Risk Indicators Improve the Prescription Quality of Drugs with Anticholinergic Properties in Nursing Homes

Aim: The objective of this study was to assess the impact of a collaborative therapeutic optimization program on the rate of potentially inappropriate prescription of drugs with anticholinergic properties in nursing homes. Methods: Quasi-experimental study in 37 nursing homes in France. The intervention included the use of quality indicators for prescriptions combined with educational sessions and dedicated materials for nursing home staff (unlimited access to study material for staff, including nurses, general practitioners, pharmacists). Indicators were calculated based on routine data collected from an electronic pill dispenser system. The primary outcome was the presence of at least one prescription containing ≥1 drug from a list of 12 drugs with anticholinergic properties. A difference-in-differences analysis was conducted at 18 months as well as propensity score weighting to minimize any potential indication bias. A generalized estimating equation model estimated the probability of being prescribed at least one target drug at any time during a 9-month period for each resident. Results: In total, 33 nursing homes (intervention group: n = 10; control group: n = 23) were included, totalling 8137 residents. There was a decrease in the use of drugs with anticholinergic properties over time in both groups, as well as a decline in the intervention group compared to the control group (Odds Ratio: 0.685, 95% CI: 0.533, 0.880; p < 0.01) that was attributable to the intervention. An estimated 49 anticholinergic properties drug prescriptions were avoided by the intervention. Conclusion: This study found that an intervention based on indicators derived from routine prescription data was effective in reducing use of drugs with anticholinergic properties prescriptions in nursing homes.

Role of Ligand Distribution in the Cytoskeleton-Associated Endocytosis of Ellipsoidal Nanoparticles

Nanoparticle (NP)–cell interaction mediated by receptor–ligand bonds is a crucial phenomenon in pathology, cellular immunity, and drug delivery systems, and relies strongly on the shape of NPs and the stiffness of the cell. Given this significance, a fundamental question is raised on how the ligand distribution may affect the membrane wrapping of non-spherical NPs under the influence of cytoskeleton deformation. To address this issue, in this work we use a coupled elasticity–diffusion model to systematically investigate the role of ligand distribution in the cytoskeleton-associated endocytosis of ellipsoidal NPs for different NP shapes, sizes, cytoskeleton stiffness, and the initial receptor densities. In this model, we have taken into account the effects of receptor diffusion, receptor–ligand binding, cytoskeleton and membrane deformations, and changes in the configuration entropy of receptors. By solving this model, we find that the uptake process can be significantly influenced by the ligand distribution. Additionally, there exists an optimal state of such a distribution, which corresponds to the fastest uptake efficiency and depends on the NP aspect ratio and cytoskeleton stiffness. We also find that the optimal distribution usually needs local ligand density to be sufficiently high at the large curvature region. Furthermore, the optimal state of NP entry into cells can tolerate slight changes to the corresponding optimal distribution of the ligands. The tolerance to such a change is enhanced as the average receptor density and NP size increase. These results may provide guidelines to control NP–cell interactions and improve the efficiency of target drug delivery systems.

Formulary Drug Review: Belumosudil

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Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

Preparation, characterization, and in vitro release kinetics of doxorubicin-loaded magnetosomes

The doxorubicin (DOX) was successfully coupled to the magnetosomes from Acidithiobacillus ferrooxidans ( At. ferrooxidans) by genipin bridging. The parameters (magnetosome concentration, DOX concentration, genipin concentration-, and cross-link time) expected for temperature significantly influenced the coupling rate. Bacterial magnetosome-doxorubicin complexes (BMDCs) were characterized by transmission electron microscope (TEM), particle size analyzer and Fourier transform infrared spectroscopy. Results indicated that BMDCs exhibited a mean particle size of 83.98 mm and displayed a negative charge. The chemical reaction occurring between CO and NH group and the physical adsorption predominated by electrostatic interaction were found to involve in coupling. BMDCs can release 40% of DOX in simulated gastrointestinal conditions within 38 h. Kinetic models including Higuchi, Korsmeyer–Peppas, Zero order, First order, Hixon-Crowell, Baker-Lonsdale, and Weibull and Gompertz were utilized to explore the release mechanism of DOX from BMDCs. All models were found to fit well (r2 ≥ 0.8144) with the release data and the Gompertz was the best fit model (r2 = 0.9742), implying that the complex mechanisms involving Fickian and Gompertz diffusion contributed to the release. These findings suggested that magnetosomes from At. ferrooxidans have great potential applications in biomedical and clinical fields as the carrier of target drug delivery systems in the future.

Molecular Modeling Techniques Applied to the Design of Multitarget Drugs: Methods and Applications

: Multifactorial diseases, such as cancer and diabetes present a challenge for the traditional “one-target, one disease” paradigm due to their complex pathogenic mechanisms. Although a combination of drugs can be used, a multitarget drug may be a better choice face of its efficacy, lower adverse effects and lower chance of resistance development. The computer-based design of these multitarget drugs can explore the same techniques used for single-target drug design, but the difficulties associated to the obtention of drugs that are capable of modulating two or more targets with similar efficacy impose new challenges, whose solutions involve the adaptation of known techniques and also to the development of new ones, including machine-learning approaches. In this review, some SBDD and LBDD techniques for the multitarget drug design are discussed, together with some cases where the application of such techniques led to effective multitarget ligands.

Formulation and In Vitro Evaluation of Pellets Containing Sulfasalazine and Caffeine to Verify Ileo-Colonic Drug Delivery

The ColoPulse coating is a pH-dependent coating that can be used to target drug release to the ileo-colonic region. ColoPulse coated tablets and capsules have demonstrated their targeting capabilities in vivo in more than 100 volunteers and patients. However, so far the ColoPulse coating has not been used for multi-particulate pellet formulations. The sulfasalazine–caffeine method can be used to confirm ileo-colonic drug delivery in vivo. Caffeine serves as a release marker in this method, while sulfasalazine serves as a marker for colonic arrival. In this study, extrusion–spheronization was used to produce microcrystalline cellulose based pellets containing both caffeine and sulfasalazine. Dissolution tests revealed that a superdisintegrant, i.e., croscarmellose sodium or sodium starch glycolate, should be incorporated in the formulation to achieve acceptable release profiles for both sulfasalazine and caffeine. However, acceptable release profiles were only obtained when the pelletizing liquid consisted of ethanol/water 1/1 (v/v) but not with pure water. This phenomenon was ascribed to the differences in the degree of swelling of the superdisintegrant in the pelletizing liquid during the granulation process. The pellets were coated with the ColoPulse coating and showed the desired pH-dependent pulsatile release profile in vitro. In future clinical studies, ileo-colonic targeting should be verified.

Genome-scale CRISPR-Cas9 knockout screening in hepatocellular carcinoma with lenvatinib resistance

Lenvatinib is the first target drug approved for advanced hepatocellular carcinoma (HCC). However, the development of drug resistance is common, and the mechanisms of lenvatinib resistance and resistant targets in HCC are poorly understood. By using CRISPR/Cas9 library screening, we screened out two key resistance genes, neurofibromin 1(NF1), and dual specificity phosphatase 9 (DUSP9), as critical drivers for lenvatinib resistance in HCC. With RNAi knockdown and CRISPR/Cas9 knockout models, we further clarified the mechanisms by which NF1 loss reactivates the PI3K/AKT and MAPK/ERK signaling pathways, while DUSP9 loss activates the MAPK/ERK signaling pathways, thereby inactivating FOXO3, followed by degradation of FOXO3, finally induced lenvatinib resistance. We also screened out trametinib, a small molecule pathway inhibitor for MEK, that can be used to reverse resistance induced by NF1 and DUSP9 loss in HCC cells. Trametinib was still able to halt HCC growth even when NF1 was knocked out in mice. Collectively, the findings indicate that NF1 and DUSP9 takes critical role in lenvatinib resistance and may be novel specific targets and predictive markers for lenvatinib resistance in HCC.