Toolkit for emerging technologies in laboratory medicine.

An emerging technology (ET) for laboratory medicine can be defined as an analytical method (including biomarkers) or device (software, applications, and algorithms) that by its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics. Considering the laboratory medicine-specific definition, this document examines eight key tools, encompassing clinical, analytical, operational, and financial aspects, used throughout the life cycle of ET implementation. The tools provide a systematic approach starting with identifying the unmet need or identifying opportunities for improvement (Tool 1), forecasting (Tool 2), technology readiness assessment (Tool 3), health technology assessment (Tool 4), organizational impact map (Tool 5), change management (Tool 6), total pathway to method evaluation checklist (Tool 7), and green procurement (Tool 8). Whilst there are differences in clinical priorities between different settings, the use of this set of tools will help support the overall quality and sustainability of the emerging technology implementation.

Emerging technology: a definition for laboratory medicine.

The term "emerging technology" (ET) is used extensively, and there are numerous definitions offered, but to our knowledge, none specifically encompass the field of laboratory medicine. An ET definition that incorporates the overarching IFCC aim of "Advancing excellence in laboratory medicine to support healthcare worldwide" would clarify discussions. We discuss key aspects of the term "emerging technology(ies)" as it applies to laboratory medicine with a view to laying the foundations for a practical definition for the profession and propose the definition of an ET as "An analytical method or device that by virtue of its stage of development, translation into broad routine clinical practice, or geographical adoption and implementation has the potential to add value to clinical diagnostics".

Trends in dermatology eponyms.

Background: Eponyms are ubiquitous in dermatology; however, their usage trends have not been studied. Objective: To characterize the usage of eponyms in dermatology from 1880 to 2020. Methods: Candidate eponyms were collected from a textbook and an online resource. A subset of these eponyms was deemed to be dermatology-focused by a panel of experienced dermatologists. Python scripts were used to permute eponyms into multiple variations and automatically search PubMed using BioPython's Entrez library. Results: The dermatologist panel designated 373 of 529 candidate eponyms as dermatology-focused. These eponyms were permuted into 3159 variations and searched in PubMed. The highest occurring dermatology-focused eponyms (DFEs) in the year 2020 included Leishmania, Behçet syndrome, Kaposi sarcoma, Langerhans cell histiocytosis, and Mohs surgery. Increased DFE usage in the general medical literature parallels the overall increase in the use of other eponyms in the medical literature. However, in the most cited dermatology journals, DFE usage did not increase in the past decade. There were several eponyms with decreased usage. Limitations: This study is limited to the publications in PubMed; only titles and abstracts could be queried. Conclusion: DFEs are increasing in usage in the general medical literature, but the usage of eponyms in the most cited dermatology journals has plateaued.

A Biopython-based method for comprehensively searching for eponyms in Pubmed.

Eponyms are common in medicine; however, their usage has varied between specialties and over time. A search of specific eponyms will reveal the frequency of usage within a medical specialty. While usage of eponyms can be studied by searching PubMed, manual searching can be time-consuming. As an alternative, we modified an existing Biopython method for searching PubMed. In this method, a list of disease eponyms is first manually collected in an Excel file. A Python script then creates permutations of the eponyms that might exist in the cited literature. These permutations include possessives (e.g., 's) as well as various forms of combining multiple surnames. PubMed is then automatically searched for this permutated library of eponyms, and duplicate citations are removed. The final output file may then be sorted and enumerated by all the data fields which exist in PubMed. This method will enable rapid searching and characterization of eponyms for any specialty of medicine. This method is agnostic to the type of terms searched and can be generally applied to the medical literature including non-eponymous terms such as gene names and chemical compounds.•Custom Python scripts using Biopython's Bio.Entrez module automate the search for medical eponyms.•This method can be more broadly used to search for any set of terms existing in PubMed.

Dry Reagent Tests in the 1880s-Dr Pavy's Pellets and Dr Oliver's Papers.

BACKGROUND: In the 1880s, concern over the inconvenience of hazardous chemical solutions used for bedside urinalysis sparked an interest in the development of dry reagents for a range of common urine tests. CONTENT: This article examines the history of Dr Pavy's Pellets and Dr Oliver's Papers, 2 different dry reagent systems developed in the 1880s for bedside urine testing. It sets these developments in the context of the earlier dry chemistry work (e.g., indicator papers) and the subsequent work that led to modern day reagent tablets and dipstick devices. SUMMARY: Tests based on dry reagents can be traced back to the 1st century, but active development, in the form of indicator papers, dates from the 1600s. In the 1880s, spurred by dissatisfaction with liquid-based bedside urine testing among clinicians, Dr Frederick William Pavy and Dr George Oliver developed dry reagent tests, based on pellets (Dr Pavy's Pellets) and chemically impregnated papers (Dr Oliver's Papers) for urine sugar and urine albumin. These reagents were commercialized by a number of companies and provided in convenient cases (Physician's Pocket Reagent Case). Eventually, these tests lost popularity and were replaced by the type of tablets and dipsticks developed by both Eli Lilly, and the Ames Division of Miles Laboratories (subsequently Bayer, and currently Siemens Healthineers) during the 1940s and 1950s.

Eponyms in clinical chemistry.

BACKGROUND: Eponyms are commonly used in medicine, but there are no specific studies of the use of eponyms in clinical chemistry. METHODS: Clinical chemistry eponyms were manually collected from books, review articles and journal articles from 1847 through 2020. Eponym usage was examined by searching titles and abstracts in PubMed. Custom Python scripts were used to first permute eponyms into multiple forms, and then to search PubMed using Biopython. The eponyms identified in PubMed were further focused on 2 clinical chemistry journals Clinica Chimica Acta [CCA] and Clinical Chemistry [CCJ]. RESULTS: The manual collection identified >300 eponyms in clinical chemistry. The Biopython search of PubMed identified a subset of 97 unique eponyms in 33,232 articles. PubMed identified 26 eponyms used in 130 CCA articles; whereas a full-text search identified 1187 articles. In comparison, PubMed identified 36 eponyms used in 158 CCJ articles; whereas a full-text CCJ search identified 708 articles. PubMed shows that the journals CCA and CCJ had a peak number of eponym citations in 1977 followed by a steady decline. CONCLUSIONS: Eponyms have been frequently used in clinical chemistry with 97 eponyms in common use in PubMed. Overall, the use of clinical chemistry eponyms appears to be declining.

Artificial Intelligence-Powered Search Tools and Resources in the Fight Against COVID-19.

Emerging technologies are set to play an important role in our response to the COVID-19 pandemic. This paper explores three prominent initiatives: COVID-19 focused datasets (e.g., CORD-19); Artificial intelligence-powered search tools (e.g., WellAI, SciSight); and contact tracing based on mobile communication technology. We believe that increasing awareness of these tools will be important in future research into the disease, COVID-19, and the virus, SARS-CoV-2.

Key questions about the future of laboratory medicine in the next decade of the 21st century: A report from the IFCC-Emerging Technologies Division.

This review advances the discussion about the future of laboratory medicine in the 2020s. In five major topic areas: 1. the "big picture" of healthcare; 2. pre-analytical factors; 3. Analytical factors; 4. post-analytical factors; and 5. relationships, which explores a next decade perspective on laboratory medicine and the likely impact of the predicted changes by means of a number of carefully focused questions that draw upon predictions made since 2013. The "big picture" of healthcare explores the effects of changing patient populations, the brain-to-brain loop, direct access testing, robots and total laboratory automation, and green technologies and sustainability. The pre-analytical section considers the role of different sample types, drones, and biobanks. The analytical section examines advances in point-of-care testing, mass spectrometry, genomics, gene and immunotherapy, 3D-printing, and total laboratory quality. The post-analytical section discusses the value of laboratory medicine, the emerging role of artificial intelligence, the management and interpretation of omics data, and common reference intervals and decision limits. Finally, the relationships section explores the role of laboratory medicine scientific societies, the educational needs of laboratory professionals, communication, the relationship between laboratory professionals and clinicians, laboratory medicine financing, and the anticipated economic opportunities and outcomes in the 2020's.

History of disruptions in laboratory medicine: what have we learned from predictions?

Predictions about the future of laboratory medicine have had a mixed success, and in some instances they have been overambitious and incorrectly assessed the future impact of emerging technologies. Current predictions suggest a more highly automated and connected future for diagnostic testing. The central laboratory of the future may be dominated by more robotics and more connectivity in order to take advantage of the benefits of the Internet of Things and artificial intelligence (AI)-based systems (e.g. decision support software and imaging analytics). For point-of-care testing, mobile health (mHealth) may be in the ascendancy driven by healthcare initiatives from technology companies such as Amazon, Apple, Facebook, Google, IBM, Microsoft and Uber.

Current and Emerging Trends in Point-of-Care Technology and Strategies for Clinical Validation and Implementation.

BACKGROUND: Point-of-care technology (POCT) provides actionable information at the site of care to allow rapid clinical decision-making. With healthcare emphasis shifting toward precision medicine, population health, and chronic disease management, the potential impact of POCT continues to grow, and several prominent POCT trends have emerged or strengthened in the last decade. CONTENT: This review summarizes current and emerging trends in POCT, including technologies approved or cleared by the Food and Drug Administration or in development. Technologies included have either impacted existing clinical diagnostics applications (e.g., continuous monitoring and targeted nucleic acid testing) or are likely to impact diagnostics delivery in the near future. The focus is limited to in vitro diagnostics applications, although in some sections, technologies beyond in vitro diagnostics are also included given the commonalities (e.g., ultrasound plug-ins for smart phones). For technologies in development (e.g., wearables, noninvasive testing, mass spectrometry and nuclear magnetic resonance, paper-based diagnostics, nanopore-based devices, and digital microfluidics), we also discuss their potential clinical applications and provide perspectives on strategies beyond technological and analytical proof of concept, with the end goal of clinical implementation and impact. SUMMARY: The field of POCT has witnessed strong growth over the past decade, as evidenced by new clinical or consumer products or research and development directions. Combined with the appropriate strategies for clinical needs assessment, validation, and implementation, these and future POCTs may significantly impact care delivery and associated outcomes and costs.

Chemiluminescence.

Radioactive reagents have been gradually replaced by nonisotopic reagents for some tasks in molecular biology. Concern over laboratory safety and the economic and environmental aspects of radioactive waste disposal have been key factors in this change. Generally, the new nonisotopic systems have improved in terms of analytical sensitivity and the time required to obtain a result. The most prominent nonisotopic analytical methods exploit chemiluminescence, described here. This technique has been particularly effective when used in combination with an enzyme label, so that the amplifying properties of an enzyme label and the high sensitivity of a chemiluminescent detection reaction are combined to produce an ultrasensitive assay (e.g., chemiluminescent detection of peroxidase- and alkaline phosphatase-labeled proteins and nucleic acid probes). In all of the commonly used applications in molecular biology, the analytical performance of the chemiluminescent systems approaches that of 125I- or 32P-based systems. Chemiluminescent systems also avoid the lengthy signal detection times required with 32P-based methods, yielding results in minutes rather than days. In addition, chemiluminescent probes can be easily stripped from membranes, allowing the membranes to be reprobed many times without significant loss of resolution. Experimental protocols for directly attaching nonisotopic labels to nucleic acids and indirect labeling methods based on biotin, fluorescein, and digoxigenin labels are now well established. The ancillary reagents (e.g., avidin, streptavidin, antidigoxigenin, and antifluorescein enzyme conjugates) required for the indirect methods are widely available.

Nanostructured luminescently labeled nucleic acids.

Important and emerging trends at the interface of luminescence, nucleic acids and nanotechnology are: (i) the conventional luminescence labeling of nucleic acid nanostructures (e.g. DNA tetrahedron); (ii) the labeling of bulk nucleic acids (e.g. single-stranded DNA, double-stranded DNA) with nanostructured luminescent labels (e.g. copper nanoclusters); and (iii) the labeling of nucleic acid nanostructures (e.g. origami DNA) with nanostructured luminescent labels (e.g. silver nanoclusters). This review surveys recent advances in these three different approaches to the generation of nanostructured luminescently labeled nucleic acids, and includes both direct and indirect labeling methods.