Nanoparticles and convergence of artificial intelligence for targeted drug delivery for cancer therapy: Current progress and challenges

Polyhydroxyalkanoates (PHAs) and its copolymer nanocarrier application in cancer treatment: An overview and challenges

In the modern era, nanomedicine has developed novel drug-delivery strategies to improve chemotherapy. Nanotechnological-based treatment approaches for cancer through targeted tumour drug delivery and stimulus-responsive tumour microenvironment have gained tremendous success in oncology. The application of building block materials of these nanomedicines plays a vital role in cancer remediation. Despite successful application in various medical treatments, nanocarriers' lack of biodegradability and biocompatibility makes their use in a clinical context difficult. In addition, the preparation of current drug delivery systems is a major constraint. The current cancer treatment methods aim to destroy diseased tissue, frequently with the use of radiation and chemotherapy. These treatment options are accompanied by a significant level of toxicity, which has excellent potential to further medical issues in the afflicted patient. Polyhydroxyalkanoate (PHA) polymers are biodegradable and biocompatible polyesters that can potentially be used as nanoparticular delivery systems for cancer treatment. Previously, PHA has shown tremendous application as a packaging material in the food and pharma industry. PHA-based nanocarriers are an effective drug delivery system because of their non-immunogenicity, regulated drug release, high drug loading capacity, and targeted drug delivery. This review focuses on creating and using PHA-based nanocarriers in cancer treatment. Despite its many benefits, PHA-based nanocarriers have yet to progress to clinical trials for drug delivery applications due to several issues, including the polymers' hydrophobic nature and high production costs. This review examines these challenges along with existing alternatives.

Unveiling Green Synthesis and Biomedical Theranostic paradigms of Selenium Nanoparticles (SeNPs) - A state-of-the-art comprehensive update

The advancements in nanotechnology, pharmaceutical sciences, and healthcare are propelling the field of theranostics, which combines therapy and diagnostics, to new heights; emphasizing the emergence of selenium nanoparticles (SeNPs) as versatile theranostic agents. This comprehensive update offers a holistic perspective on recent developments in the synthesis and theranostic applications of SeNPs, underscoring their growing importance in nanotechnology and healthcare. SeNPs have shown significant potential in multiple domains, including antioxidant, anti-inflammatory, anticancer, antimicrobial, antidiabetic, wound healing, and cytoprotective therapies. The review highlights the adaptability and biocompatibility of SeNPs, which are crucial for advanced disease detection, monitoring, and personalized treatment. Special emphasis is placed on advancements in green synthesis techniques, underscoring their eco-friendly and cost-effective benefits in biosensing, diagnostics, imaging and therapeutic applications. Additionally, the appraisal scrutinizes the progressive trends in smart stimuli-responsive SeNPs, conferring their role in innovative solutions for disease management and diagnostics. Despite their promising therapeutic and prophylactic potential, SeNPs also present several challenges, particularly regarding toxicity concerns. These challenges and their implications for clinical translation are thoroughly explored, providing a balanced view of the current state and prospects of SeNPs in theranostic applications.

Artificial intelligence in nanotechnology for treatment of diseases

Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools. AI has been employed in designing, characterising and manufacturing drug delivery nanosystems, as well as in predicting treatment efficiency. AI's potential to personalise drug delivery based on individual patient factors, optimise formulation design and predict drug properties has been highlighted. By leveraging AI and large datasets, developing safe and effective DDSs can be accelerated, ultimately improving patient outcomes and advancing pharmaceutical sciences. This review article investigates the role of AI in the development of nano-DDSs, with a focus on their therapeutic applications. The use of AI in DDSs has the potential to revolutionise treatment optimisation and improve patient care.

Emerging Applications of Nanoparticles in the Diagnosis and Treatment of Breast Cancer

Breast cancer remains the most prevalent cancer among women worldwide, driving the urgent need for innovative approaches to diagnosis and treatment. This review highlights the pivotal role of nanoparticles in revolutionizing breast cancer management through advancements of interconnected approaches including targeted therapy, imaging, and personalized medicine. Nanoparticles, with their unique physicochemical properties, have shown significant promise in addressing current treatment limitations such as drug resistance and nonspecific systemic distribution. Applications range from enhancing drug delivery systems for targeted and sustained release to developing innovative diagnostic tools for early and precise detection of metastases. Moreover, the integration of nanoparticles into photothermal therapy and their synergistic use with existing treatments, such as immunotherapy, illustrate their transformative potential in cancer care. However, the journey towards clinical adoption is fraught with challenges, including the chemical feasibility, biodistribution, efficacy, safety concerns, scalability, and regulatory hurdles. This review delves into the current state of nanoparticle research, their applications in breast cancer therapy and diagnosis, and the obstacles that must be overcome for clinical integration.

Point biserial correlation symbiotic organism search nanoengineering based drug delivery for tumor diagnosis

Nanoparticulate systems have the prospect of accounting for a new making of drug delivery systems. Nanotechnology is manifested to traverse the hurdle of both physical and biological sciences by implementing nanostructures indistinct fields of science, particularly in nano-based drug delivery. The low delivery efficiency of nanoparticles is a critical obstacle in the field of tumor diagnosis. Several nano-based drug delivery studies are focused on for tumor diagnosis. But, the nano-based drug delivery efficiency was not increased for tumor diagnosis. This work proposes a method called point biserial correlation symbiotic organism search nanoengineering-based drug delivery (PBC-SOSN). The objective and aim of the PBC-SOSN method is to achieve higher drug delivery efficiency and lesser drug delivery time for tumor diagnosis. The contribution of the PBC-SOSN is to optimized nanonengineering-based drug delivery with higher r drug delivery detection rate and smaller drug delivery error detection rate. Initially, raw data acquired from the nano-tumor dataset, and nano-drugs for glioblastoma dataset, overhead improved preprocessed samples are evolved using nano variational model decomposition-based preprocessing. After that, the preprocessed samples as input are subjected to variance analysis and point biserial correlation-based feature selection model. Finally, the preprocessed samples and features selected are subjected to symbiotic organism search nanoengineering (SOSN) to corroborate the objective. Based on these findings, point biserial correlation-based feature selection and a symbiotic organism search nanoengineering were tested for their modeling performance with a nano-tumor dataset and nano-drugs for glioblastoma dataset, finding the latter the better algorithm. Incorporated into the method is the potential to adjust the drug delivery detection rate and drug delivery error detection rate of the learned method based on selected features determined by nano variational model decomposition for efficient drug delivery.

Biochemical implications of robotic surgery: a new frontier in the operating room

Robotic surgery represents a milestone in surgical procedures, offering advantages such as less invasive methods, elimination of tremors, scaled motion, and 3D visualization. This in-depth analysis explores the complex biochemical effects of robotic methods. The use of pneumoperitoneum and steep Trendelenburg positioning can decrease pulmonary compliance and splanchnic perfusion while increasing hypercarbia. However, robotic surgery reduces surgical stress and inflammation by minimizing tissue trauma. This contributes to faster recovery but may limit immune function. Robotic procedures also limit ischemia-reperfusion injury and oxidative damage compared to open surgery. They also help preserve native antioxidant defenses and coagulation. In a clinical setting, robotic procedures reduce blood loss, pain, complications, and length of stay compared to traditional procedures. However, risks remain, including device failure, the need for conversion to open surgery and increased costs. On the oncology side, there is still debate about margins, recurrence, and long-term survival. The advent of advanced technologies, such as intraoperative biosensors, localized drug delivery systems, and the incorporation of artificial intelligence, may further improve the efficiency of robotic surgery. However, ethical dilemmas regarding patient consent, privacy, access, and regulation of this disruptive innovation need to be addressed. Overall, this review sheds light on the complex biochemical implications of robotic surgery and highlights areas that require additional mechanistic investigation. It presents a comprehensive approach to responsibly maximize the potential of robotic surgery to improve patient outcomes, integrating technical skill with careful consideration of physiological and ethical issues.

Exploring and Analyzing the Systemic Delivery Barriers for Nanoparticles

Most nanomedicines require efficient in vivo delivery to elicit diagnostic and therapeutic effects. However, en route to their intended tissues, systemically administered nanoparticles often encounter delivery barriers. To describe these barriers, we propose the term "nanoparticle blood removal pathways" (NBRP), which summarizes the interactions between nanoparticles and the body's various cell-dependent and cell-independent blood clearance mechanisms. We reviewed nanoparticle design and biological modulation strategies to mitigate nanoparticle-NBRP interactions. As these interactions affect nanoparticle delivery, we studied the preclinical literature from 2011-2021 and analyzed nanoparticle blood circulation and organ biodistribution data. Our findings revealed that nanoparticle surface chemistry affected the in vivo behavior more than other nanoparticle design parameters. Combinatory biological-PEG surface modification improved the blood area under the curve by ~418%, with a decrease in liver accumulation of up to 47%. A greater understanding of nanoparticle-NBRP interactions and associated delivery trends will provide new nanoparticle design and biological modulation strategies for safer, more effective, and more efficient nanomedicines.

The future of plant based green carbon dots as cancer Nanomedicine: From current progress to future Perspectives and beyond

BACKGROUND

The emergence of carbon dots (CDs) as anticancer agents had sparked a transformation in cancer research and treatment strategies. These fluorescent CDs, initially introduced in the early 2000 s, possess exceptional biocompatibility, tunable fluorescence, and surface modification capabilities, positioning them as promising tools in biomedical applications.

AIM OF REVIEW

The review encapsulates the transformative trajectory of green CDs as future anticancer nanomedicine, poised to redefine the strategies employed in the ongoing fight against cancer.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The versatility of CDs was rooted in their various synthesis approaches and sustainable strategies, enabling their adaptability for diverse therapeutic uses. In vitro studies had showcased CDs' selective cytotoxicity against cancer cells while sparing healthy counterparts, forming the basis for targeted therapeutic potential. This selectivity had been attributed to the reactive oxygen species (ROS) generation, which opened avenues for targeted interventions. The role of CDs in combination therapies, synergizing with chemotherapy, radiotherapy, and targeted approaches was then investigated to heighten their anticancer efficacy. Notably, in vivo studies highlight CDs' remarkable biocompatibility and minimal side effects, endorsing their translational promise. Integration with conventional cancer treatments such as chemotherapy, radiotherapy, and immunotherapy amplified the versatility and effectiveness of CDs. The exploration of CDs' applications in photo-induced treatments further solidified their significance, positioning them as photosensitizers (PS) in photodynamic therapy (PDT) and photothermal agents (PA) in photothermal therapy (PTT). In PDT, CDs triggered the generation of ROS upon light exposure, facilitating cancer cell elimination, while in PTT, they induced localized hyperthermia within cancer cells, enhancing therapeutic outcomes. In vitro and in vivo investigations validated CDs' efficacy in PDT and PTT, affirming their potential for integration into combination therapies. Looking ahead, the future of CDs in anticancer treatment encompasses bioavailability, biocompatibility, synergistic treatments, tumor targeting, artificial intelligence (AI) and robotics integration, personalized medicine, and clinical translation. This transformative odyssey of CDs as future anticancer agents is poised to redefine the paradigm of cancer treatment strategies.

The adsorption routes of 4IR technologies for effective desulphurization using cellulose nanocrystals: Current trends, challenges, and future perspectives

The combustion of liquid fuels as energy sources for transportation and power generation has necessitated governments worldwide to direct petroleum refineries to produce sulphur-free fuels for environmental sustainability. This review highlights the novel application of artificial intelligence for optimizing and predicting adsorptive desulphurization operating parameters and green isolation conditions of nanocellulose crystals from lignocellulosic biomass waste. The shortcomings of the traditional modelling and optimization techniques are stated, and artificial intelligence's role in overcoming them is broadly discussed. Also, the relationship between nanotechnology and artificial intelligence and the future perspectives of fourth industrial revolution (4IR) technologies for optimization and modelling of the adsorptive desulphurization process are elaborately discussed. The current study surveys different adsorbents used in adsorptive desulphurization and how biomass-based nanocellulose crystals (green adsorbents) are suitable alternatives for achieving cleaner fuels and environmental sustainability. Likewise, the present study reports the challenges and potential solutions to fully implementing 4IR technologies for effective desulphurization of liquid fuels in petroleum refineries. Hence, this study provides insightful information to benefit a broad audience in waste valorization for sustainability, environmental protection, and clean energy generation.

Artificial Intelligence's Impact on Drug Discovery and Development From Bench to Bedside

Artificial intelligence (AI) techniques have the potential to revolutionize drug release modeling, optimize therapy for personalized medicine, and minimize side effects. By applying AI algorithms, researchers can predict drug release profiles, incorporate patient-specific factors, and optimize dosage regimens to achieve tailored and effective therapies. This AI-based approach has the potential to improve treatment outcomes, enhance patient satisfaction, and advance the field of pharmaceutical sciences. International collaborations and professional organizations play vital roles in establishing guidelines and best practices for data collection and sharing. Open data initiatives can enhance transparency and scientific progress, facilitating algorithm validation.

Chitosan Nanoparticles for Gastroesophageal Reflux Disease Treatment

Gastroesophageal Reflux Disease (GERD) is a chronic ailment that results from the backward flow of stomach acid into the esophagus, causing heartburn and acid regurgitation. This review explores nanotechnology as a novel treatment approach for GERD. Chitosan nanoparticles (CSNPs) offer several advantages, including biocompatibility, biodegradability, and targeted drug delivery capabilities. CSNPs have been extensively studied due to their ability to encapsulate and release medications in a controlled manner. Different nanoparticle (NP) delivery systems, including gels, microspheres, and coatings, have been developed to enhance drug retention, drug targeting, and controlled release in the esophagus. These nanoparticles can target specific molecular pathways associated with acid regulation, esophageal tissue protection, and inflammation modulation. However, the optimization of nanoparticle formulations faces challenges, including ensuring stability, scalability, and regulatory compliance. The future may see CSNPs combined with other treatments like proton pump inhibitors (PPIs) or mucosal protectants for a synergistic therapeutic approach. Thus, CSNPs provide exciting opportunities for novel GERD treatment strategies.

Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design

Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.

Recent Advances in Cancer Immunotherapy Delivery Modalities

Immunotherapy is crucial in fighting cancer and achieving successful remission. Many novel strategies have recently developed, but there are still some obstacles to overcome before we can effectively attack the cancer cells and decimate the cancer environment by inducing a cascade of immune responses. To successfully demonstrate antitumor activity, immune cells must be delivered to cancer cells and exposed to the immune system. Such cutting-edge technology necessitates meticulously designed delivery methods with no loss or superior homing onto cancer environments, as well as high therapeutic efficacy and fewer adverse events. In this paper, we discuss recent advances in cancer immunotherapy delivery techniques, as well as their future prospects.