Materials-based drug delivery approaches have garnered substantial attention in recent years due to their potential to revolutionize pharmaceutical interventions. This abstract provides a concise overview of recent advancements and future prospects in this rapidly evolving field. Materials such as nanoparticles, liposomes, polymers, and hydrogels have emerged as versatile carriers for drug delivery. These materials facilitate precise control over drug release kinetics, enabling targeted and sustained therapeutic effects. Smart materials with responsiveness to external stimuli or physiological conditions have further enhanced drug delivery precision. Personalized medicine approaches are gaining traction, tailoring drug delivery systems to individual patient profiles and needs. The horizon for materials-based drug delivery is bright. Ongoing research is focused on refining material design, streamlining production processes, and ensuring safety profiles. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial for translating these advancements into clinical practice. Additionally, the convergence of drug delivery with diagnostics and imaging holds immense potential for personalized and efficient healthcare solutions. As materials-based drug delivery continues to evolve, it stands poised to reshape the landscape of pharmaceuticals, offering the promise of more effective and patient-centered therapies for a wide range of medical conditions.

Advanced bioengineering, popularly known as regenerative dentistry, has emerged and is steadily developing with the aim of replacement of lost or injured tissues in the mouth using stem cells and other biomaterials. Conventional therapies for reparative dentistry, for instance fillings or crowns, mainly entail the replenishment of affected tissues without much concern given to the regeneration of tissues. However, these methods do not enable the natural function and aesthetics of the teeth to be maintained in the long term. There are several regenerative strategies that offer the potential to address these limitations to the extent of biologically restoring the function of teeth and their components, like pulp, dentin, bone, and periodontal tissues. Hence, stem cells, especially dental tissue derived stem cells, such as dental pulp stem cells, periodontal ligament stem cells, or apical papilla stem cells, are quite promising in this regard. These stem cells have the potentiality of generating precise dental cell lineages and thus are vital for tissue healing and renewal. Further, hydrogels, growth factors, and synthetic scaffolds help in supporting the stem cells for growth, proliferation, and differentiation into functional tissues. This review aims at describing the process of stem cell-based tissue repair biomaterials in dental regeneration, and also looks into the practice and prospects of regenerative dentistry, analysing several case reports and clinical investigations that demonstrate the efficacy and limitations of the technique. Nonetheless, the tremendous potential for regenerative dentistry is a reality that is currently challenged by biological and technical constraints, such as scarcity of stem cell sources, inadequate vascularization, and the integration of the materials used in the procedure. As we move forward, the prospects for regenerative dentistry are in subsequent developments of stem cell technology, biomaterial optimization, and individualized treatment methods, which might become increasingly integrated in dental practices globally. However, there are regulatory, ethical and economic issues that may pose a hurdle in the further advancement of this discipline.

Oral cancer is a serious concern to people all over the world because of its high mortality rate and metastatic spread to other areas of the body. Despite recent advancements in biomedical research, OC detection at an early stage remains a challenge and is complex and inaccurate with conventional diagnostics procedures. It is critical to study innovative approaches that can enable a faster, easier, non-invasive, and more precise diagnosis of OC in order to increase the survival rate of patients. In this paper, we conducted a review on how biosensors might be an excellent tool for detecting OC. This review covers the strategies that use different biosensors to target various types of biomarkers and focuses on biosensors that function at the molecular level viz. DNA biosensors, RNA biosensors, and protein biosensors. In addition, we reviewed non-invasive electrochemical methods, optical methods, and nano biosensors to analyze the OC biomarkers present in body fluids such as saliva and serum. As a result, this review sheds light on the development of ground-breaking biosensors for the early detection and diagnosis of OC.

Globally, millions of people suffer from poor wound healing, which is associated with higher mortality rates and higher healthcare costs. There are several factors that can complicate the healing process of wounds, including inadequate conditions for cell migration, proliferation, and angiogenesis, microbial infections, and prolonged inflammatory responses. Current therapeutic methods have not yet been able to resolve several primary problems; therefore, their effectiveness is limited. As a result of their remarkable properties, bio-based materials have been demonstrated to have a significant impact on wound healing in recent years. In the wound microenvironment, bio-based materials can stimulate numerous cellular and molecular processes that may enhance healing by inhibiting the growth of pathogens, preventing inflammation, and stimulating angiogenesis, potentially converting a non-healing environment to an appropriately healing one. The aim of this present review article is to provide an overview of the mechanisms underlying wound healing and its pathophysiology. The development of bio-based nanomaterials for chronic diabetic wounds as well as novel methodologies for stimulating wound healing mechanisms are also discussed.

Oral cancer (OC) is a significant global health burden, with life-saving improvements in survival and outcomes being dependent on early diagnosis and precise treatment planning. However, diagnosis and treatment planning are predicated on the synthesis of complicated information derived from clinical assessment, imaging, histopathology and patient histories. Artificial intelligence-based clinical decision support systems (AI-CDSS) provides a viable solution that can be implemented via advanced methodologies for data analysis, and synthesis for better diagnostic and prognostic evaluation. This review presents AI-CDSS as a promising solution through advanced methodologies for comprehensive data analysis. In addition, it examines current implementations of AI-CDSS that facilitate early OC detection, precise staging, and personalized treatment planning by processing multimodal patient information through machine learning, computer vision, and natural language processing. These systems effectively interpret clinical results, identify critical disease patterns (including clinical stage, site, tumor dimensions, histopathologic grading, and molecular profiles), and construct comprehensive patient profiles. This comprehensive AI-CDSS approach allows for early cancer detection, a reduction in diagnostic delays and improved intervention outcomes. Moreover, the AI-CDSS also optimizes treatment plans on the basis of unique patient parameters, tumor stages and risk factors, providing personalized therapy.