Tribo-electrification of active pharmaceutical ingredients and excipients

Blending of active pharmaceutical ingredient (API) and excipients is a pre-requisite to the dry manufacture of solid dosage forms intended for oral use, whether or not granulation steps are employed prior to compaction. Excipients and API are known to be subject to tribo-electric charging, against each other and the materials in which the blends are manufactured (e.g. stainless steel 316). This study aimed to assess and compare the magnitude of tribo-electric charging of excipients and API using a material-sparing technique. Intra-sample variability in tribo-electric charging was found to be generally low. The results showed that excipients had lower charge levels and smaller variability as compared to the API materials. Some of the APIs tested charged extensively to the levels in excess of ± 150 nC/g. It was also found that the extent of particle adhesion to surfaces of the container walls for charged API was considerably greater compared to the excipients. These results suggest that the extent and variability of tribo-electric charging of APIs is the predominant contributor to variability in electrostatic charge of pharmaceutical blends and to any related formulation issues. It is therefore reasonable to conclude that, to control the electrostatic properties of a formulation, it is a priority to control the particle properties of the API

The use of artificial neural networks for the selection of the most appropriate formulation and processing variables in order to predict the in vitro dissolution of sustained release minitablets

The objective of this work was to apply artificial neural networks (ANNs) to examine the relative importance of various factors, both formulation and process, governing the in-vitro dissolution from enteric-coated sustained release (SR) minitablets. Input feature selection (IFS) algorithms were used in order to give an estimate of the relative importance of the various formulation and processing variables in determining minitablet dissolution rate. Both forward and backward stepwise algorithms were used as well as genetic algorithms. Networks were subsequently trained using the back propagation algorithm in order to check whether or not the IFS process had correctly located any unimportant inputs. IFS gave consistent rankings for the importance of the various formulation and processing variables in determining the release of drug from minitablets. Consistent ranking was achieved for both indices of the release process; ie, the time taken for release to commence through the enteric coat (Tlag) and that for the drug to diffuse through the SR matrix of the minitablet into the dissolution medium (T90-10). In the case of the Tlag phase, the main coating parameters, along with the original batch blend size and the blend time with lubricant, were found to have most influence. By contrast, with the T90-10 phase, the amounts of matrix forming polymer and direct compression filler were most important. In the subsequent training of the ANNs, removal of inputs regarded as less important led to improved network performance. ANNs were capable of ranking the relative importance of the various formulations and processing variables that influenced the release rate of the drug from minitablets. This could be done for all main stages of the release process. Subsequent training of the ANN verified that removal of less relevant inputs from the training process led to an improved performance from the ANN

The Australian National Rabbit Database: 50 yr of population monitoring of an invasive species

Abstract With ongoing introductions into Australia since the 1700s, the European rabbit (Oryctolagus cuniculus) has become one of the most widely distributed and abundant vertebrate pests, adversely impacting Australia's biodiversity and agro-economy. To better understand the population and range dynamics of the species and its impacts, occurrence and abundance data have been collected by researchers and citizens from sites covering a broad spectrum of climatic and environmental conditions in Australia. The lack of a common and accessible repository for these data has, however, limited their use in determining important spatiotemporal drivers of the structure and dynamics of the geographical range of rabbits in Australia. To meet this need, we created the Australian National Rabbit Database which combines more than 50 years of historical and contemporary survey data collected from throughout the range of the species in Australia. The survey data, obtained from a suite of complementary monitoring methods, were combined with high-resolution weather, climate and environmental information, and an assessment of data quality. The database provides records of rabbit occurrence (689,265 records) and abundance (51,241 records, > 120 distinct sites) suitable for identifying the spatiotemporal drivers of the rabbit's distribution and for determining spatial patterns of variation in its key life history traits, including maximum rates of population growth. Since all data are georeferenced and date stamped, they can be coupled with information from other databases and spatial layers to explore the potential effects of rabbit occurrence and abundance on Australia's native wildlife and agricultural production. The Australian National Rabbit Database is an important tool for understanding and managing the European rabbit in its invasive range and its effects on native biodiversity and agricultural production. It also provides a valuable resource for addressing questions related to the biology, success, and impacts of invasive species more generally. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper. This article is protected by copyright. All rights reserved