A digital replica of an object or a subject known as a ‘Digital Twin’ (DT) is gaining popularity in several industries. DT makes use of models that are powered by artificial intelligence (AI) and a sizable amount of data from various Internet of Things (IoT) devices. The DT of the patient uses historical data insights to help choose the best drug, predict the outcomes of a certain procedure and manage chronic illness. By constructing personalized patient models to enhance diagnosis, treatment and patient outcomes, DT technology, a sector that is currently in the midst of a rapid development, has the capability to completely transform healthcare (HC). With the use of this technology, various treatment approaches can be tested and simulated on a virtual version of the patient. The creation of virtual illness models using DTs can be utilized to evaluate the effectiveness of treatment options. HC experts can choose the best course of action for each patient by simulating several treatment choices. This strategy may result in treatment programmes that are more effective and individualized, which may enhance patient results. Additionally, therapy regimens for individual patients can be made using DT technology. HC practitioners can determine the best treatment options for a patient based on the patient's distinct traits by developing a virtual model of the patient. This method can be especially helpful for treating complex diseases like cancer, when the patient's unique circumstances may necessitate a variety of therapy options. The promise of DT technology for managing diseases, including its application in drug discovery, is explored in this article.