A Droplet Digital Polymerase Chain Reaction (ddPCR) Approach for Sensitive and Non-Invasive Detection of Fetal Genetic Abnormalities

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Thapar Institute of Engineering and Technology

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Non-invasive prenatal testing (NIPT) has revolutionized the early detection of fetal genetic abnormalities, yet conventional platforms such as Next Generation Sequencing (NGS) are often constrained by cost, turnaround time, and operational complexity. This dissertation investigates the clinical utility and analytical performance of droplet digital PCR (ddPCR) as an alternative approach for targeted NIPT. Comparative analysis demonstrates that ddPCR consistently achieves high sensitivity and specificity 98% and 99%, respectively, for the detection of common chromosomal aneuploidies, values that are comparable to leading NGS methods. Importantly, ddPCR yields rapid results within approximately 90 minutes, significantly expediting clinical decision-making compared to the several days required for NGS workflows. The study also highlights the robustness of ddPCR in analyzing samples with low fetal DNA fractions, costeffectiveness, and operational simplicity, making it accessible for use in both high-resource and resource-limited settings. However, ddPCR is best suited for the detection of known genetic targets, with genome-wide and exploratory diagnostics remaining the strength of NGS. Overall, ddPCR emerges as a sensitive, specific, rapid, and affordable tool for non-invasive prenatal detection of targeted fetal genetic abnormalities, with the potential to expand access to timely and accurate prenatal care. Further validation of multiplex ddPCR assays is recommended to broaden their clinical applicability

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