The effect of Clip-tone® and its smartphone application on optimisation of metered-dose inhalers inhalation technique.

BACKGROUNDS: Although metered-dose inhalers (pMDI) therapy is convenient and widely prescribed, its use usually results in repetitive inhalation technique errors. One of the most repetitive errors is inhaling too fast through the pMDI. The present study aimed to evaluate the effect of Clip-tone® along with smartphone visual feedback application on the subject's inhalation time. METHODS: Two hundred subjects were included in the study. They were randomised into four groups. Group 1 received only verbal counselling; group 2 received verbal counselling with resistance (a modified Clip-tone® that does not produce whistle attached to their pMDI); group 3 received verbal counselling plus whistle (as audio feedback) from ordinary Clip-tone® and group 4 received verbal counselling plus audio feedback (whistle) from Clip-tone® and visual feedback (smartphone application). Inhalation time through the pMDI for each subject was recorded three times and inter and intra-subjects variations were calculated. RESULTS: Verbal counselling plus audio feedback and verbal counselling plus audio and visual feedbacks groups had 45/50 (90%) and 37/50 (74%) subjects respectively, having correct inhalation flow (inhaling at between 3 to 7 seconds). Verbal counselling plus audio feedback and verbal counselling plus audio and visual feedbacks groups' inter and intra-subjects variations were lower than that of verbal counselling and verbal counselling with resistance groups which had 28/50 (52%) and 20/50 (40%) subjects respectively, with inhalation time between 3 and 7 seconds. CONCLUSIONS: Providing audio feedback by the Clip-tone® along with smartphone visual feedback application maintained the deep and slow inhalation through pMDI much better compared to verbal counselling only. We recommend the patients to take all their inhaled doses using pMDI attached to a training device like Clip-tone® along with a smartphone visual feedback application for optimisation of the aerosol delivery from the pMDI.

In vitro and in vivo performance modelling and optimisation of different dry powder inhalers: A complementary study of neural networks, genetic algorithms and decision trees.

INTRODUCTION: Aerosol delivery from DPIs could be affected by different factors. This study aimed to evaluate and predict the effects of different factors on drug delivery from DPIs. METHODS: Modelling and optimisation for both in vitro and in vivo data of different DPIs (Diskus, Turbohaler and Aerolizer) were carried out using neural networks associated with genetic algorithms and the results are confirmed using a decision tree (DT) and random forest regressor (RFR). All variables (the type of DPI, inhalation flow, inhalation volume, number of inhalations and type of subject) were coded as numbers before using them in the modelling study. RESULTS: The analysis of the in vitro model showed that Turbohaler had the highest emitted dose compared with the Diskus and the Aerolizer. Increasing flow resulted in a gradual increase in the emitted dose. Little differences between the inhalation volumes 2 and 4 litres were shown at fast inhalation flow, and interestingly two inhalations showed somewhat higher emitted doses than one-inhalation mode with Turbohaler and Diskus at slow inhalation flow. Regarding the in vivo model, the percent of drug delivered to the lung was highly increased with Turbohaler and Diskus in healthy subjects where continuous contour lines were observed. The Turbohaler showed increased lung bioavailability with the two-inhalation modes, the Diskus showed a nearly constant level at both one and two inhalations at slow inhalation. The Turbohaler and Aerolizer showed little increasing effect moving from one to two inhalations at slow inhalation. CONCLUSIONS: Modelling of the input data showed a good differentiating and prediction power for both in vitro and in vivo models. The results of the modelling refer to the high efficacy of Diskus followed by Turbohaler for delivering aerosol. With two inhalations, the three DPIs showed an increase in the percent of drug excreted at slow inhalations.