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https://www.selleckchem.com/products/gdc-0068.html Developments in information technology have impacted on all areas of modern life and in particular facilitated the growth of globalisation in commerce and communication. Within the drugs area this means that both drugs discourse and drug markets have become increasingly digitally enabled. In response to this, new methods are being developed that attempt to research and monitor the digital environment. In this commentary we present three case studies of innovative approaches and related challenges to software-automated data mining of the digital environment (i) an e-shop finder to detect e-shops offering new psychoactive substances, (ii) scraping of forum data from online discussion boards, (iii) automated sentiment analysis of discussions in online discussion boards. We conclude that the work presented brings opportunities in terms of leveraging data for developing a more timely and granular understanding of the various aspects of drug-use phenomena in the digital environment. In particular, combining the number of e-shops, discussion posts, and sentiments regarding particular substances could be used for ad hoc risk assessments as well as longitudinal drug monitoring and indicate "online popularity". The main challenges of digital data mining involve data representativity and ethical considerations. Emerging evidence indicates that illicit drug overdoses are increasing throughout the COVID-19 pandemic. There is a paucity of evidence on the causative pathways for this trend, but expert opinions, commentaries, and some reviews offer theoretical underpinnings. In this rapid review, we collate the available published evidence, expert opinions, commentaries, and reviews on the unintended pathways between COVID-19 public health responses and increasing illicit drug overdoses. Using tenets of thematic analyses and grounded theory, we also offer a visual conceptual framework for these unintended pathways. Our framework foc

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