Application of qPCR testing in clinical diagnostics: A brief review of its history, challenges and perspectives
Abstract
Real-time polymerase chain reaction (qPCR) is a molecular technique that has transformed clinical diagnostics by enabling the amplification and quantification of specific nucleic acid sequences with high sensitivity, specificity, and speed. This approach supports the detection of pathogens, genetic mutations, and biomarkers across clinical samples. qPCR is widely employed in fields, such as infectious diseases, oncology, parasitology, and medical genetics, playing a pivotal role in the rapid identification of infectious agents, including those responsible for COVID-19, tuberculosis, leprosy, leishmaniasis, and arboviral infections. Compared with conventional diagnostic methods, qPCR offers substantial advantages, including reduced turnaround times, increased analytical accuracy, and compatibility with automated workflows. Recent technological innovations, including portable thermocyclers, simplified workflows, and ready-to-use commercial kits, along with integration into digital platforms, have expanded the applicability of qPCR to low-infrastructure environments and point-of-care settings. Despite these advances, the technique faces challenges, such as high costs of equipment and reagents, reliance on trained personnel, and susceptibility to inhibition by sample-derived compounds. Nevertheless, the adoption of standardized guidelines, such as Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) and Standards for Reporting Diagnostic Accuracy (STARD), has strengthened the reproducibility and reliability of qPCR in clinical research. Future perspectives suggest an increasing role for qPCR in personalized medicine, epidemiological surveillance, and decentralized diagnostic strategies, further consolidating its importance in clinical practice and global public health. Its combined sensitivity, specificity, and adaptability will continue to drive innovation in molecular diagnostics.
Fields of Study & Subjects
Molecular Biology Techniques and Applications
Clinical Laboratory Practices and Quality Control
Statistical Methods in Clinical Trials
Publication details
- Journal / source
- AIMS molecular science
- Publisher
- American Institute of Mathematical Sciences (AIMS)
- Volume
- 13
- Issue
- 2
- Pages
- 180–204
- Publication date
- 1 January 2026
- Language
- EN