Strategies for the delivery of antidiabetic drugs via intranasal route

Diabetes is a metabolic disorder defined by higher blood glucose levels in the body generally controlled by antidiabetic agents (oral) and insulin (subcutaneous). To avoid the limitations of the conventional routes such as lower bioavailability and pain at the site of injection in case of parenteral route modified delivery systems are proposed like transdermal, pulmonary and inhalation delivery and among the other delivery systems nasal drug delivery system that shows the advantages such as reduced frequency of dose, higher patient compliance, safety, ease of administration, prolonged residence time, improved absorption of drug in the body, higher bioavailability and stability. This review article discusses the strategies adopted for the delivery of antidiabetic drugs by the intranasal delivery system. The insulin and glucagon-like peptides on experimentation show results of improved therapeutic levels and patient compliance. The drugs are transported by the paracellular route and absorbed through the epithelial tight junctions successfully by utilising different strategies. The limitations of the nasal delivery such as irritation or burning on administration, degradation by the enzymes, mucociliary clearance, lesser volume of the nasal cavity and permeation through the nasal mucosa. To overcome the challenges different strategies for the nasal administration are studied such as polymers, particulate delivery systems, complexation with peptides and smart delivery using glucose-responsive systems. A vast scope of intranasal preparations exists for antidiabetic drugs in the future for the management of diabetes and more clinical studies are the requirement for the societal impact to battle against diabetes.

Microneedle system: a modulated approach for penetration enhancement

The microneedles show advantages over transdermal drug delivery systems on account of better skin permeation bypassing the stratum corneum. To increase the flux of permeation, penetration enhancement techniques like physical and chemical methods are combined with a trans-epidermal delivery system across the skin causing minimal pain. These techniques include iontophoresis, sonophoresis, and electroporation for physical enhancement of drug delivery via topical route by either disrupting the structure of the stratum corneum or by creating pores/micro-channels within the skin. The use of chemical penetrants such as ethanol, lipids, surfactants, and terpenes improves the release kinetics by mechanisms like fluidization of lipids, denaturation of proteins, etc. A combination of microneedles and these techniques show a significant increase in the permeability of drugs across the skin by 5-10 times compared to microneedles alone. This review article focuses on various advanced strategies like the use of drug-polymer complexes, application of ultrasound frequency or tolerable electric current, formation of nano-formulations, etc. with microneedle delivery for transportation of high payload of actives, macromolecules, antibodies, gene, proteins, and peptides. In the near future, microneedle systems will offer potential targeted drug delivery, self-sealable administration across the skin, and minimally invasive vaccine transportation in cancer, diabetes, Alzheimer's, and cardiovascular diseases.HighlightsPhysical penetration enhancement techniques: iontophoresis, electroporation, and sonophoresis.Chemical penetration enhancers: polymers, lipids, surfactants.Strategies to use microneedle system with penetration enhancement techniques.The significant difference in the penetration ability of high payload actives.

CLEAR - Contact lens technologies of the future

Contact lenses in the future will likely have functions other than correction of refractive error. Lenses designed to control the development of myopia are already commercially available. Contact lenses as drug delivery devices and powered through advancements in nanotechnology will open up further opportunities for unique uses of contact lenses. This review examines the use, or potential use, of contact lenses aside from their role to correct refractive error. Contact lenses can be used to detect systemic and ocular surface diseases, treat and manage various ocular conditions and as devices that can correct presbyopia, control the development of myopia or be used for augmented vision. There is also discussion of new developments in contact lens packaging and storage cases. The use of contact lenses as devices to detect systemic disease has mostly focussed on detecting changes to glucose levels in tears for monitoring diabetic control. Glucose can be detected using changes in colour, fluorescence or generation of electric signals by embedded sensors such as boronic acid, concanavalin A or glucose oxidase. Contact lenses that have gained regulatory approval can measure changes in intraocular pressure to monitor glaucoma by measuring small changes in corneal shape. Challenges include integrating sensors into contact lenses and detecting the signals generated. Various techniques are used to optimise uptake and release of the drugs to the ocular surface to treat diseases such as dry eye, glaucoma, infection and allergy. Contact lenses that either mechanically or electronically change their shape are being investigated for the management of presbyopia. Contact lenses that slow the development of myopia are based upon incorporating concentric rings of plus power, peripheral optical zone(s) with add power or non-monotonic variations in power. Various forms of these lenses have shown a reduction in myopia in clinical trials and are available in various markets.

Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges

(1) Background: the use of machine learning techniques for the purpose of anticipating hypoglycemia has increased considerably in the past few years. Hypoglycemia is the drop in blood glucose below critical levels in diabetic patients. This may cause loss of cognitive ability, seizures, and in extreme cases, death. In almost half of all the severe cases, hypoglycemia arrives unannounced and is essentially asymptomatic. The inability of a diabetic patient to anticipate and intervene the occurrence of a hypoglycemic event often results in crisis. Hence, the prediction of hypoglycemia is a vital step in improving the life quality of a diabetic patient. The objective of this paper is to review work performed in the domain of hypoglycemia prediction by using machine learning and also to explore the latest trends and challenges that the researchers face in this area; (2) Methods: literature obtained from PubMed and Google Scholar was reviewed. Manuscripts from the last five years were searched for this purpose. A total of 903 papers were initially selected of which 57 papers were eventually shortlisted for detailed review; (3) Results: a thorough dissection of the shortlisted manuscripts provided an interesting split between the works based on two categories: hypoglycemia prediction and hypoglycemia detection. The entire review was carried out keeping this categorical distinction in perspective while providing a thorough overview of the machine learning approaches used to anticipate hypoglycemia, the type of training data, and the prediction horizon.

siRNA: an alternative treatment for diabetes and associated conditions

Diabetes is a condition that is not completely treatable but life of a diabetic patient can be smoothed by preventing or delaying the associate conditions like diabetic retinopathy, nephropathy, impaired wound healing process, etc. Apart from conventional methods to regulate diabetic condition, new techniques using siRNA have been emerged to prevent the associated conditions. This paper focuses on how siRNA used as a tool to silence the expression of genes which plays critical role in pathogenesis of these conditions. A marked improvement in wound-healing process of diabetic patients has been observed with siRNA treatment by silencing of Keap1 gene. Glucagon plays critical role in glucose homoeostasis and increases blood glucose level during hypoglycaemia. Glucose homoeostasis is impaired in diabetic patient and suppressing the expression of glucagon secretion with siRNA is used to suppress the progress of diabetes. Similarly, silencing expression of several factors has demonstrated improvement of treatment of diabetic nephropathy, retinopathy and inflammation by the use of siRNA.

S-Layer Protein-Based Biosensors

The present paper highlights the application of bacterial surface (S-) layer proteins as versatile components for the fabrication of biosensors. One technologically relevant feature of S-layer proteins is their ability to self-assemble on many surfaces and interfaces to form a crystalline two-dimensional (2D) protein lattice. The S-layer lattice on the surface of a biosensor becomes part of the interface architecture linking the bioreceptor to the transducer interface, which may cause signal amplification. The S-layer lattice as ultrathin, highly porous structure with functional groups in a well-defined special distribution and orientation and an overall anti-fouling characteristics can significantly raise the limit in terms of variety and the ease of bioreceptor immobilization, compactness of bioreceptor molecule arrangement, sensitivity, specificity, and detection limit for many types of biosensors. The present paper discusses and summarizes examples for the successful implementation of S-layer lattices on biosensor surfaces in order to give a comprehensive overview on the application potential of these bioinspired S-layer protein-based biosensors.