Antimicrobial efficacy of tobramycin polymeric nanoparticles for Pseudomonas aeruginosa infections in cystic fibrosis: formulation, characterisation and functionalisation with dornase alfa (DNase).

Inhaled antibiotics, such as tobramycin, for the treatment of Pseudomonas aeruginosa pulmonary infections are associated with the increase in life expectancy seen in cystic fibrosis (CF) patients over recent years. However, the effectiveness of this aminoglycoside is still limited by its inability to penetrate the thick DNA-rich mucus in the lungs of these patients, leading to low antibiotic exposure to resident bacteria. In this study, we created novel polymeric nanoparticle (NP) delivery vehicles for tobramycin. Using isothermal titration calorimetry, we showed that tobramycin binds with alginate polymer and, by exploiting this interaction, optimised the production of tobramycin alginate/chitosan NPs. It was established that NP antimicrobial activity against P. aeruginosa PA01 was equivalent to unencapsulated tobramycin (minimum inhibitory concentration 0.625 mg/L). Galleria mellonella was employed as an in vivo model for P. aeruginosa infection. Survival rates of 90% were observed following injection of NPs, inferring low NP toxicity. After infection with P. aeruginosa, we showed that a lethal inoculum was effectively cleared by tobramycin NPs in a dose dependent manner. Crucially, a treatment with NPs prior to infection provided a longer window of antibiotic protection, doubling survival rates from 40% with free tobramycin to 80% with NP treatment. Tobramycin NPs were then functionalised with dornase alfa (recombinant human deoxyribonuclease I, DNase), demonstrating DNA degradation and improved NP penetration of CF sputum. Following incubation with CF sputum, tobramycin NPs both with and without DNase functionalisation, exhibited anti-pseudomonal effects. Overall, this work demonstrates the production of effective antimicrobial NPs, which may have clinical utility as mucus-penetrating tobramycin delivery vehicles, combining two widely used CF therapeutics into a single NP formulation. This nano-antibiotic represents a strategy to overcome the mucus barrier, increase local drug concentrations, avoid systemic adverse effects and improve outcomes for pulmonary infections in CF.

Solubility parameter based screening methods for early stage formulation development of itraconazole amorphous solid dispersions

Objectives: This article uses conventional and newly extended solubility parameter (δ) methods to identify polymeric materials capable of forming amorphous dispersions with itraconazole (itz). Methods: Combinations of itz and Soluplus, Eudragit E PO (EPO), Kollidon 17PF (17PF) or Kollidon VA64 (VA64) were prepared as amorphous solid dispersions using quench cooling and hot melt extrusion. Storage stability was evaluated under a range of conditions using differential scanning calorimetry and powder X-ray diffraction. Key findings: The rank order of itz miscibility with polymers using both conventional and novel δ-based approaches was 17PF > VA64 > Soluplus > EPO, and the application of the Flory–Huggins lattice model to itz–excipient binary systems corroborated the findings. The solid-state characterisation analyses of the formulations manufactured by melt extrusion correlated well with pre-formulation screening. Long-term storage studies showed that the physical stability of 17PF/vitamin E TPGS–itz was poor compared with Soluplus and VA64 formulations, and for EPO/itz systems variation in stability may be observed depending on the preparation method. Conclusion: Results have demonstrated that although δ-based screening may be useful in predicting the initial state of amorphous solid dispersions, assessment of the physical behaviour of the formulations at relevant temperatures may be more appropriate for the successful development of commercially acceptable amorphous drug products.

Using Flory-Huggins phase diagrams as a pre-formulation tool for the production of amorphous solid dispersions; a comparison between hot-melt extrusion and spray drying

Objectives: Amorphous drug forms provide a useful method of enhancing the dissolution performance of poorly water-soluble drugs; however, they are inherently unstable. In this article, we have used Flory–Huggins theory to predict drug solubility and miscibility in polymer candidates, and used this information to compare spray drying and melt extrusion as processes to manufacture solid dispersions.
Method:  Solid dispersions were characterised using a combination of thermal (thermogravimetric analysis and differential scanning calorimetry) and spectroscopic (Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction methods. 
Key Findings: Spray drying permitted generation of amorphous solid dispersions to be produced across a wider drug concentration than melt extrusion. Melt extrusion provided sufficient energy for more intimate mixing to be achieved between drug and polymer, which may improve physical stability. It was also confirmed that stronger drug–polymer interactions might be generated through melt extrusion. Remixing and dissolution of recrystallised felodipine into the polymeric matrices did occur during the modulated differential scanning calorimetry analysis, but the complementary information provided from FTIR confirms that all freshly prepared spray-dried samples were amorphous with the existence of amorphous drug domains within high drug-loaded samples. 
Conclusion: Using temperature–composition phase diagrams to probe the relevance of temperature and drug composition in specific polymer candidates facilitates polymer screening for the purpose of formulating solid dispersions.

Effect of the Electrolyte Formulation on the Performances of Edlc and Li-Ion Batteries

One of the most important components in electrochemical storage devices (batteries and supercapacitors) is undoubtedly the electrolyte. The basic function of any electrolyte in these systems is the transport of ions between the positive and negative electrodes. In addition, electrochemical reactions occurring at each electrode/electrolyte interface are the origin of the current generated by storage devices. In other words, performances (capacity, power, efficiency and energy) of electrochemical storage devices are strongly related to the electrolyte properties, as well as, to the affinity for the electrolyte to selected electrode materials. Indeed, the formulation of electrolyte presenting good properties, such as high ionic conductivity and low viscosity, is then required to enhance the charge transfer reaction at electrode/electrolyte interface (e.g. charge accumulation in the case of Electrochemical Double Layer Capacitor, EDLC). For practical and safety considerations, the formulation of novel electrolytes presenting a low vapor pressure, a large liquid range temperature, a good thermal and chemical stabilities is also required.

This lecture will be focused on the effect of the electrolyte formulation on the performances of electrochemical storage devices (Li-ion batteries and supercapacitors). During which, a summary of the physical, thermal and electrochemical data obtained by our group, recently, on the formulation of novel electrolyte-based on the mixture of an ionic liquid (such as EmimNTf2 and Pyr14NTf2) and carbonate or dinitrile solvents will be presented and commented. The impact of the electrolyte formulation on the storage performances of EDLC and Li-ion batteries will be also discussed to further understand the relationship between electrolyte formulation and electrochemical performances. This talk will also be an opportunity to further discuss around the effects of additives (SEI builder: fluoroethylene carbonate and vinylene carbonate), ionic liquids, structure and nature of lithium salt (LiTFSI vs LiPF6) on the cyclability of negative electrode to then enhance the electrolyte formulation. For that, our recent results on TiSnSb and graphite negative electrodes will be presented and discussed, for example 1,2.

1-C. Marino, A. Darwiche1, N. Dupré, H.A. Wilhelm, B. Lestriez, H. Martinez, R. Dedryvère, W. Zhang, F. Ghamouss, D. Lemordant, L. Monconduit “ Study of the Electrode/Electrolyte Interface on Cycling of a Conversion Type Electrode Material in Li Batteries” J. Phys.chem. C, 2013, 117, 19302-19313

2- Mouad Dahbi, Fouad Ghamouss, Mérièm Anouti, Daniel Lemordant, François Tran-Van “Electrochemical lithiation and compatibility of graphite anode using glutaronitrile/dimethyl carbonate mixtures containing LiTFSI as electrolyte” 2013, 43, 4, 375-385.

Synchronized and controlled release of metformin hydrochloride/glipizide from elementary osmotic delivery

The combination of metformin hydrochloride (MTF) and glipizide (GLZ) is second-line medication for diabetes mellitus type 2 (DMT2). In the present study, elementary osmotic pump(EOP)tablet is designed to deliver the combination of MTF and GLZ in a sustained and synchronized manner. By analyzing different variables of the formulation, sodium hydrogen carbonate is introduced as pH modifier to improve the release of GLZ, while ethyl cellulose acts as release retardant to reduce the burst release phase of MTF. A two factor, three level face-centered central composite design (FCCD) is applied to investigate the impact of different factors on drug release profile. Compared with conventional tablets, the elementary osmotic pump (EOP) tablet demonstrates a controlled release behavior with relative bioavailability of 99.2% for MTF and 99.3% for GLZ. Data also shows EOP tablet is able to release MTF and GLZ in a synchronized and sustained manner both in vitro and in vivo

Automated Equation Formulation for Causal Loop Diagrams

The annotation of Business Dynamics models with parameters and equations, to simulate the system under study and further evaluate its simulation output, typically involves a lot of manual work. In this paper we present an approach for automated equation formulation of a given Causal Loop Diagram (CLD) and a set of associated time series with the help of neural network evolution (NEvo). NEvo enables the automated retrieval of surrogate equations for each quantity in the given CLD, hence it produces a fully annotated CLD that can be used for later simulations to predict future KPI development. In the end of the paper, we provide a detailed evaluation of NEvo on a business use-case to demonstrate its single step prediction capabilities.