Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development

Abstract

<b><i>Introduction:</i></b> The SARS-CoV-2 pandemic has led to one of the most critical and boundless waves of publications in the history of modern science. The necessity to find and pursue relevant information and quantify its quality is broadly acknowledged. Modern information retrieval techniques combined with artificial intelligence (AI) appear as one of the key strategies for COVID-19 living evidence management. Nevertheless, most AI projects that retrieve COVID-19 literature still require manual tasks. <b><i>Methods:</i></b> In this context, we pre­sent a novel, automated search platform, called Risklick AI, which aims to automatically gather COVID-19 scientific evidence and enables scientists, policy makers, and healthcare professionals to find the most relevant information tailored to their question of interest in real time. <b><i>Results:</i></b> Here, we compare the capacity of Risklick AI to find COVID-19-related clinical trials and scientific publications in comparison with clinicaltrials.gov and PubMed in the field of pharmacology and clinical intervention. <b><i>Discussion:</i></b> The results demonstrate that Risklick AI is able to find COVID-19 references more effectively, both in terms of precision and recall, compared to the baseline platforms. Hence, Risklick AI could become a useful alternative assistant to scientists fighting the COVID-19 pandemic.

Information Retrieval in an Infodemic: The Case of COVID-19 Publications

“…The efficient literature discovery process fostered by our methods may lead to faster publication cycles when required, for example reducing from weeks to days the drafting time of COVID-19 reviews [ 58 ], but also to less costly creation of curated living evidence portals, which will inform clinicians and public health officers with the best available evidence [ 59 ]. Indeed, as shown in [ 27 , 60 ], these methodologies outperform commercially available tools for searching and discovering COVID-19–related literature. Moreover, as they are data-driven, it is expected that they can be extrapolated to other types of corpora, such as clinical trial protocols and biomedical metadata datasets [ 60 , 61 ], enabling thus a more comprehensive identification of scientific evidence.…”

“…Indeed, as shown in [ 27 , 60 ], these methodologies outperform commercially available tools for searching and discovering COVID-19–related literature. Moreover, as they are data-driven, it is expected that they can be extrapolated to other types of corpora, such as clinical trial protocols and biomedical metadata datasets [ 60 , 61 ], enabling thus a more comprehensive identification of scientific evidence. Equally important, as the COVID-19 infodemic is not the first and unlikely the last [ 62 , 63 ], our methodology and findings could be extended to help tackling future epi-, pan-, and infodemics by supporting relevant actors to scan large and fast-changing collections to create timely reviews and curated evidence and apply localized infodemic management approaches.…”

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“…The COVID-19 pandemic revealed the necessity for accelerated vaccine development worldwide (3,7). In this critical context, we performed a risk analysis on the different vaccine technologies proposed by the manufacturers against COVID-19 in the early months of 2020 by using the AI-based search engine Risklick (12,13). We graded seven different risks across seven different vaccine technologies by using a Probability and Impact Matrix (as illustrated in Supplementary Figure 1, for the risks linked to safety for each vaccine).…”

“…The Risklick AI collects and updates clinical trial data from a wide variety of sources such as the Clinical Trials Registr and datasets from the WHO each day. The metadata related to the publications are acquired from 14 international sources [BioRxiv; MedRxiv; Medline; Embase; Pubmed; Cinahl; Web of Science; Scopus; Cochrane; the International Clinical Trials Registry Platform (ICTRP); Dimensions; Living Evidence; Kaggle Cord-19 Dataset; and Google Scholar] allowing superior search performance relative to other acknowledged scientific publications search engines (12,13). The Risklick AI is able to find and process COVID-19 references more effectively in terms of precision, F1 score, and recall, compared to the baseline platforms.…”

“…Hence, we analyzed the risks of the different technologies to produce the vaccines proposed by the pharmaceutical companies providing vaccines against COVID-19. This analysis was performed using scientific publications from early 2020 and utilizing the artificial intelligence (AI)-based search engine Risklick (12,13). By calculating the risk score using a Probability and Impact Matrix and a semi-automated AI interface, we estimated the major risks faced by the pharmaceutical companies providing the vaccines.…”