📄 Abstract
Personalized medicine (PM) offers a new way of approaching healthcare. It moves away from the traditional "one-size-fits-all" model and focuses on treatments tailored to individual genetic, environmental, and lifestyle factors. This new approach takes advantage of progress in genomics, pharmacogenomics, and artificial intelligence to improve treatment effectiveness and reduce side effects. Recent studies highlight the use of multi-omics data to better classify diseases and develop treatment plans, which improves precision in clinical decisions. For example, using artificial intelligence to analyze complex datasets has helped identify new biomarkers and predict how patients will respond to treatments. This paves the way for more personalized therapies. Additionally, the creation of personalized vaccines and gene editing therapies, like CRISPR, shows the potential of PM in tackling rare and complex diseases. However, implementing PM widely faces obstacles, such as regulatory issues, ethical concerns, and differences in healthcare access. Efforts are being made to create systems that promote fair access to personalized treatments, ensuring everyone benefits from these advancements. In conclusion, personalized medicine has great potential to change healthcare for the better, but its success depends on working together to overcome current challenges and create a patient-focused approach.
📚 How to Cite:
Sahil Shaukat Pathan, Dhanashri Puri, Rani Mehtre, Vijaysinh Sable , PERSONALIZED MEDICINE: INTEGRATING MULTI-OMICS, ARTIFICIAL INTELLIGENCE, AND TARGETED THERAPEUTICS FOR PRECISION HEALTHCARE , Volume 10 , Issue 11, November 2025, EPRA International Journal of Research & Development (IJRD) , DOI: https://doi.org/10.36713/epra24881