When gene editing technology achieves the leap of "one treatment for multiple diseases," when artificial intelligence compresses the new drug development cycle from ten years to a few months, and when three-dimensional bone marrow models replicate the human hematopoietic microenvironment in the laboratory—innovative breakthroughs in the biomedical field are reshaping the boundaries of health protection at an unprecedented speed. JinYi Internet believes that these cutting-edge explorations, integrating life sciences, engineering technology, and information technology, are not only solving many medical problems but also reshaping the underlying logic of disease treatment, driving the transformation of the medical system from "symptomatic treatment" to "precision prevention" and "personalized intervention."
The iterative upgrades in gene editing technology are rewriting the history of genetic disease treatment. Traditional gene therapy often relies on "customized" solutions, developing treatments for specific gene mutations one by one. This approach is not only time-consuming and costly but also limits the scope of beneficiaries. However, the PERT gene editing strategy proposed by Liu Ruqian's team at Harvard University uses lead editing technology to modify endogenous tRNA, restoring the full function of proteins whose synthesis was prematurely terminated due to nonsense mutations. This enables broad-spectrum treatment for a variety of genetic diseases. In cell models of diseases such as Batten disease and Tay-Sachs disease, this unified editing system successfully restored the activity of key enzymes; in the Hurler syndrome mouse model, it almost completely reversed the physiological changes of the disease. This breakthrough marks the transition of "disease-independent" gene therapy from concept to empirical evidence, bringing new hope to approximately 24% of patients worldwide suffering from genetic diseases caused by nonsense mutations. Meanwhile, the evoCAST gene editor has achieved precise insertion of long segments of DNA, and base editing technology has successfully cured infants with rare diseases. These advancements have propelled gene therapy from "single-point correction" to "large-fragment reconstruction" and "personalized customization," gradually overcoming treatment bottlenecks in complex genetic diseases such as cystic fibrosis and hemophilia.
Cross-disciplinary integration of technologies has become a core driving force for biomedical innovation. The deep coupling of artificial intelligence and biomedicine is disrupting the traditional pharmaceutical R&D paradigm. Traditional new drug development takes an average of 10 years and costs billions of dollars, while with the help of AI's big data mining and virtual screening capabilities, researchers can quickly identify drug targets, optimize compound structures, and even predict clinical trial results. Shenzhen Xige Biotech's AI system has helped shorten the development cycle of new gastric cancer drugs by 60%, Moderna completed the design of a COVID-19 candidate vaccine in just 42 days using AI, and the AI ??discovery of the Halicin antibiotic has broken through the trial-and-error dilemma of traditional R&D. In the field of therapeutic technology, cross-disciplinary innovation has also yielded remarkable results: the Swiss team used hydroxyapatite as a scaffold and combined it with a three-dimensional bone marrow model constructed from induced pluripotent stem cells to accurately replicate complex structures such as blood vessels, bone cells, and immune cells. This model can maintain blood production for several weeks, providing a platform that is closer to the real human environment for blood cancer research and drug testing. It also puts into practice the principle of "replacing, reducing, and improving" animal experiments in scientific research ethics.
Looking ahead, JinYi Interactive believes that the core direction of biomedical innovation will be a two-way pursuit of "precision" and "inclusivity." On the one hand, with the development of multi-omics technologies and biosensor technologies, medicine will become more closely aligned with individual differences, decoding the health code from multiple dimensions such as genes, proteins, and metabolites, enabling early warning and precise intervention for diseases. On the other hand, AI-driven cost reduction in R&D, technological breakthroughs in universal therapies, and the widespread adoption of non-viral delivery systems will continue to lower the barriers to innovative medicine, making rare disease treatments less exorbitantly priced and allowing advanced therapies to transcend geographical limitations. When the sharpness of technological breakthroughs and the bottom line of ethical regulation are balanced, and when innovative achievements can fairly benefit every group, biomedical innovation will ultimately achieve its ultimate goal—protecting life and health, and expanding the quality and boundaries of human existence.
