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Diabetes: Management and Pharmacotherapy01:15

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The therapy for diabetes aims to alleviate hyperglycemia-related symptoms, prevent acute metabolic decompensation, and reduce chronic end-organ complications. Glycemic control is evaluated through short-term (self-monitoring, continuous glucose monitoring) and long-term (A1c, fructosamine) metrics, enabling near real-time tracking of blood glucose levels and reflecting glycemic control over specific time frames.
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Diabetes mellitus is a chronic metabolic disorder characterized by high blood glucose levels due to inadequate insulin production, insulin resistance, or both. The condition affects millions worldwide and can significantly impact their health and quality of life.
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For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
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Insulin is released by beta cells of the pancreas when blood glucose levels are high. It facilitates glucose absorption and utilization in insulin-dependent cells with insulin receptors on their plasma membranes. Insulin promotes glucose uptake by increasing the number of glucose transport proteins in the cell membrane, allowing glucose to enter the cell. As a result, glucose utilization and ATP production are enhanced.
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems.

Aayush Kaushal1, Aanchal Musafir1, Gourav Sharma1

  • 1University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.

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|June 27, 2025
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Summary

Nanotechnology and artificial intelligence (AI) are revolutionizing diabetes management. These innovations offer improved insulin delivery, continuous glucose monitoring, and personalized treatments, enhancing patient outcomes and quality of life.

Keywords:
AI in diabetes managementcarbon nanomaterialscontinuous glucose monitoring (CGM)diabetes mellitusdiabetic wound healingdrug delivery systemselectrochemical biosensorsglucose biosensorsglucose monitoringinsulin deliverymicroneedlesnanofibersnanomedicinenanotechnologynon-invasive monitoringpolymeric nanoparticlesquantum dots (QDs)smart nanocarrierswearable biosensors

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Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Endocrinology

Background:

  • Diabetes mellitus presents a significant global health burden with limitations in current treatment efficacy and long-term control.
  • Conventional diabetes management strategies often struggle to achieve optimal glycemic control and prevent complications.
  • Nanotechnology presents novel solutions for enhancing drug delivery, glucose monitoring, and therapeutic precision in diabetes care.

Purpose of the Study:

  • To review the current advancements and future potential of nanotechnology in reshaping diabetes diagnosis and treatment.
  • To explore the integration of artificial intelligence (AI) with nanotechnology for personalized diabetes management.
  • To highlight the transformative impact of these technologies on improving patient quality of life.

Main Methods:

  • Review of current literature on nanotechnology applications in diabetes management, including nanosystems for insulin delivery and nanosensors for glucose monitoring.
  • Exploration of targeted drug delivery systems utilizing nanomaterials like microneedles, carbon nanomaterials, and quantum dots.
  • Discussion of the synergistic role of artificial intelligence (AI) in analyzing patient data for personalized treatment adjustments and predictive analytics.

Main Results:

  • Nanotechnology has led to smart nanosystems for enhanced insulin delivery and revolutionary nanosensors for real-time glucose monitoring.
  • Targeted drug delivery systems utilizing nanomaterials improve therapeutic efficacy and minimize side effects.
  • The integration of AI with nanotechnology enables personalized, data-driven treatment plans for diabetes management.

Conclusions:

  • Nanotechnology, particularly when combined with AI, offers a transformative approach to diabetes care, addressing limitations of conventional methods.
  • Continued research into the safety and biocompatibility of nanomaterials is crucial for clinical translation.
  • The convergence of nanotechnology and AI promises a future of personalized, responsive, and more effective diabetes management strategies, significantly improving patient outcomes.