Infrastructure autopoiesis: requisite variety to engage complexity

Infrastructure systems must change to match the growing complexity of the environments they operate in. Yet the models of governance and the core technologies they rely on are structured around models of relative long-term stability that appear increasingly insufficient and even problematic. As the environments in which infrastructure function become more complex, infrastructure systems must adapt to develop a repertoire of responses sufficient to respond to the increasing variety of conditions and challenges. Whereas in the past infrastructure leadership and system design has emphasized organization strategies that primarily focus on exploitation (e.g., efficiency and production, amenable to conditions of stability), in the future they must create space for exploration, the innovation of what the organization is and does. They will need to create the abilities to maintain themselves in the face of growing complexity by creating the knowledge, processes, and technologies necessary to engage environment complexity. We refer to this capacity as infrastructure autopoiesis. In doing so infrastructure organizations should focus on four key tenets. First, a shift to sustained adaptation – perpetual change in the face of destabilizing conditions often marked by uncertainty – and away from rigid processes and technologies is necessary. Second, infrastructure organizations should pursue restructuring their bureaucracies to distribute more resources and decisionmaking capacity horizontally, across the organization’s hierarchy. Third, they should build capacity for horizon scanning, the process of systematically searching the environment for opportunities and threats. Fourth, they should emphasize loose fit design, the flexibility of assets to pivot function as the environment changes. The inability to engage with complexity can be expected to result in a decoupling between what our infrastructure systems can do and what we need them to do, and autopoietic capabilities may help close this gap by creating the conditions for a sufficient repertoire to emerge.

A horizon scanning approach to rapidly detect alien fern species through horticultural trade

Horticultural trade is a well-documented pathway of introduction for numerous invasive species globally, including ferns. In this study, we analysed trade in terrestrial true ferns (Polypodiophyta) in six anglophone countries: Canada (CA), the United States of America (US), Great Britain and Ireland (GB, for ease of reading), South Africa (ZA), Australia (AU), and New Zealand (NZ). The study provides an overview of fern trade and explored the relationship between trade and alien fern introductions with a view to better inform management interventions. Using a horizon scanning approach in consulting horticultural catalogues, we identified a total of 382 fern species currently traded by 148 traders in a period of just six months. International trade was observed in only three countries with most trade occurring at national scales and e-commerce was not the dominant mode of trade noted in this study, with a relatively higher proportion of species traded on-ground. Alien species accounted for more than 60 % of the total number of traded species in most countries except in AU and NZ, and a surprising number of species (11-14 species per country) known to be naturalised or invasive in their country of trade remain actively traded, with fewer species in CA (2) and AU (5). A total of 194 species noted in trade have not previously been recorded as alien in plant species inventories and did not have an invasion status assigned in their countries of trade. We identified 62 species of concern (i.e., potential future invaders) with Dryopteris erythrosora, Anisocampium niponicum, Polystichum polyblepharum, Austroblechnum penna-marina subsp. penna-marina, Asplenium nidus, Dicksonia antarctica, Polypodium vulgare, and Adiantum raddianum indicated as priority species for regulation in trade due to their high market presence. Citizen science records were noted for very few species of concern with only two records indicating the occurrence of two species in natural or semi-natural areas. This research constitutes one of few studies that have applied a horizon scanning approach using horticultural catalogues to identify alien species, and highlights the efficiency of this approach as a tool for the early detection of potentially invasive species.

Adaptive Deep Brain Stimulation for the Treatment of Parkinson Disease and Essential Tremor

Horizon Scan reports provide brief summaries of information regarding new and emerging health technologies; Heath Technology Update articles typically focus on a single device or intervention. These technologies are identified through the CADTH Horizon Scanning Service as topics of potential interest to health care decision-makers in Canada. This Horizon Scan summarizes the available information regarding an emerging technology, Percept PC Deep Brain Stimulation (DBS) system with BrainSense technology, for the treatment of Parkinson disease and essential tremors.

OP218 Searching Preprint Repositories For COVID-19 Therapeutics Using A Semi-Automated Text-Mining Tool

IntroductionThe COVID-19 pandemic led to a significant surge in clinical research activities in the search for effective and safe treatments. Attempting to disseminate early findings from clinical trials in a bid to accelerate patient access to promising treatments, a rise in the use of preprint repositories was observed. In the UK, NIHR Innovation Observatory (NIHRIO) provided primary horizon-scanning intelligence on global trials to a multi-agency initiative on COVID-19 therapeutics. This intelligence included signals from preliminary results to support the selection, prioritisation and access to promising medicines.MethodsA semi-automated text mining tool in Python3 used trial IDs (identifiers) of ongoing and completed studies selected from major clinical trial registries according to pre-determined criteria. Two sources, BioRxiv and MedRxiv are searched using the IDs as search criteria. Weekly, the tool automatically searches, de-duplicates, excludes reviews, and extracts title, authors, publication date, URL and DOI. The output produced is verified by two reviewers that manually screen and exclude studies that do not report results.ResultsA total of 36,771 publications were uploaded to BioRxiv and MedRxiv between March 3 and November 9 2020. Approximately 20–30 COVID-19 preprints per week were pre-selected by the tool. After manual screening and selection, a total of 123 preprints reporting clinical trial preliminary results were included. Additionally, 50 preprints that presented results of other study types on new vaccines and repurposed medicines for COVID-19 were also reported.ConclusionsUsing text mining for identification of clinical trial preliminary results proved an efficient approach to deal with the great volume of information. Semi-automation of searching increased efficiency allowing the reviewers to focus on relevant papers. More consistency in reporting of trial IDs would support automation. A comparison of accuracy of the tool on screening titles/abstract or full papers may help to support further refinement and increase efficiency gains.This project is funded by the NIHR [(HSRIC-2016-10009)/Innovation Observatory]. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Beyond the MAA-Y90 Paradigm: The Evolution of Radioembolization Dosimetry Approaches and Scout Particles

Radioembolization is a well-established treatment for primary and metastatic liver cancer. There is increasing interest in personalized treatment planning supported by dosimetry, as it provides an opportunity to optimize dose delivery to tumor and minimize nontarget deposition, which demonstrably increases the efficacy and safety of this therapy. However, the optimal dosimetry procedure in the radioembolization setting is still evolving; existing data are limited as few trials have prospectively tailored dose based on personalized planning and predominantly semi-empirical methods are used for dose calculation. Since the pretreatment or “scout” procedure forms the basis of dosimetry calculations, an accurate and reliable technique is essential. 99mTc-MAA SPECT constitutes the current accepted standard for pretreatment imaging; however, inconsistent patterns in published data raise the question whether this is the optimal agent. Alternative particles are now being introduced to the market, and early indications suggest use of an identical scout and treatment particle may be superior to the current standard. This review will undertake an evaluation of the increasingly refined dosimetric methods driving radioembolization practices, and a horizon scanning exercise identifying alternative scout particle solutions. Together these constitute a compelling vision for future treatment planning methods that prioritize individualized care.

PHYTO-THREATS: Addressing Threats to UK Forests and Woodlands from Phytophthora; Identifying Risks of Spread in Trade and Methods for Mitigation

The multidisciplinary ‘Phyto-threats’ project was initiated in 2016 to address the increasing risks to UK forest and woodland ecosystems from trade-disseminated Phytophthora. A major component of this project was to examine the risk of Phytophthora spread through nursery and trade practices. Close to 4000 water and root samples were collected from plant nurseries located across the UK over a three-year period. Approximately half of the samples tested positive for Phytophthora DNA using a metabarcoding approach with 63 Phytophthora species identified across nurseries, including quarantine-regulated pathogens and species not previously reported in the UK. Phytophthora diversity within nurseries was linked to high-risk management practices such as use of open rather than closed water sources. Analyses of global Phytophthora risks identified biological traits and trade pathways that explained global spread and host range, and which may be of value for horizon-scanning. Phytophthoras having a higher oospore wall index and faster growth rates had wider host ranges, whereas cold-tolerant species had broader geographic and latitudinal ranges. Annual workshops revealed how stakeholder and sector ‘appetite’ for nursery accreditation increased over three years, although an exploratory cost-benefit analysis indicated that the predicted benefits of introducing best practice expected by nurseries outweigh their costs only when a wider range of pests and diseases (for example, Xylella) is considered. However, scenario analyses demonstrated the significant potential carbon costs to society from the introduction and spread of a new tree-infecting Phytophthora: Thus, the overall net benefit to society from nurseries adopting best practice could be substantial.

Study on Horizon Scanning by Citation Network Analysis and Text Mining: A Focus on Drug Development Related to T Cell Immune Response

Certain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.

Study on Horizon Scanning with a Focus on the Development of AI-Based Medical Products: Citation Network Analysis

Horizon scanning for innovative technologies that might be applied to medical products and requires new assessment approaches to prepare regulators, allowing earlier access to the product for patients and an improved benefit/risk ratio. The purpose of this study is to confirm that citation network analysis and text mining for bibliographic information analysis can be used for horizon scanning of the rapidly developing field of AI-based medical technologies and extract the latest research trend information from the field. We classified 119,553 publications obtained from SCI constructed with the keywords “conventional,” “machine-learning,” or “deep-learning" and grouped them into 36 clusters, which demonstrated the academic landscape of AI applications. We also confirmed that one or two close clusters included the key articles on AI-based medical image analysis, suggesting that clusters specific to the technology were appropriately formed. Significant research progress could be detected as a quick increase in constituent papers and the number of citations of hub papers in the cluster. Then we tracked recent research trends by re-analyzing “young” clusters based on the average publication year of the constituent papers of each cluster. The latest topics in AI-based medical technologies include electrocardiograms and electroencephalograms (ECG/EEG), human activity recognition, natural language processing of clinical records, and drug discovery. We could detect rapid increase in research activity of AI-based ECG/EEG a few years prior to the issuance of the draft guidance by US-FDA. Our study showed that a citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of rapidly developing AI-based medical technologies.

Assessment of the Spatial Invasion Risk of Intentionally Introduced Alien Plant Species (IIAPS) under Environmental Change in South Korea

Predicting the regions at risk of invasion from IIAPS is an integral horizon-scanning activity that plays a crucial role in preventing, controlling, and eradicating invasive species. Here, we quantify the spatial distribution area and invasion risk of IIAPS using a species distribution model under different levels of environmental change in South Korea. From the model predictions, the current average spatial extent of the 10 IIAPS is 33,948 km2, and the individual spatial extents are estimated to change by −7% to 150% by 2050 and by −9% to 156% by 2070. The spatial invasion risk assessment shows that, currently, moderate-to-high invasion risk is limited to coastal areas and densely populated metropolitan cities (e.g., Seoul, Busan, and Gwangju), but that the area with this level of risk is expected to spread toward the central and northern regions of the country in the future, covering 86.21% of the total area of the country by 2070. These results demonstrate that the risk of invasion by IIAPS is estimated to enlarge across the whole country under future environmental changes. The modeling system provided in this study may contribute to the initial control and strategic management of IIAPS to maintain the dynamic ecosystems of South Korea.