Integrating Gene Therapy and Artificial Intelligence for Personalized Treatment of Thalassemia: Approaches, Challenges, and Future Perspectives

Thalassemia is a hereditary hemoglobinopathy characterized by impaired globin‑chain synthesis, leading to chronic anemia, iron overload, and multi‑organ complications. While allogeneic stem‑cell transplantation remains the only established curative option, it is limited by donor availability and transplant‑related risks. Recent progress in gene therapy, including lentiviral gene addition, CRISPR‑based gene editing, and emerging base‑editing platforms, offers a promising pathway toward durable, individualized correction of the underlying genetic defect. However, patient‑specific variability in genotype, disease severity, iron burden, immune profile, and treatment response continues to challenge uniform clinical outcomes. In this context, artificial intelligence (AI) has emerged as a transformative tool capable of enabling precision medicine in thalassemia. This review explores the synergistic integration of gene therapy and AI to optimize personalized treatment strategies. Machine‑learning models can predict patient‑specific responses to gene therapy by analyzing complex genomic, transcriptomic, and clinical datasets. Deep‑learning algorithms facilitate the design and optimization of viral vectors, guide RNAs, and gene‑editing architectures with enhanced safety and efficiency. AI‑driven digital platforms also support real‑time monitoring of post‑therapy outcomes, enabling early detection of adverse effects, prediction of long‑term hematologic stability, and adaptive treatment modifications. Moreover, AI‑based decision‑support systems can personalize patient selection, risk stratification, and therapeutic timing, ultimately improving efficacy and reducing complications. By integrating advanced gene‑editing technologies with intelligent computational models, a new generation of highly personalized therapies for thalassemia is becoming achievable. This review highlights the current progress, existing challenges, and future directions for implementing AI‑enhanced gene therapy as a cornerstone of precision hematology.

کلیدواژه ها:

Thalassemia ، Gene Therapy ، Artificial Intelligence ، Personalized Medicine ، CRISPR Gene Editing ، Machine Learning