Comparison of in vivo behaviors of intramuscularly long-acting celecoxib nanosuspensions with different particle sizes for the postoperative pain treatment.

Celecoxib (CXB) has a good analgesic effect on postoperative acute pain, but clinically its compliance is compromised because of frequent administration. Therefore, the development of injectable celecoxib nanosuspensions (CXB-NS) for long-acting analgesic effects is highly desirable. However, how the particle size affects the in vivo behaviors of CXB-NS remains unclear. Herein, CXB-NS with different sizes were prepared by the wet-milling method. Following intramuscular (i.m.) injection in rats (50 mg/kg), all CXB-NS achieved sustained systemic exposure and long-acting analgesic effects. More importantly, CXB-NS showed size-dependent pharmacokinetic profiles and analgesic effects, and the smallest CXB-NS (about 0.5 µm) had the highest Cmax, T1/2, and AUC0-240h and the strongest analgesic effects on incision pain. Therefore, small sizes are preferred for long action by i.m. injection, and the CXB-NS developed in this study were alternative formulations for the treatment of postoperative acute pain.

Programmed pH-responsive core-shell nanoparticles for precisely targeted therapy of ulcerative colitis.

pH-Responsive nanotherapeutics were recently developed for the treatment of ulcerative colitis (UC). However, they target the entire colon rather than the UC site, which leads to insufficient accumulation in inflamed colon lesions and causes side effects. Core-shell nanoparticles exhibit unique advantages in improving the precision of targeted delivery. In this study, Eudragit® EPO and L100, two pH-sensitive materials, were coated on nano-sized curcumin to fabricate core-shell nanoparticles. The developed CNs@EPO@L100 exhibited programmed pH-responsive drug release behavior, improved in vitro anti-inflammatory ability, and enhanced accumulation at the site of inflammation in the colon. Furthermore, after oral administration, CNs@EPO@L100 significantly ameliorated the inflammatory symptoms in mice. Taken together, this study provides insights into programmed release through the rational application of pH-sensitive materials and offers strategies for a precisely targeted therapy of UC using core-shell nanoparticles.

Liquid-liquid phase separation drug aggregate: Merit for oral delivery of amorphous solid dispersions.

As a promising strategy, amorphous solid dispersion has been extensively employed in improving the oral bioavailability of insoluble drugs. Despite the numerous advantages, the problems associated with supersaturation stability limit its further application. Recently, the formation and stability of the liquid-liquid phase separation drug aggregate (LLPS-DA) have been found to be vital for supersaturation maintenance. An in-depth review of LLPS-DA was required to further explore the supersaturation maintenance mechanism in vivo. Hence, this study aimed to present a short review to introduce the LLPS-DA, highlight the in vivo advantages for oral administration, and discuss the prospects to help understand the in vivo behavior of LLPS-DA.

Hydrophobic ion pairing-based self-emulsifying drug delivery systems: a new strategy for improving the therapeutic efficacy of water-soluble drugs.

INTRODUCTION: Self-emulsifying drug delivery systems (SEDDS) are formulations consisting of oil phase, emulsifiers, and co-emulsifiers, which can be spontaneously emulsified in the body to form O/W microemulsion. Traditionally, SEDDS are used commercially for the improvement of oral absorption and in vivo performances for poorly water-soluble drugs. However, SEDDS formulations were rarely reported for the delivery of water-soluble drugs. Recent studies have found that SEDDS have the potential for water-soluble macromolecular drugs by the application of the hydrophobic ion pairing (HIP) technology. AREAS COVERED: This review summarized the characteristics of HIP complexes in SEDDS and introduced their advantages and discussed the future prospects of HIP-based SEDDS in drug delivery. EXPERT OPINION: Hydrophobic ion pairing (HIP) is a technology that combines lipophilic structures on polar counterions to increase the lipophilicity through electrostatic interaction. Recent studies showed that HIP-based SEDDS offer an effective way to increase the mucosal permeability and improve the chemical stability for antibiotics, proteases, DNA-based drugs, and other water-soluble macromolecular drugs. It is believed that HIP-based SEDDS offer a potential and attractive method capable of delivering hydrophilic macromolecules with ionizable groups for oral administration.

Roles of effective stabilizers in improving oral bioavailability of naringenin nanocrystals: Maintenance of supersaturation generated upon dissolution by inhibition of drug dimerization.

Nanocrystals (NCs), a colloidal dispersion system formulated with stabilizers, have attracted widespread interest due to their ability to effectively improve the oral bioavailability of poorly water-soluble drugs. The stabilizer plays a key role because it can affect the physical stability and even the oral bioavailability of NCs. However, how stabilizers affect the bioavailability of NCs remains unknown. In this study, F68, F127, HPMC, and PVP were each used as a stabilizer to formulate naringenin NCs. The NCs formulated with PVP exhibited excellent release behaviors, cellular uptake, permeability, oral bioavailability, and anti-inflammatory effects. The underlying mechanism is that PVP effectively inhibits the formation of naringenin dimer, which in turn improves the physical stability of the supersaturated solution generated when NC is dissolved. This finding provides insights into the effects of stabilizers on the in vivo performances of NCs and supplies valuable knowledge for the development of poorly water-soluble drugs.

Stabilizer-induced different in vivo behaviors for intramuscularly long-acting celecoxib nanocrystals.

Nanocrystals (NCs) have been widely recognized as an available policy for the formulation of long-acting injections for insoluble drugs. Stabilizers are extremely important for the physical stability of NCs because they can reduce the surface free energy of the system. However, whether stabilizers can affect the in vivo performances of long-acting injectable NCs is unclear. In this study, three celecoxib (CXB) NCs formulated with different stabilizers (PVP K17, TPGS, and F68) were successfully developed by the wet milling method. Among the formulations, CXB-NCs/PVP K17 had a lower dissolution rate. More importantly, CXB-NCs/PVP K17 did not show burst release after intramuscular (i.m.) injection to rats, and it had a strong analgesic effect. These results showed that the stabilizers played a key role in the in vivo behaviors of long-acting injectable NCs. This strongly suggested that the burst release could be avoided by alteration of stabilizers of NCs by i.m. injection.

Preclinical studies of a high drug-loaded meloxicam nanocrystals injection for analgesia.

Meloxicam (MLX) is considered to have significant analgesic properties. However, the analgesic effects of MLX are compromised by its poor water solubility and thus the low drug loading. The purpose of this study was to develop a high drug-loaded MLX injection by formulating it into nanocrystals (NCs) for the treatment of analgesia. The developed MLXNCs exhibited satisfactory particle sizes and remarkably in vitro dissolution behaviors. In addition, the plasma concentrations of MLXNCs were comparable with the MLX solution (formulated with 1.0% polyoxyethylene castor oil 35) in rats. The acetic acid-induced writhing tests, hot plate tests and hind paw incision experiments demonstrated that the MLXNCs had significant analgesic effects. The findings provide insights into the developed high drug-loaded MLXNCs and provide new therapeutic options for acute and chronic pain management.

Assessment of the invisible blood contamination on nurses' gloved hands during vascular access procedures in a hemodialysis unit.

A prospective study was conducted to assess potential invisible blood contamination on nurses' gloved hands during vascular access procedures using the occult blood detection method in a hemodialysis unit. 60.13% (273/454) of samples tested positive for hemoglobin. These results highlighted the importance of hand hygiene and glove change during hemodialysis access care.

Assessing Workplace Stress Among Nurses Using Heart Rate Variability Analysis With Wearable ECG Device-A Pilot Study.

This study aims to measure workplace stress of nurses using heart rate variability (HRV) analysis based on data derived from wearable ECG heart rate monitors. The study population consists of 17 nurses at a major public hospital in China. Data was collected from 7 DON nurses (department of neurosurgery; all females; mean age: 31.43 ± 4.50), and 9 ICU nurses (intensive care unit; 8 females and 1 male; mean age: 31.33 ± 5.43). Each participant was asked to wear a wireless ECG heart rate monitor to measure stress level during work, and to complete the Chinese Nurses Stress Response Scale (CNSRS) after work as subjective response criteria. Demographic information, body posture, heart rate, R-R intervals (RRI), low frequency components (LF) and high frequency components (HF) were collected. LF%, LnHF and the squared root of the mean squared differences of successive NN intervals (RMSSD) based on HRV analysis were used to estimate the stress level of nurses. DON nurses reported a higher LF%, lower LnHF and lower RMSSD than ICU nurses. Work shifts were shown to have significant effects on LF%, LnHF and RMSSD respectively, with nurses in long shifts and night shifts reported high stress levels. Higher LF%, lower LnHF and lower RMSSD were found during work shift. Posture analysis revealed negative correlations with LnHF and RMSSD in walking and standing/sitting positions, and a significant negative correlation with LF% in lying-down position. Nurses with higher LF% reported higher CNSRS scores in all subscales, whereas nurses with lower LnHF or RMSSD reported higher CNSRS scores in social phobia and fatigue subscales. The results of this study support the idea that HRV can be used to investigate workplace stress among nurses under real work condition, and can serve as a preventive measure for identifying stress-related illnesses among nurses.

Nimodipine nanocrystals for oral bioavailability improvement: preparation, characterization and pharmacokinetic studies.

This study intended to develop nimodipine (NMD) nanocrystals with different sizes for oral administration and to investigate the relationship between dissolution and pharmacokinetics for NMD nanocrystals and Nimotop(®). NMD nanocrystals were prepared by combination of microprecipitation and high pressure homogenization and were further lyophilized. The particle size, morphology and aqueous solubility of the NMD nanocrystals were determined. With Nimotop(®) as the control, the dissolution rate was evaluated and the pharmacokinetic study was undertaken in beagle dogs. NMD nanocrystals with mean diameters of about 159.0, 503.0 and 833.3 nm were prepared, respectively. The lyophilization didn't affect the particle sizes of the redispersed nanocrystals. The aqueous solubility was significantly improved and displayed a size-dependent manner. The nanocrystals exhibited lower dissolution patterns than Nimotop(®) under non-sink condition, but bioavailability of the two nanocrystals (159.0 and 833.3 nm) was equivalent, about 2.6-fold higher than Nimotop(®). In conclusion, oral nanocrystal drug delivery system was a promising strategy in improving the oral bioavailability of poorly soluble or insoluble drugs. But we could not establish a favorable in vitro in vivo correlation for NMD nanocrystals and Nimotop(®) and thus the oral absorption mechanism of the NMD nanocrystals required further study.

Nimodipine nanocrystals for oral bioavailability improvement: role of mesenteric lymph transport in the oral absorption.

PURPOSE: We had conducted a comprehensive study on preparation, characterization and pharmacokinetics of nimodipine nanocrystals for oral administration previously, and nimodipine nanocrystals displayed lower dissolution profiles but higher bioavailability than Nimotop(®). In this study, we aimed at elucidating the reasons of unfavorable in vitro in vivo correlation for NMD nanocrystals and Nimotop(®) with a hypothesis that special oral absorption mechanism was involved in the absorption of nimodipine nanocrystals. METHODS: Investigations of oral absorption mechanism of the nanocrystals were performed on everted gut sac models, lymphatically (mesenteric lymph duct) cannulated SD rats, Caco-2 cell monolayers and chylomicron flow blocking rats, respectively. RESULTS: The permeability of nanocrystals in duodenum, ileum and colon was not superior to that of Nimotop(®), suggestive of special absorption mechanisms involved. Exudates of nanocrystals from enterocytes were detected in mesenteric lymphatic fluids using a transmission electron microscope, and the bioavailability was only about half of the control after the mesenteric lymph was blocked. The nanocrystals were taken up by enterocytes via macropinocytosis and caveolin-mediated endocytosis pathways. CONCLUSIONS: It was impossible to establish a favorable in vitro in vivo correlation for NMD nanocrystals and Nimotop(®), because portions of the nanocrystals underwent macropinocytosis and caveolin-mediated endocytosis by enterocytes as intact nanocrystal forms, then bypassed the liver first-pass metabolism.

Relationship between dissolution and bioavailability for nimodipine colloidal dispersions: the critical size in improving bioavailability.

To compare the dissolution and bioavailability for nimodipine microcrystals and nanocrystals, and to determine the critical size range in improving the oral absorption of nimodipine. Nimodipine microcrystals and nanocrystals were prepared using a microprecipitation method. The particle size was determined with a laser diffraction method. X-ray powder diffraction was applied to inspect the potential crystal form transition. The aqueous solubility was determined by shaking flasks, and the dissolution behavior was evaluated using the paddle method. The pharmacokinetics was performed in beagle dogs in a crossover experimental design. Three nimodipine colloidal dispersions (16296.7, 4060.0 and 833.3 nm) were prepared, respectively. Nimodipine had undergone crystal form transition during microprecipitation process, but experienced no conversion under the high-pressure homogenization. The colloidal dispersions did not show any difference in aqueous equilibrium solubility. Additionally, the three formulations also displayed similar dissolution curves in purified water and 0.05% SDS. The AUC for dispersions of 4060.0 and 833.3 nm sizes was 1.69 and 2.59-fold higher than that for 16296.7 nm system in dogs. To sum up, the critical particle size was found to be within the range of 833.3-4060.0 nm (average volume-weighted particle size) in improving the bioavailability of nimodipine, and dissolution performance was not an effective index in evaluating the bioavailability for nimodipine colloidal dispersions.

Predicting human plasma protein binding of drugs using plasma protein interaction QSAR analysis (PPI-QSAR).

A novel method, named as the plasma protein-interaction QSAR analysis (PPI-QSAR) was used to construct the QSAR models for human plasma protein binding. The intra-molecular descriptors of drugs and inter-molecular interaction descriptors resulted from the docking simulation between drug molecules and human serum albumin were included as independent variables in this method. A structure-based in silico model for a data set of 65 antibiotic drugs was constructed by the multiple linear regression method and validated by the residual analysis, the normal Probability-Probability plot and Williams plot. The R(2) and Q(2) values of the entire data set were 0.87 and 0.77, respectively, for the training set were 0.86 and 0.72, respectively. The results indicated that the fitted model is robust, stable and satisfies all the prerequisites of the regression models. Combining intra-molecular descriptors with inter-molecular interaction descriptors between drug molecules and human serum albumin, the drug plasma protein binding could be modeled and predicted by the PPI-QSAR method successfully.

Structure-based in silico model profiles the binding constant of poorly soluble drugs with ß-cyclodextrin.

Cyclodextrin inclusion complexation technique is the key method to enhance the solubility and absorption of poorly soluble drugs in the early development stage, and thus it is essential to predict the binding constant between drug molecules and cyclodextrin. Structure-based in silico model was constructed for a data set of 86 poorly soluble drugs and used to profile the binding constant of drug-ß-cyclodextrin inclusion complex. The stepwise regression was employed to select the optimum subset of the independent variables. The in silico model was built by the multiple linear regression method and validated by the residual analysis, the normal Probability-Probability plot and Williams plot. For the entire data set, the R(2) and Q(2) of the model were 0.78 and 0.67, respectively. The results indicated that the fitted model is robust, stable and satisfies all the prerequisites of the regression models. The chemical space position and important contributors were compared between selected drug molecules and organic compounds available in the literature. It was suggested that the binding behavior of drug molecules with ß-CD should differ from that of the common organic compounds. Focusing on structurally diverse drugs, the in silico model can be used as an efficient tool to rapidly screen the drug-ß-cyclodextrin inclusion complex stability and to rationally design the new drug delivery system of poorly soluble drugs.

Contribution of molecular properties to extrapolation of the volume of distribution in human from preclinical animal species data.

This paper quantitatively investigated the contribution of molecular properties to the volume of distribution in human (V(d human) ) when extrapolated from preclinical animal data, and identified which molecular descriptors and animal species were essential or better for acquiring the optimal accuracy of extrapolation. First, several two-dimensional molecular descriptors which can potentially contribute to V(d) were selected to establish the model to predict V(d) in humans. Then, several linear predictive models were constructed by partial least squares (PLS) using three or one animal data in combination with or without the molecular descriptors. Stepwise regression was performed to determine the important molecular descriptors. For comparison, the allometric method was also performed to estimate the V(d human) from preclinical species (rat, dog and monkey) data. The predictive accuracy of PLS models was better than that obtained by the allometric method. Moreover, the predictive accuracy of these models was improved when the molecular descriptors were introduced. Interestingly, the common contributors selected were molecular weight (MW) and the negatively charged fraction value (f(i-) ) for any stepwise regression model concerning molecular descriptors. Additionally, the dog was a more suitable species for predicting V(d human) during drug-lead pharmacokinetic optimization. More importantly, the introduction of molecular properties could improve the predictive accuracy for the prediction of V(d human) from the preclinical species, among which MW and f(i-) were the significant parameters and the latter was considered in the extrapolation process for the first time.

Prediction of volume of distribution values in human using immobilized artificial membrane partitioning coefficients, the fraction of compound ionized and plasma protein binding data.

We developed an improved Lombardeo's method (J. Med. Chem., 2004) for prediction of VD(ss) in human. With ElogD substituted by logk(IAM), together with f(i (7.4)) (the fraction of compound ionized at pH 7.4) and logf(u) (logarithmic fraction of compound unbound in plasma), the predictive equation of f(ut) (the fraction of the compound unbound in tissues) for the 121 compounds was built, predictive VD(ss) was further obtained from the Øie-Tozer equation. Our model could be applicable to structurally diverse compounds, including acids, bases, neutrals, and ampholytes. Interior and exterior validation results indicated the model had a robust predictive ability. Compared to the Lombardeo's and Hollósy's (J. Med. Chem., 2006) methods, our model can be generally applicable with better predictive accuracy.

Nanoparticle albumin-bound (NAB) technology is a promising method for anti-cancer drug delivery.

Albumin is a versatile drug carrier in anti-cancer drug delivery system and it also has an actively targeting capacity to tumors. Recently, nanoparticle albumin-bound (nab) paclitaxel (nab-paclitaxel; Abraxane) has been approved in 2006 for use in patients with metastatic breast cancer who have failed in the combination chemotherapy, and so the nab-technology has attracted much interest in the anti-cancer drug delivery system. The details about the preparation, characterization and evaluation of nab-paclitaxel (ABI-007) are discussed. The pharmacokinetics, pharmacodynamics and the clinical trials of ABI-007 are also reviewed. Furthermore, the recent applications of nab-technology in the anti-cancer drug delivery systems are summarized by virtue of the patents pertaining to nab-technology. To sum up, nab-technology has a great potential of being applied extensively in the field of anti-cancer agents delivery in the future in order to acquire the good safety and better therapeutical effect.

Structure-based prediction of the nonspecific binding of drugs to hepatic microsomes.

For the accurate prediction of in vivo hepatic clearance or drug-drug interaction potential through in vitro microsomal metabolic data, it is essential to evaluate the fraction unbound in hepatic microsomal incubation media. Here, a structure-based in silico predictive model of the nonspecific binding (fu(mic), fraction unbound in hepatic microsomes) for 86 drugs was successfully developed based on seven selected molecular descriptors. The R(2) of the predicted and observed log((1 - fu(mic))/fu(mic)) for the training set (n = 64) and test set (n = 22) were 0.82 and 0.85, respectively. The average fold error (AFE, calculated by fu(mic) rather than log((1 - fu(mic))/fu(mic))) of the in silico model was 1.33 (n = 86). The predictive capability of fu(mic) for neutral drugs compared well to that for basic compounds (R(2) = 0.82, AFE = 1.18 and fold error values were all below 2, except for felodipine and progesterone) in our model. This model appears to perform better for neutral compounds when compared to models previously published in the literature. Therefore, this in silico model may be used as an additional tool to estimate fu(mic) and for predicting in vivo hepatic clearance and inhibition potential from in vitro hepatic microsomal studies.

First-principle, structure-based prediction of hepatic metabolic clearance values in human.

The first-principle, quantitative structure-hepatic clearance relationship for 50 drugs was constructed based on selected molecular descriptors calculated by TSAR software. The R(2) of the predicted and observed hepatic clearance for the training set (n=36) and test set (n=13) were 0.85 and 0.73, respectively. The average fold error (AFE) of the in silico model was 1.28 (n=50). The prediction accuracy of in silico model was superior to in vitro hepatocytes' model in literature (n=50, AFE=2.55). It is attractive to predict human hepatic clearance based on molecular descriptors merely. The structure-based model can be used as an efficient tool in the rapid identification of hepatic clearance of new drug candidates in drug discovery.

Predicting the volume of distribution of drugs in humans.

Recent studies have shown that many promising new drug candidates were abandoned due to poor pharmacokinetic properties (PKs). Therefore, it is important to predict the PKs of compounds during the early stages of drug development. The volume of distribution (VD) is one of the most important PK parameters. When considered along with systemic clearance, the VD determines the biological half-life, which is used for designing suitable dosage regimens and rational formulations. At present, the methods used to predict VD include (i) the extrapolation of animal data, (ii) physiologically based pharmacokinetic (PBPK) modeling and (iii) in silico approaches that employ quantitative structure-pharmacokinetic relationships (QSPR). In this article, the latest progress in the field of VD prediction is summarized in terms of the above three areas, respectively, and these approaches are expected to be valuable for screening new drugs during the early stages of drug discovery and development.