Sepsis is a life-threatening organ dysfunction caused by the spread of infectious diseases throughout the body, resulting in a dysfunctional immune system response. It includes a wide range of symptomsa ffecting multiple organs, making accurate diagnosis challenging. Early detection is crucial for reducing the severity and improving outcomes of sepsis. While bacterial infections are the primary cause, viral and fungal infections can also lead to sepsis and often go underdiagnosed despiteaccounting for a significant number of cases. Current diagnostic tests, like blood cultures, have long turnaround times, hindering early diagnosis. Thus an accurate early diagnostic test is needed for faster and more targeted sepsis treatment. MicroRNAs (miRNAs) have shown promise as biomarkers forsuch a test, and combining multiple miRNAs in a biomarker panel may enhance diagnostic accuracy. This study aimed to compare manual and robotic methods for miRNA extraction from plasma samples to assess the viability of incorporating robotic miRNA extractions into a diagnostic kit. Furthermore, the study aimed to assess the performance of two- tailed RT-qPCR in detecting and quantifying a candidate miRNA biomarker (mirSeps-4) from human plasma samples. The results demonstrate the capability of two-tailed RT-qPCR to detect and quantify the candidate miRNA. Additionally, absolute quantification of qPCR results showed that robotic extractions yielded a significantly greater quantity of mirSeps-4 in unspiked samples.