Development of an In Vitro Drug Release Method to Enable In Vitro-In Vivo Correlation of Potassium Chloride Extended-Release Tablets.

An in vitro drug release test was developed to establish a level A in vitro-in vivo correlation (IVIVC) for predicting the in vivo performance of potassium chloride extended-release (ER) matrix tablets. Three ER formulations of potassium chloride with different in vitro release rates were designed using the USP dissolution test, and their urinary pharmacokinetic profiles were evaluated in healthy subjects. Due to the lack of IVIVC with the USP method, experiments were designed to investigate the effects of in vitro test conditions on drug release in order to match in vitro drug release with in vivo behaviors of different formulations. The evaluated in vitro variables included the type of USP apparatus, surfactant, and ionic strength of the dissolution medium. Based on the study findings and data analysis, a discriminatory drug release method was successfully developed that enabled the establishment and validation of a level A IVIVC model of the potassium chloride ER tablet using urinary pharmacokinetic data. This method uses USP apparatus I at 50 rpm in 900 mL of 150 mM NaCl solution containing 40 mM sodium dodecyl sulfate at 37 °C. The current study highlights the value of investigating test conditions in developing a predictive in vitro test method for establishing IVIVC.

An ensemble learning framework for potential miRNA-disease association prediction with positive-unlabeled data.

To explore the pathogenic mechanisms of MicroRNA (miRNA) on diverse diseases, many researchers have concentrated on discovering the potential associations between miRNA and disease using machine learning methods. However, the prediction accuracy of supervised machine learning methods is limited by lacking of experimentally-validated uncorrelated miRNA-disease pairs. Without these negative samples, training a highly accurate model is much more difficult. Different from traditional miRNA-disease prediction models using randomly selected unknown samples as negative training samples, we propose an ensemble learning framework to solve this positive-unlabeled (PU) learning problem. The framework incorporates two steps, i.e., a novel semi-supervised Kmeans (SS-Kmeans) to extract reliable negative samples from unknown miRNA-disease pairs and subagging method to generate diverse training sample sets to make full use of those reliable negative samples for ensemble learning. Combined with effective random vector functional link (RVFL) network as prediction model, the proposed framework showed superior prediction accuracy comparing with other popular approaches. A case study on lung and gastric neoplasms further confirms the framework's efficacy at identifying miRNA disease associations.

Melting point prediction of organic molecules by deciphering the chemical structure into a natural language.

Establishing quantitative structure-property relationships for the rational design of small molecule drugs at the early discovery stage is highly desirable. Using natural language processing (NLP), we proposed a machine learning model to process the line notation of small organic molecules, allowing the prediction of their melting points. The model prediction accuracy benefits from training upon different canonicalized SMILES forms of the same molecules and does not decrease with increasing size, complexity, and structural flexibility. When a combination of two different canonicalized SMILES forms is used to train the model, the prediction accuracy improves. Largely distinguished from the previous fragment-based or descriptor-based models, the prediction accuracy of this NLP-based model does not decrease with increasing size, complexity, and structural flexibility of molecules. By representing the chemical structure as a natural language, this NLP-based model offers a potential tool for quantitative structure-property prediction for drug discovery and development.

Modeling Physical Stability of Amorphous Solids Based on Temperature and Moisture Stresses.

Isothermal microcalorimetry was utilized to monitor the crystallization process of amorphous ritonavir (RTV) and its hydroxypropylmethylcellulose acetate succinate-based amorphous solid dispersion under various stressed conditions. An empirical model was developed: ln(τ)=ln(A)+EaRT-b⋅wc, where τ is the crystallization induction period, A is a pre-exponential factor, Ea is the apparent activation energy, b is the moisture sensitivity parameter, and wc is water content. To minimize the propagation of errors associated with the estimates, a nonlinear approach was used to calculate mean estimates and confidence intervals. The physical stability of neat amorphous RTV and RTV in hydroxypropylmethylcellulose acetate succinate solid dispersions was found to be mainly governed by the nucleation kinetic process. The impact of polymers and moisture on the crystallization process can be quantitatively described by Ea and b in this Arrhenius-type model. The good agreement between the measured values under some less stressful test conditions and those predicted, reflected by the slope and R(2) of the correlation plot of these 2 sets of data on a natural logarithm scale, indicates its predictability of long-term physical stability of amorphous RTV in solid dispersions. To further improve the model, more understanding of the impact of temperature and moisture on the amorphous physical stability and fundamentals regarding nucleation and crystallization is needed.

Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD) for brain cancer.

The rapid development of new and emerging science & technologies (NESTs) brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area - nano-enabled drug delivery (NEDD). NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1) international cooperation is increasing, but networking characteristics change over time; (2) highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3) research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

Nano-enabled drug delivery systems for brain cancer and Alzheimer's disease: research patterns and opportunities.

"Tech mining" applies bibliometric and text analytic methods to scientific literature of a target field. In this study, we compare the evolution of nano-enabled drug delivery (NEDD) systems for two different applications - viz., brain cancer (BC) and Alzheimer's disease (AD) - using this approach. In this process, we derive research intelligence from papers indexed in MEDLINE. Review by domain specialists helps understand the macro-level disease problems and pathologies to identify commonalities and differences between BC and AD. Results provide a fresh perspective on the developmental pathways for NEDD approaches that have been used in the treatment of BC and AD. Results also point toward finding future solutions to drug delivery issues that are critical to medical practitioners and pharmaceutical scientists addressing the brain. FROM THE CLINICAL EDITOR: Drug delivery to brain cells has been very challenging due to the presence of the blood-brain barrier (BBB). Suitable and effective nano-enabled drug delivery (NEDD) system is urgently needed. In this study, the authors utilized "tech-mining" tools to describe and compare various choices of delivery system available for the diagnosis, as well as treatment, of brain cancer and Alzheimer's disease.

Impact of Solubilizing Additives on Supersaturation and Membrane Transport of Drugs.

PURPOSE: Many enabling formulations give rise to supersaturated solutions wherein the solute possesses higher thermodynamic activity gradients than the solute in a saturated solution. Since flux across a membrane is driven by solute activity rather than concentration, understanding how solute thermodynamic activity varies with solution composition, particularly in the presence of solubilizing additives, is important in the context of passive absorption. METHODS: In this study, a side-by-side diffusion cell was used to evaluate solute flux for solutions of nifedipine and felodipine in the absence and presence of different solubilizing additives at various solute concentrations. RESULTS: At a given solute concentration above the equilibrium solubility, it was observed that the solubilizing additives could reduce the membrane flux, indicating that the extent of supersaturation can be reduced. However, the flux could be increased back to the same maximum value (which was determined by the concentration where liquid-liquid phase separation (LLPS) occurred) by increasing the total solute concentration. Qualitatively, the shape of the curves of solute flux through membrane as a function of total solute concentration is the same in the absence and presence of solubilizing additives. Quantitatively, however, LLPS occurs at higher solute concentrations in the presence of solubilizing additives. Moreover, the ratios of the LLPS onset concentration and equilibrium solubility vary significantly in the absence and presence of additives. CONCLUSIONS: These findings clearly point out the flaws in using solute concentration in estimating solute activity or supersaturation, and reaffirm the use of flux measurements to understand supersaturated systems. Clear differentiation between solubilization and supersaturation, as well as thorough understanding of their respective impacts on membrane transport kinetics is important for the rational design of enabling formulations for poorly soluble compounds.

Enhancements and limits in drug membrane transport using supersaturated solutions of poorly water soluble drugs.

Amorphous solid dispersions (ASDs) give rise to supersaturated solutions (solution concentration greater than equilibrium crystalline solubility). We have recently found that supersaturating dosage forms can exhibit the phenomenon of liquid-liquid phase separation (LLPS). Thus, the high supersaturation generated by dissolving ASDs can lead to a two-phase system wherein one phase is an initially nanodimensioned and drug-rich phase and the other is a drug-lean continuous aqueous phase. Herein, the membrane transport of supersaturated solutions, at concentrations above and below the LLPS concentration has been evaluated using a side-by-side diffusion cell. Measurements of solution concentration with time in the receiver cell yield the flux, which reflects the solute thermodynamic activity in the donor cell. As the nominal concentration of solute in the donor cell increases, a linear increase in flux was observed up to the concentration where LLPS occurred. Thereafter, the flux remained essentially constant. Both nifedipine and felodipine solutions exhibit such behavior as long as crystallization is absent. This suggests that there is an upper limit in passive membrane transport that is dictated by the LLPS concentration. These results have several important implications for drug delivery, especially for poorly soluble compounds requiring enabling formulation technologies.

A novel accelerated oxidative stability screening method for pharmaceutical solids.

Despite the fact that oxidation is the second most frequent degradation pathway for pharmaceuticals, means of evaluating the oxidative stability of pharmaceutical solids, especially effective stress testing, are still lacking. This paper describes a novel experimental method for peroxide-mediated oxidative stress testing on pharmaceutical solids. The method utilizes urea-hydrogen peroxide, a molecular complex that undergoes solid-state decomposition and releases hydrogen peroxide vapor at elevated temperatures (e.g., 30°C), as a source of peroxide. The experimental setting for this method is simple, convenient, and can be operated routinely in most laboratories. The fundamental parameter of the system, that is, hydrogen peroxide vapor pressure, was determined using a modified spectrophotometric method. The feasibility and utility of the proposed method in solid form selection have been demonstrated using various solid forms of ephedrine. No degradation was detected for ephedrine hydrochloride after exposure to the hydrogen peroxide vapor for 2 weeks, whereas both anhydrate and hemihydrate free base forms degraded rapidly under the test conditions. In addition, both the anhydrate and the hemihydrate free base degraded faster when exposed to hydrogen peroxide vapor at 30°C under dry condition than at 30°C/75% relative humidity (RH). A new degradation product was also observed under the drier condition. The proposed method provides more relevant screening conditions for solid dosage forms, and is useful in selecting optimal solid form(s), determining potential degradation products, and formulation screening during development.

Nanotemplate-engineered nanoparticles containing gadolinium for magnetic resonance imaging of tumors.

PURPOSE: To design nanoparticles containing accessible gadolinium atoms (Gd-NPs) as a contrast agent for magnetic resonance imaging of tumors. METHODS: Nanoparticles containing phospholipid-chelates (phosphoethanolamine diethylenetriaminepentaacetate) and DSPE-PEG (MW5000) were prepared from Brij 78 and stearyl alcohol using the nanotemplate engineering approach. After addition of GdCl3, the presence of gadolinium on the surface of nanoparticles was quantified using inductively coupled plasma atomic emission spectroscopy. The in vitro relaxivities of the Gd-NPs in phosphate buffered saline were assessed at 4.7 T. The conditional binding constants of nanoparticle formulations were determined spectrophotometrically by competitive titration. Transmetallation kinetics of Gd from nanoparticles with Cu2+ and Zn2+ as the competing ions was measured in acetate buffer. The biodistribution profiles, pharmacokinetics, and contrast enhancement in tumor region was studied after administration of Gd-NPs to nude mice bearing A549 lung carcinoma xenografts. RESULTS: Gd-NPs with an average diameter of 138 nm possessing surface chelating functions were prepared from GRAS (generally regarded as safe) materials. The longitudinal relaxivity (r1) and transverse relaxivity (r2) of Gd-NPs in 10% fetal bovine serum at 4.7 T were 7.1 (+/-0.2) and 13.0 (+/-0.7) 1/mM/s, respectively. These pegylated Gd-NPs had enhanced relaxivities and exhibited particle size stability, sufficient binding affinity, and kinetic inertness under physiologic conditions. The contrast enhancement in tumors was demonstrated 40, 120, and 360 minutes after intravenous injection of Gd-NPs at a dose of 0.1 mmol Gd/kg. The Gd plasma concentration of Gd-NPs over a period of 24 hours fit a two-compartmental model with Cl sys = 0.89 mL/h and MRT = 5.93 h. The amount of Gd that accumulated in the tumor region was consistent with the estimated value obtained by T1 measurements using MR imaging. CONCLUSION: Pegylated nanoparticles composed of biocompatible, biodegradable materials and possessing accessible Gd ions on their surface induce relaxivities in the bulk water signal and accumulated sufficiently in tumors, demonstrating their utility as potential magnetic resonance imaging tumor contrast enhancement agents.

Biocompatible nanotemplate-engineered nanoparticles containing gadolinium: stability and relaxivity of a potential MRI contrast agent.

In this article, we use a nanotemplate engineering approach to prepare biodegradable nanoparticles composed of FDA-approved materials and possessing accessible gadolinium (Gd) atoms and demonstrate their potential as a Magnetic Resonance Imaging (MRI) contrast agent. Nanoparticles containing dimyristoyl phosphoethanolamine diethylene triamine penta acetate (PE-DTPA) were prepared using 3.5 mg of Brij 78, 2.0 mg of emulsifying wax and 0.5 mg of PE-DTPA/ml from a microemulsion precursor. After the addition of GdCl3, the presence of Gd on the surface of nanoparticles was characterized using inductively coupled plasma atomic emission spectroscopy and Scanning Transmission Electron Microscopy (STEM). The in vitro relaxivities of the PE-DTPA-Gd nanoparticles in different media were assessed at different field strengths. The conditional stability constant of Gd binding to the nanoparticles was determined using competitive spectrophotometric titration. Transmetallation kinetics of the gadolinium ion from PE-DTPA-Gd nanoparticles with zinc as the competing ionic was measured using the relaxivity evolution method. Nanoparticles with a diameter of approximately 130 nm possessing surface chelating functions were made from GRAS (Generally Regarded As Safe) materials. STEM demonstrated the uniform distribution of Gd3+ on the surface of the nanoparticles. The thermodynamic binding constant for Gd3+ to the nanoparticles was approximately 10(18) M(-1) and transmetallation studies with Zn2+ yielded kinetic constants K1 and K(-1) of 0.033 and 0.022 1/h, respectively, with an equilibrium constant of 1.5. A payload of approximately 10(5) Gd/nanoparticle was achieved; enhanced relaxivities were observed, including a pH dependence of the transverse relaxivity (r2). Nanoparticles composed of materials that have been demonstrated to be hemocompatible and enzymatically metabolized and possessing accessible Gd ions on their surface induce relaxivities in the bulk water signal that make them potentially useful as next-generation MRI tumor contrast enhancement agents.

Identification and characterization of pltZ, a gene involved in the repression of pyoluteorin biosynthesis in Pseudomonas sp. M18.

A new regulator gene named pltZ, which is located downstream of the plt gene cluster in the genome of Pseudomonas sp. M18, was identified, sequenced and characterized in this report. The deduced amino acid sequence of PltZ shares significant homology with other bacterial regulators in the TetR family. The chromosomal pltZ disruption mutant gave rise to 4.4-fold enhancement of pyoluteorin biosynthesis but did not exert significant influence on the accumulation of phenazine-1-carboxylic acid compared with the wild-type M18. The negative regulation of pltZ on pyoluteorin biosynthesis was further confirmed by multiplied pltZ gene dosage experiments and pltA'-'lacZ translational fusion analyses.

[Gene cloning of rpoD and its impact on biosynthesis of antibiotics in Fluorescent pseudomonas M18].

Fluorescent pseudomonas M18, one of plant growth promoting rhizobacteria which can inhibit growth of several phytopathogenes, produces several secondary metabolites including antibiotics phenazine-1-carboxylic acid (PCA) and pyoluteorin (Plt). The rpoD gene encoding the housekeeping sigma factor sigma70 was cloned and sequenced from M18. Through sequencing and homogeneous comparison, the deduced RpoD amino acid sequence between M18 strain and Pseudomonasfluorescens CHAO shows 100% identity. It indicates that rpoD gene is very conserved in different members of fluorescent pseudomonads. The rpoD gene was placed downstream of the constitutive Ptac promoter in the shuttle vector pME6032 between E. coli and Pseudomonas fluorescens and the recombinant plasmid was introduced into M18. It was found that the time of both PCA and Plt began to accumulate was 4 and 8 hours earlier and the yield of these antibiotics was increased one and six times more respectively in M18 in comparison with the control.