

Singh, Ajay; Rosenkranz, Daniel; Ansari, Mohammad Hasan Dad; Singh, Rishabh; Kanase, Anurag; Singh, Shubham; Johnston, Blair D.; Tentschert, Jutta; Laux, Peter; Luch, Andreas

doi:10.1002/aisy.202070125

Cited by 35 publications

(21 citation statements)

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“…Neural networks-based biological activity predictions that depend on artificial intelligence and machine learning processing along with other computer-aided drug design approaches have become widely accepted as an integral step during the drug discovery process. 30 , 31 …”

Section: Resultsmentioning

confidence: 99%

Cytotoxic Potential, Metabolic Profiling, and Liposomes of Coscinoderma sp. Crude Extract Supported by in silico Analysis

Musa¹,

Elmaidomy²,

Sayed³

et al. 2021

IJN

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Introduction Sponge- Coscinoderma sp. (Family: Spongiidae) is a coastal sponge that possesses a broad variety of natural-products. However, the exact chemical constituents and cytotoxic activity of the extract are still undefinable. Methodology In the present study, the metabolomic profiling of Coscinoderma sp. dereplicated 20 compounds, utilizing liquid chromatography coupled with high-resolution mass spectrometry (LC-HRESIMS). Coscinoderma- derived crude extract, before and after encapsulation within nanosized liposomes, was in vitro screened against hepatic, breast, and colorectal carcinoma human cell lines (HepG2, MCF-7, and Caco-2, respectively). Results The identified metabolites were fit to diverse chemical classes, covering diterpenes, an indole alkaloid, sesterterpenoid, sterol, and methylherbipoline salt. Comprehensive in silico experiments predicted several compounds in the sponge-derived extract (eg, compounds 1 – 15 ) to have an anticancer potential via targeting multiple targets. The crude extract showed moderate antiproliferative activities towards studied cell lines with IC 50 values range from 10.7 to 12.4 µg/mL. The formulated extract-containing liposomes (size 141±12.3nm, PDI 0.222, zeta potential 20.8 ± 2.3), significantly enhanced the in vitro anticancer activity of the entrapped extract (IC 50 values ranged from 1.7 to 4.1 µg/mL). Discussion Encapsulation of both the hydrophilic and the lipophilic components of the extract within the lipid-based nanovesicles enhanced the cellular uptake and accessibility of the entrapped cargo. This study introduces liposomal nano-vesicles as a promising approach to improve the therapeutic potential of sponge-derived extracts.

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Section: Resultsmentioning

confidence: 99%

Cytotoxic Potential, Metabolic Profiling, and Liposomes of Coscinoderma sp. Crude Extract Supported by in silico Analysis

Musa¹,

Elmaidomy²,

Sayed³

et al. 2021

IJN

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show abstract

“…Therefore, continuing research is needed to obtain reliable information in the future. Recently, advances in machine learning and artificial intelligence immensely decoded and empowered, the cell-nanomaterial interaction modelling, which gave modern to nanomedicine to predict the biosafety and efficacy 378 , 379 and in-silico methods 380 , 381 to potentially decipher the quantitative nanostructure activity-relationship (Nano-QSAR). In 2010, the two timelines (nanoparticles and artificial intelligence) merged as artificial intelligence was applied to the task of identifying and predicting of grouping according to their properties, interaction, and toxicity of nanoparticles ( Figure 11 ).…”

Section: Discussionmentioning

confidence: 99%

“…In 2010, the two timelines (nanoparticles and artificial intelligence) merged as artificial intelligence was applied to the task of identifying and predicting of grouping according to their properties, interaction, and toxicity of nanoparticles ( Figure 11 ). 379 The fields of nanoparticles and artificial intelligence will continue to complement each other. There will be significant progress in research field of surfactant-coated nanoparticles as the develop of these technologies.…”

Section: Discussionmentioning

confidence: 99%

A Critical Review of the Use of Surfactant-Coated Nanoparticles in Nanomedicine and Food Nanotechnology

Miyazawa¹,

Itaya²,

Burdeos³

et al. 2021

IJN

115

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Surfactants, whose existence has been recognized as early as 2800 BC, have had a long history with the development of human civilization. With the rapid development of nanotechnology in the latter half of the 20th century, breakthroughs in nanomedicine and food nanotechnology using nanoparticles have been remarkable, and new applications have been developed. The technology of surfactant-coated nanoparticles, which provides new functions to nanoparticles for use in the fields of nanomedicine and food nanotechnology, is attracting a lot of attention in the fields of basic research and industry. This review systematically describes these "surfactant-coated nanoparticles" through various sections in order: 1) surfactants, 2) surfactant-coated nanoparticles, application of surfactant-coated nanoparticles to 3) nanomedicine, and 4) food nanotechnology. Furthermore, current progress and problems of the technology using surfactant-coated nanoparticles through recent research reports have been discussed.

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“…The toxicity and safety concerns are great challenges for nanomedicine clinical translation. Recent advances in machine learning and artificial intelligence immensely decoded and empowered the cell-nanomaterial interaction, which gifted the computational tool for the prediction process 125,126 and in-silico methods 127,128 to potentially decipher the quantitative nanostructure activity-relationship (Nano-QSAR) for nanotoxicology and nanotherapeutics ( Figure 6).…”

Section: Conclusion and Perspectivementioning

confidence: 99%

Nanomedicine-Based Therapeutics to Combat Acute Lung Injury

Bian¹,

Cai²,

Cui³

et al. 2021

IJN

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Acute lung injury (ALI) or its aggravated stage acute respiratory distress syndrome (ARDS) may lead to a life-threatening form of respiratory failure, resulting in high mortality of up to 30-40% in most studies. Although there have been decades of research since ALI was first described in 1967, the clinical therapeutic alternatives for ALI are still in a state of limited availability. Supportive treatment and mechanical ventilation still have priority. Despite some preclinical studies demonstrating the benefit of pharmacological interventions, none of these has been proved completely effective to date. Recent advances in nanotechnology may shed new light on the pharmacotherapy of ALI. Nanomedicine possesses targeting and synergistic therapeutic capability, thus boosting pharmaceutical efficacy and mitigating the side effects. Currently, a variety of nanomedicine with diverse frameworks and functional groups have been elaborately developed, in accordance with their lung targeting ability and the pathophysiology of ALI. The in-depth review of the current literature reveals that liposomes, polymers, inorganic materials, cell membranes, platelets, and other nanomedicine approaches have conferred attractive therapeutic benefits for ALI treatment. In this review, we explore the recent progress in the study of the nanomedicinebased therapy of ALI, presenting various nanomedical approaches, drug choices, therapeutic strategies, and outcomes, thereby providing insight into the trends.

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Artificial Intelligence and Machine Learning Empower Advanced Biomedical Material Design to Toxicity Prediction

Cited by 35 publications

References 0 publications

Cytotoxic Potential, Metabolic Profiling, and Liposomes of Coscinoderma sp. Crude Extract Supported by in silico Analysis

Cytotoxic Potential, Metabolic Profiling, and Liposomes of Coscinoderma sp. Crude Extract Supported by in silico Analysis

A Critical Review of the Use of Surfactant-Coated Nanoparticles in Nanomedicine and Food Nanotechnology

Nanomedicine-Based Therapeutics to Combat Acute Lung Injury

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