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The successful delivery of drugs across the oral mucosa represents a continuing challenge, as well as a great opportunity. Oral transmucosal delivery, especially buccal and sublingual delivery, has progressed far beyond the use of traditional dosage forms with novel approaches emerging continuously. This review highlights the physiological challenges as well as the advances and opportunities for buccal/sublingual drug delivery. Particular attention is given to new approaches which can extend dosage form retention time or can be engineered to deliver complex molecules such as proteins and peptides. The review will also discuss the physiology and local environment of the oral cavity in vivo and how this relates to the performance of transmucosal delivery systems.

Gas chromatography was used to study the cannabinoid content ("potency") of illicit cannabis seized by police in England in 2004/5. Of the four hundred and fifty two samples, indoor-grown unpollinated female cannabis ("sinsemilla") was the most frequent form, followed by resin (hashish) and imported outdoor-grown herbal cannabis (marijuana). The content of the psychoactive cannabinoid delta 9-tetrahydrocannabinol (THC) varied widely. The median THC content of herbal cannabis and resin was 2.1% and 3.5%, respectively. The median 13.9% THC content of sinsemilla was significantly higher than that recorded in the UK in 1996/8. In sinsemilla and imported herbal cannabis, the content of the antipsychotic cannabinoid cannabidiol (CBD) was extremely low. In resin, however, the average CBD content exceeded that of THC, and the relative proportions of the two cannabinoids varied widely between samples. The increases in average THC content and relative popularity of sinsemilla cannabis, combined with the absence of the anti-psychotic cannabinoid CBD, suggest that the current trends in cannabis use pose an increasing risk to those users susceptible to the harmful psychological effects associated with high doses of THC.

Hyaluronic acid (HA) is a naturally occurring polyanionic, polysaccharide that consists of N-acetyl-D-glucosamine and beta-glucoronic acid. It is present in the intercellular matrix of most vertebrate connective tissues especially skin where it has a protective, structure stabilizing and shock-absorbing role. The unique viscoelastic nature of HA along with its biocompatibility and non-immunogenicity has led to its use in a number of clinical applications, which include: the supplementation of joint fluid in arthritis; as a surgical aid in eye surgery; and to facilitate the healing and regeneration of surgical wounds. More recently, HA has been investigated as a drug delivery agent for various routes of administration, including ophthalmic, nasal, pulmonary, parenteral and topical. In fact, regulatory approval in the USA, Canada and Europe was granted recently for 3% diclofenac in 2.5% HA gel, Solaraze, for the topical treatment of actinic keratoses, which is the third most common skin complaint in the USA. The gel is well tolerated, safe and efficacious and provides an attractive, cost-effective alternative to cryoablation, curettage or dermabrasion, or treatment with 5-fluorouracil. The purpose of this review is to describe briefly the physical, chemical and biological properties of HA together with some details of its medical and pharmaceutical uses with emphasis on this more recent topical application.

Hyaluronic acid (HA), is a polyanionic polysaccharide that consists of N-acetyl-D-glucosamine and beta-glucoronic acid. It is most frequently referred to as hyaluronan because it exists in vivo as a polyanion and not in the protonated acid form. HA is distributed widely in vertebrates and presents as a component of the cell coat of many strains of bacteria. Initially the main functions of HA were believed to be mechanical as it has a protective, structure stabilizing and shock-absorbing role in the body. However, more recently the role of HA in the mediation of physiological functions via interaction with binding proteins and cell surface receptors including morphogenesis, regeneration, wound healing, and tumor invasion, as well as in the dynamic regulation of such interactions on cell signaling and behavior has been documented. The unique viscoelastic nature of hyaluronan along with its biocompatibility and nonimmunogenicity has led to its use in a number of cosmetic, medical, and pharmaceutical applications. More recently, HA has been investigated as a drug delivery agent for ophthalmic, nasal, pulmonary, parenteral, and dermal routes. The purpose of our review is to describe the physical, chemical, and biological properties of native HA together with how it can be produced and assayed along with a detailed analysis of its medical and pharmaceutical applications.

The General Solubility Equation (GSE) is a QSPR model based on the melting point and log P of a chemical substance. It is used to predict the aqueous solubility of nonionizable chemical compounds. However, its reliance on experimentally derived descriptors, particularly melting point, limits its applicability to virtual compounds. The studies presented show that the GSE is able to predict, to within 1 log unit, the experimental aqueous solubility (log S) for 81% of the compounds in a data set of 1265 diverse chemical structures (-8.48 < log S < 1.58). However, the predictive ability of the GSE is reduced to 75% when applied to a subset of the data (1160 compounds -6.00 < log S < 0.00), which discounts those compounds occupying the sparsely populated regions of data space. This highlights how sparsely populated extremities of data sets can significantly skew results for linear regression-based models. Replacing the melting point descriptor of the GSE with a descriptor which accounts for topographical polar surface area (TPSA) produces a model of comparable quality to the GSE (the solubility of 81% of compounds in the full data set predicted accurately). As such, we propose an alternative simple model for predicting aqueous solubility which replaces the melting point descriptor of the GSE with TPSA and hence can be applied to virtual compounds. In addition, incorporating TPSA into the GSE in addition to log P and melting point gives a three descriptor model that improves accurate prediction of aqueous solubility over the GSE by 5.1% for the full and 6.6% for the reduced data set, respectively.

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