In order to enhance the delivery of drugs with limited absorption due to poor solubility/dissolution, approaches are being developed to improve the dissolution rates and solubility of drug molecules. These approaches include identification of water-soluble salts of parent drugs, preparation of stable amorphous drug formulations, inclusion of solubility-enhancing agents in the dosage form, and particle size reduction. Technologies to reduce drug particle size to sub-micrometer range are being applied to product development more frequently. Electrospinning is being considered as one of the technologies which can produce nanosized drugs incorporated in polymeric nanofibers. In vitro and in vivo studies have demonstrated that the release rates of drugs from these nanofiber formulations are enhanced compared to those from original drug substance. This technology has the potential to be used for enhancing the oral delivery of poorly soluble drugs.
Abstract. The workshop "Bioequivalence, Biopharmaceutics Classification System, and Beyond" was held May 21-23, 2007 in North Bethesda, MD, USA. This workshop provided an opportunity for pharmaceutical scientists to discuss the FDA guidance on the Biopharmaceutics Classification System (BCS), bioequivalence of oral products, and related FDA initiatives such as the FDA Critical Path Initiative. The objective of this Summary Workshop Report is to document the main points from this workshop. Key highlights of the workshop were (a) the described granting of over a dozen BCS-based biowaivers by the FDA for Class I drugs whose formulations exhibit rapid dissolution, (b) continued scientific support for biowaivers for Class III compounds whose formulations exhibit very rapid dissolution, (c) scientific support for a number of permeability methodologies to assess BCS permeability class, (d) utilization of BCS in pharmaceutical research and development, and (e) scientific progress in in vitro dissolution methods to predict dosage form performance.
Neoplastic growth and cellular differentiation are critical hallmarks of tumor development. It is well established that cell-to-cell communication between tumor cells and “normal” surrounding cells regulates tumor differentiation and proliferation, aggressiveness, and resistance to treatment. Nevertheless, the mechanisms that result in tumor growth and spread as well as the adaptation of healthy surrounding cells to the tumor environment are poorly understood. A major component of these communication systems is composed of connexin (Cx)-containing channels including gap junctions (GJs), tunneling nanotubes (TNTs), and hemichannels (HCs). There are hundreds of reports about the role of Cx-containing channels in the pathogenesis of cancer, and most of them demonstrate a downregulation of these proteins. Nonetheless, new data demonstrate that a localized communication via Cx-containing GJs, HCs, and TNTs plays a key role in tumor growth, differentiation, and resistance to therapies. Moreover, the type and downstream effects of signals communicated between the different populations of tumor cells are still unknown. However, new approaches such as artificial intelligence (AI) and machine learning (ML) could provide new insights into these signals communicated between connected cells. We propose that the identification and characterization of these new communication systems and their associated signaling could provide new targets to prevent or reduce the devastating consequences of cancer.
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