Comment on "In Vivo Drug Delivery Performance of Lipiodol-Based Emulsion or Drug-Eluting Beads in Patients with Hepatocellular Carcinoma"

A novel combination therapy for multidrug resistant pathogens using chitosan nanoparticles loaded with β-lactam antibiotics and β-lactamase inhibitors

Antimicrobial resistance is one of the greatest global threats. Particularly, multidrug resistant extended-spectrum β-lactamase (ESBL)-producing pathogens confer resistance to many commonly used medically important antibiotics, especially beta-lactam antibiotics. Here, we developed an innovative combination approach to therapy for multidrug resistant pathogens by encapsulating cephalosporin antibiotics and β-lactamase inhibitors with chitosan nanoparticles (CNAIs). The four combinations of CNAIs including two cephalosporin antibiotics (cefotaxime and ceftiofur) with two β-lactamase inhibitors (tazobactam and clavulanate) were engineered as water-oil-water emulsions. Four combinations of CNAIs showed efficient antimicrobial activity against multidrug resistant ESBL-producing Enterobacteriaceae. The CNAIs showed enhanced antimicrobial activity compared to naïve chitosan nanoparticles and to the combination of cephalosporin antibiotics and β-lactamase inhibitors. Furthermore, CNAIs attached on the bacterial surface changed the permeability to the outer membrane, resulting in cell damage that leads to cell death. Taken together, CNAIs have provided promising potential for treatment of diseases caused by critically important ESBL-producing multidrug resistant pathogens.

Porcine and Human In Vivo Simulations for Doxorubicin-Containing Formulations Used in Locoregional Hepatocellular Carcinoma Treatment

It is important to be able to simulate and predict formulation effects on the pharmacokinetics of a drug in order to optimize effectivity in clinical practice and drug development. Two formulations containing doxorubicin are used in the treatment of hepatocellular carcinoma (HCC): a Lipiodol-based emulsion (LIPDOX) and a loadable microbead system (DEBDOX). Although equally effective, the formulations are vastly different, and little is known about the parameters affecting doxorubicin release in vivo. However, mathematical modeling can be used to predict doxorubicin release properties from these formulations and its in vivo pharmacokinetic (PK) profiles. A porcine semi-physiologically based pharmacokinetic (PBPK) model was scaled to a human physiologically based biopharmaceutical (PBBP) model that was altered to include HCC. DOX in vitro and in vivo release data from LIPDOX or DEBDOX were collected from the literature and combined with these in silico models. The simulated pharmacokinetic profiles were then compared with observed porcine and human HCC patient data. DOX pharmacokinetic profiles of LIPDOX-treated HCC patients were best predicted from release data sets acquired by in vitro methods that did not use a diffusion barrier. For the DEBDOX group, the best predictions were from the in vitro release method with a low ion concentration and a reduced loading dose. The in silico modeling combined with historical release data was effective in predicting in vivo plasma exposure. This can give useful insights into the release method properties necessary for correct in vivo predictions of pharmacokinetic profiles of HCC patients dosed with LIPDOX or DEBDOX.