Novel Technique of Interproximal Enamel Reduction Based on Computer-Aided Navigation Technique-An In Vitro Study.

The aim of this study was to analyze and compare the accuracy of a novel interproximal enamel reduction (IPR) technique based on a computer-aided static navigation technique with respect to a conventional free-hand-based technique for interproximal enamel reduction. Twenty anatomical-based experimental cast models of polyurethane were randomly distributed into the following IPR techniques: IPR technique based on computer-aided static navigation technique (n = 10) (GI) for Group A and conventional free-hand-based technique for the IPR (n = 10) (FHT) for Group B. The anatomical-based experimental cast models of polyurethane randomly assigned to the GI study group were submitted for a preoperative 3D intraoral surface scan; then, datasets were uploaded into 3D implant-planning software to design virtual templates for the interproximal enamel reduction technique. Afterward, the anatomical-based experimental cast models of polyurethane of both GI and FHT study groups were subjected to a postoperative digital impression by a 3D intraoral surface scan to compare the accuracy of the interproximal enamel reduction techniques at the buccal (mm), lingual/palatal (mm), and angular (◦) levels using the Student t-test. Statistically significant differences between the interproximal enamel reduction technique based on the computer-aided static navigation technique and the conventional free-hand-based technique for the interproximal enamel reduction at the buccal (p = 0.0008) and lingual/palatal (p < 0.0001) levels; however, no statistically significant differences were shown at the angular level (p = 0.1042). The interproximal enamel reduction technique based on computer-aided static navigation technique was more accurate than the conventional free-hand-based technique for interproximal enamel reduction.

In Vitro-In Silico Modeling of Caffeine and Diclofenac Permeation in Static and Fluidic Systems with a 16HBE Lung Cell Barrier.

Static in vitro permeation experiments are commonly used to gain insights into the permeation properties of drug substances but exhibit limitations due to missing physiologic cell stimuli. Thus, fluidic systems integrating stimuli, such as physicochemical fluxes, have been developed. However, as fluidic in vitro studies display higher complexity compared to static systems, analysis of experimental readouts is challenging. Here, the integration of in silico tools holds the potential to evaluate fluidic experiments and to investigate specific simulation scenarios. This study aimed to develop in silico models that describe and predict the permeation and disposition of two model substances in a static and fluidic in vitro system. For this, in vitro permeation studies with a 16HBE cellular barrier under both static and fluidic conditions were performed over 72 h. In silico models were implemented and employed to describe and predict concentration-time profiles of caffeine and diclofenac in various experimental setups. For both substances, in silico modeling identified reduced apparent permeabilities in the fluidic compared to the static cellular setting. The developed in vitro-in silico modeling framework can be expanded further, integrating additional cell tissues in the fluidic system, and can be employed in future studies to model pharmacokinetic and pharmacodynamic drug behavior.