The results from past studies about the effects of second-generation e-prescribing systems on community pharmacists' outcomes and practices are inconclusive, and the claims of effectiveness and efficiency of such systems have not been supported in all studies. There is a strong need to study the factors that lead to positive outcomes for the users of these systems.
Some hospitals have implemented computerized physician order entry (CPOE) systems to reduce the medical error rates. However, research in this area has been very limited, especially regarding the impact of CPOE use on the reduction of prescribing errors. Moreover, the past studies have dealt with the overall impact of CPOE on the reduction of broadly termed "medical errors", and they have not specified which medical errors have been reduced by CPOE. Furthermore, the majority of the past research in this field has been either qualitative or has not used robust empirical techniques. This research examined the impacts of usability of CPOE systems on the reduction of doctors' prescribing errors.
Norfloxacin (NOR), widely employed as an anti-bacterial drug, has poor oral bioavailability. Nano based drug delivery systems are widely used to overcome the existing oral bioavailability challenges. Lipid-Polymer Hybrid Nanoparticles (LPHNs) exhibit the distinctive advantages of both polymeric and liposomes nanoparticles, while excluding some of their disadvantages. In the current study, NOR loaded LPHNs were prepared, and were solid amorphous in nature, followed by in vitro and in vivo evaluation. The optimized process conditions resulted in LPHNs with the acceptable particle size 121.27 nm, Polydispersity Index (PDI) of 0.214 and zeta potential of -32 mv. The addition of a helper lipid, oleic acid, and polymers, ethyl cellulose, substantially increased the encapsulation efficiency (EE%) (65% to 97%). In vitro study showed a sustained drug release profile (75% within 12 h) for NOR LPHNs. The optimized NOR LPHNs showed a significant increase (p < 0.05) in bioavailability compared to the commercial product. From the acute toxicity study, the LD50 value was found to be greater than 1600 mg/kg. The molecular modelling studies substantiated the experimental results with the best combination of polymers and surfactants that produced highly stable LPHNs. Therefore, LPHNs proved to be a promising system for the delivery of NOR, as well as for other antibiotics and hydrophobic drugs.
The tumor-specific targeting of chemotherapeutic agents for specific necrosis of cancer cells without affecting the normal cells poses a great challenge for researchers and scientists. Though extensive research has been carried out to investigate chemotherapy-based targeted drug delivery, the identification of the most promising strategy capable of bypassing non-specific cytotoxicity is still a major concern. Recent advancements in the arena of onco-targeted therapies have enabled safe and effective tumor-specific localization through stimuli-responsive drug delivery systems. Owing to their promising characteristic features, stimuli-responsive drug delivery platforms have revolutionized the chemotherapy-based treatments with added benefits of enhanced bioavailability and selective cytotoxicity of cancer cells compared to the conventional modalities. The insensitivity of stimuli-responsive drug delivery platforms when exposed to normal cells prevents the release of cytotoxic drugs into the normal cells and therefore alleviates the off-target events associated with chemotherapy. Contrastingly, they showed amplified sensitivity and triggered release of chemotherapeutic payload when internalized into the tumor microenvironment causing maximum cytotoxic responses and the induction of cancer cell necrosis. This review focuses on the physical stimuli-responsive drug delivery systems and chemical stimuli-responsive drug delivery systems for triggered cancer chemotherapy through active and/or passive targeting. Moreover, the review also provided a brief insight into the molecular dynamic simulations associated with stimuli-based tumor targeting.