The Effect of Azithromycin on Ivermectin Pharmacokinetics—A Population Pharmacokinetic Model Analysis

This paper describes the use of a modeling and simulation approach to explore a reported pharmacokinetic interaction between two drugs (ivermectin and azithromycin), which along with albendazole, are being developed for combination use in neglected tropical diseases. This approach is complementary to more traditional pharmacokinetic and safety studies that need to be conducted to support combined use of different health interventions. A mathematical model of ivermectin pharmacokinetics was created and used to simulate multiple trials, and the probability of certain outcomes (very high peak blood ivermectin levels when given in combination) was determined. All simulated peak blood levels were within ranges known to be safe and well tolerated. Additional field studies are needed to confirm these findings

Evaluation of serum level of some angiogenic factors in non hodgkin's lymphoma

Background: Angiogenesis is a prerequisite for growth of tumors whether solid or liquid tumors. The process of angiogenesis is very complex and tightly regulated by positive and negative regulatory factors, the precise role of these processes in lymphoma pathogenesis is under active investigation. This work aimed at assessing serum levels of certain angiogenic factors in cases of non Hodgkin's lymphoma (NHL) whether newly diagnosed or relapsed and there correlations to disease progression and staging. Methods: Serum levels of certain positive regulatory factors for angiogenisis namely "Angiogenin, Nitric oxide, Copper", and Zinc as a negative regulatory factor were assayed, and Copper / zinc ratio were determined in 57 patients of NHL classified into four groups according to the disease stage investigated before the start of chemotherapy and 20 healthy controls. Result: Patients in 1 st group (stage I and II) showed significant elevation in serum levels of angiogenin, copper, and insignificant changes occurred in serum levels of zinc, nitric oxide and in copper zinc ratio in comparison with the control group. On the other hand; patients in 2 nd group (stage III) and 3 rd group (stage IV) showed highly significant increase in serum levels of copper and copper zinc ratio; while insignificant changes occurred in serum levels of angiogenin and nitric oxide. Conversely, highly significant decrease occurred in serum levels of zinc in 2 nd group only. Patients in 4 th group (relapsed cases) showed highly significant increase in serum levels of copper, significant increase in serum levels of angiogenin and in copper/inc ratio, while insignificant changes occurred in serum levels of zinc, and nitric oxide. The comparison between different patients groups revealed no significant differences in all special investigations except for zinc where there was a significant lower level of zinc in 2 nd group than 1 st group, and for copper and copper/zinc ratio; there were significant rise of each in 4thgroup in comparison to 1 st group. Conclusion: The serum angiogenin and copper levels may play an important role in early detection of NHL as it increased significantly in early stages, the highest levels were found in advanced cases together with low zinc level suggesting their role in follow up of NHL together with consideration of copper /zinc ratio while limited role of nitric oxid had been observed

Observed, population predicted, and individual predicted ivermectin concentrations of individual subjects following ivermectin alone (No AZ) and after co-administration with azithromycin (AZ) for Subpopulation B, where increased bioavailability is observed in the interaction period.

<p>The solid line represents the fit predicted by the typical pharmacokinetic mixture model parameters. The dashed line shows the fit of the post hoc estimates of the population model. Circles represent the observed concentrations.</p

Key pharmacokinetic parameters.

<p>Key pharmacokinetic parameters.</p

Upper panel: Observed maximum ivermectin concentration data in baseline and interaction arms from all subjects (open boxes) and from subpopulations A and B (shaded and hatched boxes).

<p>Lower panel: Maximum concentration data from 1000 simulation replicates using the non-mixture model in all subjects (open boxes) and from the mixture model in subpopulations A and B (shaded and hatched boxes). The line in the interior of the box denotes the median, the bottom and top edges denote the first and third quartiles, respectively. The lines from the top and bottom edges extend to 1.5 times the interquartile range. Values exceeding the interquartile range are plotted as individual points.</p

Final Non-Mixture Model Parameter Estimates and Their Variabilities.

<p>Point Estimate = Final Parameter Estimates for <i>θ</i>s, ω<i>s</i>, and σs; SEE = standard error of estimates; %RSE = relative standard error (100^*(SEE/Estimate));</p><p>IIV(%CV) = interpatient variability (100^*sqrt(Estimate for <i>ω²</i>)); <i>ω²</i>: random effect parameter that represents inter-patient variance; σ^2: random effect parameter that represents residual variance.</p

Two-compartment pharmacokinetic structural model for ivermectin.

<p>The best fit was obtained by models for two subpopulation (A and B), characterized by different F values, relative to the baseline model that included all subjects. Parameters: central and peripheral compartment volumes, total body clearance (CL), inter-compartmental clearance (Q), rate of absorption, and relative bioavailability (F). Note that albendazole was administered in both baseline and interaction phases.</p