继脑机接口之后，AI制药“粉墨登场”？高贝塔医疗器械指数ETF（159898）连续6日吸金3.66亿元

Group 1 - Nvidia and Eli Lilly will invest $1 billion over the next five years to establish an AI drug laboratory, focusing on accelerating medical discovery and production through robotics and physical AI [1] - The announcement has led to a significant rise in related pharmaceutical stocks, with Dean Diagnostics hitting the daily limit up for three consecutive trading days, and other companies like BGI Genomics and Berry Genomics seeing increases of over 16% and 8% respectively [1] - The medical device index ETF (159898) has gained 2.52% and has seen a net subscription of 366 million yuan over six consecutive days, indicating high market interest [1] Group 2 - Huafu Securities predicts that 2026 will mark the beginning of a new five-year period for AI healthcare, with expectations of more proactive fiscal signals supporting AI medical applications [2] - The current demand for AI applications in healthcare is expected to sustain the industry's long-term development, with recent events indicating a shift towards commercialization [2] - The National Medical Products Administration is expected to release ten measures by 2025-2026 to support the innovation and development of AI healthcare and high-end medical devices [2] Group 3 - The medical device index ETF (159898) tracks the CSI All-Share Medical Device Index, focusing entirely on the A-share medical device sector, with a pure beta quality [3] - The top ten holdings of the index include leading companies like Mindray Medical and United Imaging Healthcare, with over 80% of the portfolio in the ChiNext and STAR Market [3] Group 4 - The ETF's index includes a significant focus on brain-computer interface concepts, which account for approximately 24% of the index [4] - There is a scarcity of pure brain-computer interface stocks in the A-share market, presenting opportunities for capturing innovation in the industry [4] Group 5 - The medical device sector, which includes brain-computer interfaces, is expected to see substantial demand before and during the initial production phase of these technologies [5]