Screening Technologies Research Articles

Making a Difference from Day One: The Urgent Need for Universal Neonatal Hearing Screening

Neonatal hearing screening (NHS) is a critical public health measure for early identification of hearing loss, ensuring timely access to interventions that can dramatically improve a child’s language development, cognitive abilities, and social inclusion. Beyond clinical benefits, NHS provides long-term advantages in education and quality of life. Given that congenital hearing loss affects approximately 1–2 in every 1000 newborns worldwide, the case for universal screening is clear. Countries like the United States and Australia have successfully implemented NHS, leading to earlier diagnoses, improved language development, and better educational outcomes. In Europe, while many nations have adopted NHS, consistency remains a challenge. Countries such as Norway and the United Kingdom stand out for their well-established systems, whereas others, like Greece, have made notable progress but have yet to mandate NHS nationwide. This highlights the need for cohesive national policies across Europe to ensure universal coverage. Screening methods such as Transient Evoked Otoacoustic Emissions (TEOAE) and Automated Auditory Brainstem Response (AABR) are established tools for detecting hearing impairments in neonates. Despite their demonstrated efficacy, NHS remains inconsistent globally, particularly in low- and middle-income regions that lack mandatory policies or access to reliable screening technologies. This perspective advocates for the urgent need to make NHS mandatory in all countries, emphasizing its societal benefits and cost-effectiveness. Early diagnosis supports prompt intervention, like hearing aids or cochlear implants, which are most effective when implemented before six months. It also empowers families to make informed decisions, fosters educational inclusion, and mitigates the social and emotional challenges of undiagnosed hearing loss. Policymakers, healthcare providers, and international organizations must prioritize universal NHS to ensure no child is left behind due to unaddressed hearing loss.

A machine learning based framework for breast cancer prediction using biomarkers

<p>Breast cancer is the most frequent cancer in women and the second-leading cause of cancer-related deaths globally. The main problems in managing breast cancer are high heterogeneity and the formation of therapeutic resistance. White blood cells, omics and large Wisconsin diagnostic breast cancer datasets present the three-decade genomic revolution and advance the understanding of cellular function. The precision of cancer diagnosis has also increased over the past decades. High throughput sequencing, screening, and artificial intelligence technologies have significantly improved and increased the methodologies used for diagnosis, prognosis, and therapy. This paper follows several phases of breast cancer, studies datasets and evaluate many algorithms of machine learning (ML) used for analysis and feature selection i.e. k-means, similarity correlation, genetic algorithm, and principal component analysis, have been used to recognize the subset of proteins with the highest significance for breast cancer prediction by using different biomarkers. The best correlation, as determined by Pearson correlation, between copy number and protein is 0.014, and the accuracy achieved by the genetic algorithm is 93.5% using multi-omics datasets.</p>

Risk beyond the pap: A review of key epidemiological studies on cervical cancer risk factors and populations at highest risk

Cervical cancer remains a significant public health concern, with notable mortality rates worldwide despite advancements in screening technologies such as the Pap smear. While screening has substantially reduced the disease's incidence, understanding risk factors that extend beyond regular screening practices is essential for comprehensive cervical cancer prevention. This review synthesizes key epidemiological studies focused on the various biological, lifestyle, and demographic factors influencing cervical cancer risk, thereby identifying the populations at the highest risk. The methodology encompasses rigorous selection criteria, including studies from renowned databases such as PubMed and Scopus, and evaluates the strengths and limitations of common epidemiological study designs like case-control and cohort studies. The review categorizes risk factors into four primary areas: HPV infection, smoking, sexual behavior and contraceptive use, and genetic predisposition, each substantiated by evidence from recent epidemiological research. Additionally, it assesses populations facing elevated risk, such as those influenced by socioeconomic, geographic, and ethnic disparities, as well as immunocompromised and age-defined groups, to outline how these variables affect cervical cancer susceptibility. The findings underscore persistent disparities in cervical cancer incidence, especially among underserved and minority populations, where access to healthcare and awareness of risk factors remain limited. This review emphasizes the importance of addressing these disparities through targeted public health policies and enhanced screening protocols. Finally, the paper recommends future research directions, highlighting the need for longitudinal and multi-population studies to better understand the complex interplay of risk factors. Insights from this review can inform public health initiatives and shape preventative measures that extend beyond screening to reduce cervical cancer risk across vulnerable populations.

Study on the Relationship between Secondary Metabolites and Resistance to Anthracnose in Stylosanthes

Stylosanthes is an excellent tropical leguminous forage. Anthracnose caused by Colletotrichum gloeosporioides is a major limiting factor in Stylosanthes production, which can lead to reduced forage and seed production and decreased quality. How to quickly screen resistant parents and varieties of Stylosanthes that are resistant to anthracnose has become an urgent problem to be solved in production. In this study, the high-performance liquid chromatography detection technology was established for simultaneous analysis of the content of salicylic acid, triethyl orthobenzoate, indazole, and soyasapogenol B in Stylosanthes leaves. The technology was further applied in the analysis of the relationship between secondary metabolites and resistance to anthracnose in 105 accessions of Stylosanthes. The result shows that salicylic acid is the most important factor for resistance to anthracnose. By detecting the content of salicylic acid in Stylosanthes leaves, a rapid screening technology for anthracnose-resistant parents and varieties of Stylosanthes was established, and 5 accessions of Stylosanthes with high resistance to anthracnose were screened. This study is of great significance to the Stylosanthes germplasm preservation and identification and its breeding.

Is 26S proteasome non-ATPase regulatory subunit 6 a potential molecular target for intrahepatic cholangiocarcinoma?

In this editorial we comment on the article by Tang et al published in the recent issue of World Journal of Hepatology . Drug therapy of intrahepatic cholangiocarcinoma (iCCA) poses an enormous challenge since only a small proportion of patients demonstrate beneficial responses to therapeutic agents. Thus, there has been a sustained search for novel molecular targets for iCCA. The study by Tang et al evaluated the role of 26S proteasome non-ATPase regulatory subunit 6 (PSMD6), a 19S regulatory subunit of the proteasome, in human iCCA cells and specimens. The authors employed clustered regularly interspaced short palindromic repeat (CRISPR) knockout screening technology integrated with the computational CERES algorithm, and analyzed the human protein atlas (THPA) database and tissue microarrays. The results show that PSMD6 is a gene essential for the proliferation of 17 iCCA cell lines, and PSMD6 protein was overexpressed in iCCA tissues without a significant correlation with the clinicopathological parameters. The authors conclude that PSMD6 may play a promoting role in iCCA. The major limitations and defects of this study are the lack of detailed information of CRISPR knockout screening, in vivo experiments, and a discussion of plausible mechanistic cues, which, therefore, dampen the significance of the results. Further studies are required to verify PSMD6 as a molecular target for developing novel therapeutics for iCCA. In addition, the editorial article summarizes the latest advances in molecular targeted drugs and recently emerging immunotherapy in the clinical management of iCCA, development of proteasome inhibitors for cancer therapy, and advantages of CRISPR screening technology, computational methods, and THPA database as experimental tools for fighting cancer. We hope that these comments may provide some clues for those engaged in the field of basic and clinical research into iCCA.

Overexpression of proteasome 26S subunit non-ATPase 6 protein and its clinicopathological significance in intrahepatic cholangiocarcinoma

BACKGROUND Currently, intrahepatic cholangiocarcinoma (ICC) poses a continuing, significant health challenge, but the relationship has yet to be established between ICC and the proteasome 26S subunit non-ATPase 6 (PSMD6). AIM To investigate the protein expression and clinicopathological significance of PSMD6 in ICC. METHODS The potential impact of the PSMD6 gene on the growth of ICC cell lines was analyzed using clustered regularly interspaced short palindromic repeat knockout screening technology. Forty-two paired specimens of ICC and adjacent non-cancerous tissues were collected. PSMD6 protein expression was determined by immunohistochemistry. Receiver operating characteristic curve analysis was performed to validate PSMD6 expression level, and its association with ICC patients’ various clinicopathological characteristics was investigated. RESULTS The PSMD6 gene was found to be essential for the growth of ICC cell lines. PSMD6 protein was significantly overexpressed in ICC tissues (P < 0.001), but showed no significant association with patient age, gender, pathological grade, or tumor-node-metastasis stage (P > 0.05). CONCLUSION PSMD6 can promote the growth of ICC cells, thus playing a pro-oncogenic role.

Deep Learning AI for DR Microaneurysm Screening Based on Fundus Images

Abstract. Since 2014, Artificial Intelligence (AI) image detection has developed rapidly in the medical field, while the global incidence of diabetes has increased rapidly. As an early sign of diabetic retinopathy (DR), the detection of diabetic microaneurysms is particularly important for the prevention and treatment of diabetes. Therefore, the artificial intelligence exhibition of DR microaneurysm screening based on fundus images shows great potential in this regard. This paper reviews the research progress of artificial intelligence technology for DR microangioma screening based on fundus images in recent years, and focuses on the improvement measures taken for different depth learning methods. These improvement measures aim to optimize model performance, improve training efficiency and enhance the generalization ability of the model. Some model experimental results are compared and analyzed in order to get the best model in a specific dataset or result. Finally, the current challenges are discussed and suggestions for the development of this field are put forward.

Global Trends and Hotspots in Non-Targeted Screening of Water Pollution Research: Bibliometric and Visual Analysis

Non-targeted screening (NTS) technology has been showing significant potential in identifying contaminants of emerging concern (CECs) in water and has attracted great attention in academia in recent years. It is a method that analyzes samples without pre-selecting substances, enabling the detection and identification of unknown compounds, which is crucial for environmental health and public protection. This study uses the Bibliometrix package in R 4.4.1 and CiteSpace 6.3.R1 software to statistically analyze 589 relevant publications from the Web of Science Core Collection from 2007 to 2024. Our work concentrates on NTS of water bodies; thus, articles that only analyze water sediments without analyzing the water were not considered for inclusion. By conducting a quantitative analysis and visualizing the publication trends, countries, authors, journals, and keywords, the present study identifies research hotspots, compositions, and paradigms within this field, trying to analyze the horizontal and vertical development trends and structural evolution of the research area. The research found that the application of NTS in water pollution studies has progressed through three phases: theoretical exploration, rapid development, and steady progress. From the national level, China leads with the highest number of publications (131), followed by Germany (105), Spain (50), and the United States (39). The top three authors by publication volume are J. Hollender, Nikolaos S. Thomaidis, and Emma L. Schymanski, while the top three by citation count are J. Hollender, Emma L. Schymanski, and M. Krauss. However, international collaboration between countries and researchers still remains an area for improvement. Science of the Total Environment is the journal with the highest number of publications (81), and Environmental Science & Technology holds the highest number of citations. Research on NTS methodologies, suspect screening, and health risk assessments are hot topics in the academic community. Future research is expected to be multidisciplinary, with emerging hotspots likely to focus on including the identification of novel pollutants through NTS, toxicity assessments of biotransformed compounds, and the health impacts and mechanisms of related compounds.

Enhancing the erythritol production of Yarrowia lipolytica by high-throughput screening based on highly sensitive artificial sensor and anchor protein cwp2.

Yarrowia lipolytica is widely used for the industrial production of the natural sweetener erythritol. Despite improvements in fermentation process control and metabolic pathway regulation, bottlenecks still exist in terms of yield and screening technology. Therefore, we constructed an artificial sensor system for effective erythritol detection, established a single-cell droplet-based high-throughput screening system based on fluorescence-activated cell sorting, and obtained Y. lipolytica with improved erythritol production through mutagenesis and high-throughput screening. We used a droplet generator to co-cultivate Y. lipolytica 5-14 with Escherichia coli and used the E. coli fluorescent signal to detect the concentration of erythritol synthesized by Y. lipolytica 5-14 for high-throughput screening. Strains were subjected to UV mutagenesis for 120 s. Under optimized fermentation conditions using Y. lipolytica mutants in 96-well plates, the screening efficiency reached 16.7%. Y. lipolytica 5-14-E6 showed a 21% increase in erythritol to 109.84 g/L. After fermentation at 30°C in a 100 m3 fermenter for 75 h, the mutant Y. lipolytica 5-14-E6 erythritol yield reached 178 g/L.

FinTech vs. Bank: The impact of lending technology on credit market competition

Does the recent proliferation of technology in lending process have an impact on business loan market competition? Using a theoretical model that assumes heterogeneity in lenders’ screening abilities and borrowers’ investment horizons, we show that FinTech (Traditional) lenders primarily supply unsecured (asset-backed) loans to borrowers with short-term (long-term) projects. The model builds on the interplay between screening ability and collateral requirements to characterize the competition between two ex-ante symmetric lenders. Lenders use screening technology and collateral requirements to mitigate competition and restrict the supply of credit through an endogenous segmentation of the loan market. As information technology improves, the effect on credit supply and equilibrium interest rates becomes more nuanced and depends on the market segment. The results offer a supply-side explanation for the growth of unsecured lending.

Comparative Genomics and Epigenomics of Transcriptional Regulation.

Transcriptional regulation in response to diverse physiological cues involves complicated biological processes. Recent initiatives that leverage whole genome sequencing and annotation of regulatory elements significantly contribute to our understanding of transcriptional gene regulation. Advances in the data sets available for comparative genomics and epigenomics can identify evolutionarily constrained regulatory variants and shed light on noncoding elements that influence transcription in different tissues and developmental stages across species. Most epigenomic data, however, are generated from healthy subjects at specific developmental stages. To bridge the genotype-phenotype gap, future research should focus on generating multidimensional epigenomic data under diverse physiological conditions. Farm animal species offer advantages in terms of feasibility, cost, and experimental design for such integrative analyses in comparison to humans. Deep learning modeling and cutting-edge technologies in sequencing and functional screening and validation also provide great promise for better understanding transcriptional regulation in this dynamic field.

Development of an Electrochemical Paper-Based Device Modified with Functionalized Biochar for the Screening of Paracetamol in Substandard Medicines.

The global prevalence of counterfeit and low-quality pharmaceuticals poses significant health risks and challenges in medical treatments, creating a need for rapid and reliable drug screening technologies. This study introduces a cost-effective electrochemical paper-based device (ePAD) modified with functionalized bamboo-derived biochar (BCF) for the detection of paracetamol in substandard medicines. The sensor was fabricated using a custom 3D-printed stencil in PLA, designed for efficient production, and a 60:40 (m/m) graphite (GR) and glass varnish (GV) conductive ink, resulting in a robust and sensitive platform. The electroactive area of the ePAD/BCF sensor was determined as 0.37 cm2. Characterization via SEM and cyclic voltammetry (CV) verified its structural and electrochemical stability. The sensor demonstrated linear detection of paracetamol from 5.0 to 60.0 µmol L-1 with a detection limit of 3.50 µmol L-1. Interference studies showed high selectivity, with recoveries of over 90%, and the sensor successfully quantified paracetamol in commercial analgesic and anti-flu samples. This sustainable, bamboo-based ePAD offers a promising solution for rapid on-site pharmaceutical quality control, with significant potential to enhance drug screening accuracy.

Single-cell encoded gene silencing for high-throughput combinatorial siRNA screening.

The use of combinatorial siRNAs shows great promise for drug discovery, but the identification of safe and effective siRNA combinations remains challenging. Here, we develop a massively multiplexed technology for systematic screening of siRNA-based cocktail therapeutics. We employ composite micro-carriers that are responsive to near infrared light and magnetic field to achieve photoporation-facilitated siRNA transfection to individual cells. Thus, randomized gene silencing by different siRNA formulations can be performed with high-throughput single-cell-based analyses. For screening anti-cancer siRNA cocktails, we test more than 1300 siRNA combinations for knocking down multiple genes related to tumor growth, discovering effective 3-siRNA formulations with an emphasis on the critical role of inhibiting Cyclin D1 and survivin, along with their complementary targets for synergic efficacy. This approach enables orders of magnitude reduction in time and cost associated with largescale siRNA screening, and resolves key insights to siRNA pharmacology that are not permissive to existing methods.

Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy.

It is imperative to comprehend the mechanisms that underlie drug toxicity in order to enhance the efficacy and safety of novel therapeutic agents. The capacity to identify molecular pathways that contribute to drug-induced toxicity has been significantly enhanced by recent developments in omics technologies, such as transcriptomics, proteomics, and metabolomics. This has enabled the early identification of potential adverse effects. These insights are further enhanced by computational tools, including quantitative structure-activity relationship (QSAR) analyses and machine learning models, which accurately predict toxicity endpoints. Additionally, technologies such as physiologically based pharmacokinetic (PBPK) modeling and micro-physiological systems (MPS) provide more precise preclinical-to-clinical translation, thereby improving drug safety assessments. This review emphasizes the synergy between sophisticated screening technologies, in silico modeling, and omics data, emphasizing their roles in reducing late-stage drug development failures. Challenges persist in the integration of a variety of data types and the interpretation of intricate biological interactions, despite the progress that has been made. The development of standardized methodologies that further enhance predictive toxicology is contingent upon the ongoing collaboration between researchers, clinicians, and regulatory bodies. This collaboration ensures the development of therapeutic pharmaceuticals that are more effective and safer.

An Updated Assessment of Safety Strategies for Platelet Blood Concentrates (PCs): A Short Review Article

Background: Platelet concentrates (PCs) are one of the most used blood components in blood banks due to their essential role in treating thrombocytopenia, and while viral transmission has been largely addressed, bacterial contamination of platelet concentrates (PCs) are still regarded as a crucial safety concern. Objective: This short review aimed to consolidate current knowledge on the strategies followed in blood banks to maximize the quality and shelf life of platelet concentrates (PCs). Different methods of each strategy were considered, focusing on outcomes related to approved and effective outcomes. Methods: The current study is based on PubMed, Wiley, and Web of Science databases to assess donor selection, bacterial screening, and pathogen reduction technologies utilized for PCs quality. All articles were collected until April 2024. Studies utilizing approved interventions and relevant hospital outcomes were inclusive. However, repetitive data and unapproved methods were among the exclusive criteria. Collected published manuscripts were reviewed. Results: The studies reviewed and referenced in this article consensus that pathogen reduction technologies (PRTs) utilizing Ultraviolet rays (UV) was found to be effective in eliminating various bacterial contamination. Furthermore, the need for donor and bacterial screening is still essential and could not be overlooked. Pathogen reduction technologies (PRTs) remain important and valid despite studies suggesting the reduced platelet concentrates (PCs) quality and the need for frequent transmission of PCs. Some studies even foresee pathogen reduction technologies (PRTs) as replacing the cultural bacterial detection methods. Conclusion:We conclude that preventing bacterial contamination in platelet concentrates (PCs) requires a multifaceted approach. However, future research should focus on optimizing these strategies while minimizing their potential adverse effects on platelet function and safet

An iridium(III) complex-based luminogenic probe for high-throughput screening of hydrogen sulfide donors in living cells

The scarcity of suitable high-throughput screening technology for hydrogen sulfide (H2S) donors has hampered the discovery of H2S donors. In this study, a long-lived cyclometalated iridium complex was rationally designed as a mitochondria-targeted H2S probe to monitor the real-time dynamic change of H2S. By using the time-resolved emission spectroscopy (TRES) technique, an anti-interference high-throughput screening system was developed to monitor H2S in living cells with decreased false negative results. As a proof-of-concept, three natural products were identified as potential H2S donors from a natural product library using the developed TRES probe. Notably, the discovery of allicin and diallyl trisulfide demonstrated the feasibility of this screening platform, while garlic-derived allyl methyl sulfide was explored as a H2S donor candidate. The results were further validated by a commercial assay. We anticipate this high-throughput platform could facilitate the discovery of H2S donors by discriminating the endogenous interfering fluorescence from biological systems.

High‐Throughput Screening Technologies of Efficient Catalysts for the Ammonia Economy

AbstractDriven by the growing global demand for sustainable energy, ammonia is gaining recognition as a crucial energy carrier with the potential for widespread manufacturing. This has spurred the emergence of a “sustainable ammonia economy”. Efficient catalyst development is paramount to achieving this purpose. Although the traditional trial‐and‐error methods have led to substantial progress, they are inherently time‐consuming. In recent years, high‐throughput screening strategies are revolutionizing catalyst discovery, offering an efficient and cost‐effective approach for identifying high‐performance catalysts across various processes within the ammonia economy. This review explores recent advancements in these rapid catalyst screening techniques for ammonia‐based processes. By outlining the general screening principles and the key steps involved in the computational analysis of catalysts relevant to different stages of the ammonia economy, this review aims to provide fundamental insights for the development of novel catalysts using these accelerated methods.

Diagnosis and treatment of patients with gastroesophageal reflux disease - a systematic review of cost-effectiveness and economic burden.

This study aims to review the existing knowledge on the cost-effectiveness and item costs related to the diagnosis and treatment of gastroesophageal reflux disease (GERD) patients at different stages. The study adhered to the PRISMA guidelines. The systematic search involved several steps: finding and identifying relevant articles, filtering them according to the set criteria, and examining the final number of selected articles to obtain the primary information. The number of articles published between 2013 and September 2024 in the Web of Science and PubMed databases was considered. The CHEERS checklist was used for the risk of bias assessment. Ultimately, 36 studies were included. Regarding the cost-effectiveness of GERD treatment, Proton pump inhibitors (PPIs) appeared to be the dominant solution for non-refractory patients. However, this might change with the adoption of the novel drug vonoprazan, which is more effective and cheaper. With advancements in emerging technologies, new diagnostic and screening approaches such as Endosheath, Cytosponge, and combined multichannel intraluminal impedance and pH monitoring catheters should be considered, with potential implications for optimal GERD management strategies. The new diagnostic methods are reliable, safe, and more comfortable than standard procedures. PPIs are commonly used as the first line of treatment for GERD. Surgery, such as magnetic sphincter augmentation or laparoscopic fundoplication, is only recommended for patients with treatment-resistant GERD or severe symptoms. Advances in emerging technologies for diagnostics and screening may lead to a shift in the entire GERD treatment model, offering less invasive options and potentially improving patients' quality of life.

Impact of active case finding for tuberculosis with mass chest X-ray screening in Glasgow, Scotland, 1950-1963: An epidemiological analysis of historical data.

Community active case finding (ACF) for tuberculosis was widely implemented in Europe and North America between 1940 and 1970, when incidence was comparable to many present-day high-burden countries. Using an interrupted time series analysis, we analysed the effect of the 1957 Glasgow mass chest X-ray campaign to inform contemporary approaches to screening. Case notifications for 1950 to 1963 were extracted from public health records and linked to demographic data. We fitted Bayesian multilevel regression models to estimate annual relative case notification rates (CNRs) during and after a mass screening intervention implemented over 5 weeks in 1957 compared to the counterfactual scenario where the intervention had not occurred. We additionally estimated case detection ratios and incidence. From 11 March 1957 to 12 April 1957, 714,915 people (622,349 of 819,301 [76.0%] resident adults ≥15 years) were screened with miniature chest X-ray; 2,369 (0.4%) were diagnosed with tuberculosis. Pre-intervention (1950 to 1956), pulmonary CNRs were declining at 2.3% per year from a CNR of 222/100,000 in 1950. With the intervention in 1957, there was a doubling in the pulmonary CNR (RR: 1.95, 95% uncertainty interval [UI] [1.81, 2.11]) and 35% decline in the year after (RR: 0.65, 95% UI [0.59, 0.71]). Post-intervention (1958 to 1963) annual rates of decline (5.4% per year) were greater (RR: 0.77, 95% UI [0.69, 0.85]), and there were an estimated 4,599 (95% UI [3,641, 5,683]) pulmonary case notifications averted due to the intervention. Effects were consistent across all city wards and notifications declined in young children (0 to 5 years) with the intervention. Limitations include the lack of data in historical reports on microbiological testing for tuberculosis, and uncertainty in contributory effects of other contemporaneous interventions including slum clearances, introduction of BCG vaccination programmes, and the ending of postwar food rationing. A single, rapid round of mass screening with chest X-ray (probably the largest ever conducted) likely resulted in a major and sustained reduction in tuberculosis case notifications. Synthesis of evidence from other historical tuberculosis screening programmes is needed to confirm findings from Glasgow and to provide insights into ongoing efforts to successfully implement ACF interventions in today's high tuberculosis burden countries and with new screening tools and technologies.

Infrared biospectroscopy as a rapid screening tool for COVID-19 diagnosis

BackgroundAdvanced screening technologies, particularly biospectroscopic techniques like infrared attenuated total reflection (IR-ATR) spectroscopy, are gaining significance for their potential to offer fast, reliable, and specific diagnostic methods. These techniques, combined with chemometric approaches, have been increasingly applied for identifying bacterial and viral infections, cancer screening, and are now reported as useful in the context of COVID-19 and Long-COVID. The application IR-ATR, in point-of-care settings is crucial across various contexts. The ongoing progress in deploying IR-ATR in clinical settings represents a significant advancement in infectious disease screening.ObjectiveThe main objective of this study is to demonstrate the efficacy of IR-ATR as a rapid, sensitive, and specific tool for pathogen detection and infection monitoring at the clinical level, in agreement with existing literature.MethodsThe present study applied IR-ATR spectroscopy as a direct screening methodology that discriminates between patients infected with the SARS-CoV-2 virus and healthy subjects via dried serum samples.ResultsThe chemometric analysis through PCA presented an accuracy of 99.18% with a sensitivity and specificity of 98.83% and 97.32% respectively.ConclusionsThis approach supports the potential of IR-ATR for pathogen detection -SARS-CoV-2- in clinical settings as a rapid, sensitive, specific and minimally invasive technique that could be valuable for the deployment of rapid platforms for pathogen identification and viral infection monitoring.