Tailoring Atomoxetine Release Rate from DLP 3D-Printed Tablets Using Artificial Neural Networks: Influence of Tablet Thickness and Drug Loading.

Various three-dimensional printing (3DP) technologies have been investigated so far in relation to their potential to produce customizable medicines and medical devices. The aim of this study was to examine the possibility of tailoring drug release rates from immediate to prolonged release by varying the tablet thickness and the drug loading, as well as to develop artificial neural network (ANN) predictive models for atomoxetine (ATH) release rate from DLP 3D-printed tablets. Photoreactive mixtures were comprised of poly(ethylene glycol) diacrylate (PEGDA) and poly(ethylene glycol) 400 in a constant ratio of 3:1, water, photoinitiator and ATH as a model drug whose content was varied from 5% to 20% (w/w). Designed 3D models of cylindrical shape tablets were of constant diameter, but different thickness. A series of tablets with doses ranging from 2.06 mg to 37.48 mg, exhibiting immediate- and modified-release profiles were successfully fabricated, confirming the potential of this technology in manufacturing dosage forms on demand, with the possibility to adjust the dose and release behavior by varying drug loading and dimensions of tablets. DSC (differential scanning calorimetry), XRPD (X-ray powder diffraction) and microscopic analysis showed that ATH remained in a crystalline form in tablets, while FTIR spectroscopy confirmed that no interactions occurred between ATH and polymers.

Evaluation of a Potential Metabolism-Mediated Drug-Drug Interaction Between Atomoxetine and Bupropion in Healthy Volunteers.

PURPOSE: To evaluate the impact of bupropion on the pharmacokinetic profile of atomoxetine and its main active metabolite (glucuronidated form), 4-hydroxyatomoxetine-O-glucuronide, in healthy volunteers. METHODS: An open-label, non-randomized, two-period, sequential clinical trial was conducted as follows: during Period I (Reference), each volunteer received a single oral dose of 25 mg atomoxetine, whilst during Period II (Test), a combination of 25 mg atomoxetine and 300 mg bupropion was administered to all volunteers, after a pretreatment regimen with bupropion for 7 days. Next, after determining atomoxetine and 4-hydroxyatomoxetine-O-glucuronide plasma concentrations, their pharmacokinetic parameters were calculated using a noncompartmental method and subsequently compared to determine any statistically significant differences between the two periods. RESULTS: Bupropion intake influenced all the pharmacokinetic parameters of both atomoxetine and its metabolite. For atomoxetine, Cmax increased from 226±96.1 to 386±137 ng/mL and more importantly, AUC0-∞ was significantly increasedfrom 1580±1040 to 8060±4160 ng*h/mL, while the mean t1/2 was prolonged after bupropion pretreatment. For 4-hydroxyatomoxetine-O-glucuronide, Cmax and AUC0-∞  were decreased from 707±269 to 212±145 ng/mL and from 5750±1240 to 3860±1220 ng*h/mL, respectively. CONCLUSIONS: These results demonstrated that the effect of bupropion on CYP2D6 activity was responsible for an increased systemic exposure to atomoxetine (5.1-fold) and also for a decreased exposure to its main metabolite (1.5-fold). Additional studies are required in order to evaluate the clinical relevance of this pharmacokinetic drug interaction.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

Exploring the Inhibitory Mechanism of Approved Selective Norepinephrine Reuptake Inhibitors and Reboxetine Enantiomers by Molecular Dynamics Study.

Selective norepinephrine reuptake inhibitors (sNRIs) provide an effective class of approved antipsychotics, whose inhibitory mechanism could facilitate the discovery of privileged scaffolds with enhanced drug efficacy. However, the crystal structure of human norepinephrine transporter (hNET) has not been determined yet and the inhibitory mechanism of sNRIs remains elusive. In this work, multiple computational methods were integrated to explore the inhibitory mechanism of approved sNRIs (atomoxetine, maprotiline, reboxetine and viloxazine), and 3 lines of evidences were provided to verify the calculation results. Consequently, a binding mode defined by interactions between three chemical moieties in sNRIs and eleven residues in hNET was identified as shared by approved sNRIs. In the meantime, binding modes of reboxetine's enantiomers with hNET were compared. 6 key residues favoring the binding of (S, S)-reboxetine over that of (R, R)-reboxetine were discovered. This is the first study reporting that those 11 residues are the common determinants for the binding of approved sNRIs. The identified binding mode shed light on the inhibitory mechanism of approved sNRIs, which could help identify novel scaffolds with improved drug efficacy.