Bioscience Methods 2024, Vol.15, No.3, 91-101 http://bioscipublisher.com/index.php/bm 94 inherited diseases. Genetic testing can identify carriers of specific mutations, helping breeders make informed decisions and reducing the prevalence of genetic disorders in the feline population. 3.3 Oncology and cancer detection Molecular diagnostics are crucial for the early detection of tumors in pets. Liquid biopsy, which involves the analysis of circulating tumor DNA (ctDNA) or other tumor-derived molecules in body fluids, offers a non-invasive method for early cancer detection. This technique can identify tumors at an early stage, improving the chances of successful treatment. The identification of biomarkers through molecular diagnostics has transformed veterinary oncology. Biomarkers can indicate the presence of cancer, predict disease progression, and guide treatment decisions. The use of molecular tests to detect these biomarkers allows for personalized cancer therapy, improving outcomes for pets with cancer (Sokolenko and Imyanitov, 2018). 3.4 Monitoring and management of chronic diseases Molecular diagnostics are used to monitor and manage chronic diseases such as diabetes in pets. Genetic testing can identify predispositions to diabetes, while molecular assays can monitor glucose levels and other relevant biomarkers. This enables veterinarians to tailor treatment plans and manage the disease more effectively (Upadhyay et al., 2021). Chronic kidney disease (CKD) in pets can also be monitored using molecular diagnostics. Biomarkers identified through molecular techniques can indicate the early stages of kidney disease, allowing for timely intervention. Regular monitoring of these biomarkers helps in managing the progression of CKD and improving the quality of life for affected pets (Otto et al., 2016; Xue et al., 2021). By integrating molecular diagnostics into veterinary practice, the detection, treatment, and management of various diseases in pets have become more precise and effective, leading to better health outcomes and enhanced quality of life for our animal companions. 4 Technological Advancements in Molecular Diagnostics 4.1 Advances in PCR technology Polymerase Chain Reaction (PCR) technology has seen significant advancements, particularly with the integration of microfluidic systems. These systems have enabled the miniaturization of PCR processes onto chip devices, which offer benefits such as increased speed, reduced cost, enhanced portability, and automation. These improvements are crucial for point-of-care (POC) diagnostics, especially in resource-limited settings where traditional, centralized laboratory-based PCR methods are impractical (Park et al., 2011). Additionally, the development of loop-mediated isothermal amplification (LAMP) techniques linked to smartphone technology has further enhanced the efficiency and sensitivity of PCR-based diagnostics for various pathogens, including those affecting pets (Upadhyay et al., 2021). 4.2 Innovations in sequencing platforms Recent innovations in sequencing platforms have made significant strides in making molecular diagnostics more accessible and efficient. Mobile phone-based multimodal microscopes have been developed to perform targeted next-generation DNA sequencing and in situ mutation analysis. These portable devices allow for on-site diagnostics, which is particularly beneficial for telemedicine applications and remote veterinary care (Figure 2) (Kühnemund et al., 2017). Furthermore, the integration of plasmonic assays with sequencing technologies has facilitated the development of cost-effective, sensitive, and rapid diagnostic methods suitable for both developed and developing regions (Yu and Wei, 2018). 4.3 Integration of AI and machine learning The integration of artificial intelligence (AI) and machine learning into molecular diagnostics is revolutionizing the field by enhancing the accuracy and speed of disease detection. AI algorithms can analyze complex datasets generated by molecular diagnostic tools, providing rapid and precise diagnostic results. This integration is particularly useful in the development of portable diagnostic instruments, which require efficient data processing capabilities to function effectively in various settings, including veterinary clinics and field conditions (Lepej and Poljak, 2020). AI-driven platforms are also being used to improve the sensitivity and specificity of diagnostic assays, thereby reducing the likelihood of false positives and negatives.
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