Currently, there exists a significant disparity between the knowledge of Ayurveda and its real-world applications, leading to the erosion of the credibility of its fundamental principles. To decrease the gap between traditional and modern sciences and practices, translational studies are crucial. Translational research is defined as a process where research outcomes move from the laboratory setting of researchers to practical applications in community and patient care settings. The first stage (T1) transfers knowledge from basic to clinical research, while the second stage (T2) applies clinical study findings to real-world settings and community health improvement. The Ayurvedic knowledge system seems to be organized as a translational model itself, wherein Tattva (principles) corresponds to Śāstra (theoretical constructs), and Śāstra to Vyavahāra (practical applications). As a result, the entire system is set up to convert knowledge into actions that will benefit society. The aim of the Śāstra, particularly in the field of medicine, is to enhance human well-being and not to be restricted to scholarly investigations. Ayurveda’s three-tiered knowledge system is intended to make sure that theoretical understandings are applied in practical scenarios. The use of information from basic research to studies that might aid in the production of new products is known as translational research. The results of translational research take the form of concrete items in today’s market-based economy. The primary source of therapeutic alternatives may come from translational research on medicinal plants used in traditional medicine. Drug discovery and development from medicinal plants is a difficult process that calls for knowledge and experience. In order to produce drugs from natural resources, it is necessary to use modern technologies to study the chemistry, pharmacological activity, and underlying mechanisms of action of medicinal plants. New technologies such as high-throughput screening and automated separation methods like flash chromatography are significantly transforming drug development processes. Better drug candidates may result from creative drug design enabled by a systems biology approach combined with the use of current technology like genomics, transcriptomics, proteomics, metabolomics/metabonomics, automation, and computational techniques. When such a strategy is applied successfully, it will enable the development of next-generation drugs to combat the ever-increasing health challenges.