Thyroid diseases, such as Hashimoto’s thyroiditis, Graves’ disease, and thyroid cancer, affect millions of people worldwide, often remaining undiagnosed or misdiagnosed. Despite existing therapies, many patients face improper medication dosing, side effects, and ineffective treatments, leading to a reduced quality of life and increased healthcare costs. The main challenge lies in the fact that current treatments largely do not account for individual genetic predispositions and environmental factors.

Our project introduces a new, personalized approach to thyroid disease diagnosis and treatment, leveraging advanced technologies such as next-generation sequencing (NGS) and polygenic risk scoring (PRS). By integrating pharmacogenomics, electronic health records, and lifestyle data, we enable more precise risk assessment and tailored therapies. This approach allows healthcare professionals to better understand patients’ specific needs and optimize treatment strategies, reducing the risk of side effects and ineffective interventions.

The development of specialized gene panels for thyroid diseases and the implementation of artificial intelligence in data analysis are key steps toward incorporating personalized medicine into clinical practice. These innovative solutions not only enhance existing treatment methods but also enable earlier disease detection and complication prevention. Our goal is to improve thyroid disease management, making it more precise, effective, and accessible to all patients.