Every individual is genetically different. This highlights the importance of exploring the possibility of personalized medicine tailored for each person’s unique genetic profile. Due to this genetic variability, people have varied responses to the same medication. Thus, it is all the more necessary to withdraw from traditional medication and adopt personalized medicine. Using genomic data analysis techniques, healthcare specialists will be able to distinguish the minute genetic differences to produce unique therapies for each patient. This paper traverses the development of an algorithm to integrate the patient’s genomic data with his medical history. Personalized treatment can be recommended based on the inferences using genomic AI. These insights derived from the algorithm can be scrutinized by decision support systems. This step ensures the reliability of the prescribed personalized treatment and confidence of patients on the medication. Each time the model predicts medication compositions and dosages using genomic data, it becomes more accurate improving therapeutic results.