Advances of medical nanorobots for future cancer treatments

Journal of Hematology & Oncology, Journal Year: 2023, Volume and Issue: 16(1)

Published: July 14, 2023

Early detection and diagnosis of many cancers is very challenging. Late stage a cancer always leads to high mortality rates. It imperative develop novel more sensitive effective therapeutic methods for treatments. The development new treatments has become crucial aspect medical advancements. Nanobots, as one the most promising applications nanomedicines, are at forefront multidisciplinary research. With progress nanotechnology, nanobots enable assembly deployment functional molecular/nanosized machines increasingly being utilized in treatment. In recent years, various practical have transitioned from theory practice, vitro experiments vivo applications. this paper, we review analyze advancements treatments, with particular emphasis on their key fundamental features drug delivery, tumor sensing diagnosis, targeted therapy, minimally invasive surgery, other comprehensive At same time, discuss challenges potential research opportunities revolutionizing future, expected sophisticated capable performing multiple functions tasks, ultimately becoming true nanosubmarines bloodstream.

Language: Английский

---

Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis

Progress in molecular biology and translational science, Journal Year: 2022, Volume and Issue: unknown, P. 57 - 100

Published: Jan. 1, 2022

Language: Английский

---

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review

Archives of Toxicology, Journal Year: 2023, Volume and Issue: 97(4), P. 963 - 979

Published: March 7, 2023

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation order to ensure safe application living organisms. Artificial intelligence (AI) and machine learning (MI) can be used analyze interpret large amounts data the field toxicology, such as from toxicological databases high-content image-based screening data. Physiologically based pharmacokinetic (PBPK) models nano-quantitative structure-activity relationship (QSAR) predict behavior toxic effects nanomaterials, respectively. PBPK Nano-QSAR are prominent ML tool for harmful event analysis that is understand mechanisms by which chemical compounds cause effects, while toxicogenomics study genetic basis responses Despite potential these methods, there still many challenges uncertainties need addressed field. In this review, we provide an overview artificial (ML) techniques nanomedicine nanotoxicology better materials at nanoscale.

Language: Английский

---

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology

Biomedicine & Pharmacotherapy, Journal Year: 2023, Volume and Issue: 163, P. 114784 - 114784

Published: April 28, 2023

More information about a person's genetic makeup, drug response, multi-omics and genomic response is now available leading to gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled computational toxicogenomics as pivotal part next-gen risk assessment paradigm. Artificial Intelligence (AI) potential provid new ways analyzing patient data making predictions treatment outcomes or toxicity. As medicine involve huge processing, AI can expedite this process by providing powerful analysis, interpretation algorithms. integrate multitude including genome data, records, clinical identify patterns derive predictive models anticipating assessing any approaches. In article, we have studied current trends future perspectives in & toxicology, role connecting two fields, impact on toxicology. work, also study key challenges limitations medicine, toxicogenomics, order fully realize their potential.

Language: Английский

---

Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 52726 - 52739

Published: Jan. 1, 2023

Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial predict fate drugs placental barrier; it could serve as an alternative animal testing. The ability a molecule effectively cross barrier and reach fetus determines drug's toxicological effects on fetus. In this regard, our study aims permeability molecules across barrier. Based publicly available datasets, several machine learning models are comprehensively analysed different fingerprints toolkits find best suitable models. Several dataset analysis utilised data diversity. Further, demonstrates application neural network-based permeability. K-nearest neighbour (KNN), standard vector classifier (SVC) Multi-layer perceptron (MLP) found be best-performing with prediction percentage 82%, 86.4% 90.8%, respectively. Different compared chosen set drugs, like Aliskiren, some insulin secretagogues glucocorticoids negative while predicting

Language: Английский

---

Herbal concoction Unveiled: A computational analysis of phytochemicals' pharmacokinetic and toxicological profiles using novel approach methodologies (NAMs)

Current Research in Toxicology, Journal Year: 2023, Volume and Issue: 5, P. 100118 - 100118

Published: Jan. 1, 2023

Herbal medications have an extensive history of use in treating various diseases, attributed to their perceived efficacy and safety. Traditional medicine practitioners contemporary healthcare providers shown particular interest herbal syrups, especially for respiratory illnesses associated with the SARS-CoV-2 virus. However, current understanding pharmacokinetic toxicological properties phytochemicals these mixtures is limited. This study presents a comprehensive computational analysis utilizing novel approach methodologies (NAMs) investigate profiles syrup, leveraging in-silico techniques prediction tools such as PubChem, SwissADME, Molsoft's database. Although molecular dynamics, docking, broader system-wide analyses were not considered, future studies hold potential further investigation areas. By combining drug-likeness simulation, researchers identify diverse suitable complex medication development examining pharmacokinetic-toxicological phytopharmaceutical syrup. The focuses on solutions infections, goal adding pool all-natural treatments ailments. research has revolutionize environmental alternative by models innovative analytical enhanced therapeutic benefits explore network-based systems biology approaches deeper interactions biological systems. Overall, our offers valuable insights into concoction. paves way advancements medicine. we acknowledge need address aforementioned topics that adequately covered this research.

Language: Английский

---

Navigating regulatory challenges in molecularly tailored nanomedicine

Published: April 25, 2024

Nanomedicine, a convergence of nanotechnology and medical sciences, has unleashed transformative potential in healthcare. However, harnessing the benefits nanomedicine requires thorough understanding its regulatory landscape. An in-depth discussion considerations, including molecular safety assessment, harmonization landscape, shaping future innovation, is presented this discourse. The assessment entails evaluating interactions between nanoparticles biomolecules, ensuring compatibility at level. Harmonization involves developing international standards guidelines for consistent approach, while innovations emphasizes integrating assessments into early stages development. Challenges encompass need standardized methods, balancing innovation with safety, addressing unique features novel designs. As landscape evolves, effective strategies must navigate intricate interplay molecules technologies, both patient access product safety.

Language: Английский

---

AI-enhanced biomedical micro/nanorobots in microfluidics

Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(5), P. 1419 - 1440

Published: Jan. 1, 2024

Although developed independently at the beginning, AI, micro/nanorobots and microfluidics have become more intertwined in past few years which has greatly propelled cutting-edge development fields of biomedical sciences.

Language: Английский

---

Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment

Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104653 - 104653

Published: Feb. 1, 2025

Language: Английский

---

Artificial Intelligence Enabled Biomineralization for Eco‐Friendly Nanomaterial Synthesis: Charting Future Trends

Nano Select, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 30, 2025

ABSTRACT The applications of nanoparticles (NPs) have shown tremendous growth during the last decade in field biomedicine. Although chemical and physical methods dominate large‐scale NP synthesis, such are also known for their adverse impact on environment health. In contrast, use biological systems provides a sustainable alternative producing functional NPs by biomineralization process. transformative power artificial intelligence (AI) has been proven prudent diagnosis, drug development, therapy, clinical decision‐making. AI can be utilized tailored design, scale‐up biomedical applications. present review an overview process its advantages over other eco‐friendly synthesis opportunities. Specific emphasis is provided application cancer therapy how biologically compatible improve management. Finally, to best our knowledge, potential integrating comprehensively analyzed first time. Additionally, help surpass conventionally synthesized toxicity toxicology material science provided.

Language: Английский

---