■Lin Yuzhu
When the market talks about artificial intelligence (AI) investment, the focus is often on “shovel-selling” companies such as GPUs, servers, data centers and semiconductors. However, investment opportunities in AI do not only exist in hardware and computing power. As AI begins to penetrate into the medical research and development process, the biotechnology industry may also become the next important application scenario.
The investment value of AI is extending from hardware computing power to the biotech medical field, using algorithms to accelerate the development of new drugs and precision medicine. (Reuters)
AI flips the new drug development track
Biotechnology companies and international pharmaceutical companies have recently made historic breakthroughs in the field of cancer treatment. The personalized cancer vaccine jointly developed by the two parties (development code: mRNA-4157/V940) significantly reduced the risk of cancer recurrence and cancer cell metastasis in patients after surgery for high-risk melanoma (a malignant skin cancer) in a large-scale Phase III clinical trial. This achievement is not only the world's first customized mRNA cancer drug proven to be effective in the final clinical stage, but also breaks the deadlock in the past where "cancer vaccines" have mostly remained in the imagination. The most critical driving force behind this is the combination of multiple technologies such as gene sequencing, biological information analysis, and mRNA manufacturing. The comprehensive intervention of artificial intelligence (AI) technology has also opened a new revolution in the anti-cancer drug market. Traditional cancer treatments (such as chemotherapy and radiotherapy) mostly adopt a "one-size-fits-all" model. While killing cancer cells, they often severely damage normal healthy cells in the patient's body, causing strong side effects. Since the "signatures" (called neoantigens in medicine) on the surface of each cancer patient's tumor are different, how to accurately identify the patient's unique cancer characteristics from thousands of cell information and make a drug would take several years and unimaginable labor costs in the past. However, after collaborating with AI, the biotech industry used patented AI algorithms and deep learning models to analyze massive data within a few days after the patient's tumor was removed and gene sequencing was completed, and the patient's 34 unique cancer characteristics that were most easily recognized by the immune system were screened out. AI not only looks for features, but also works like a super simulator to predict which design can best stimulate the patient's own immune cells (T cells) to accurately hunt cancer cells. This golden combination of "AI screening + mRNA manufacturing" shortens the pharmaceutical preparation time to just a few weeks. In addition to playing a decisive role in drug research and development, AI is also gradually changing the process of new drug development.
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Personalized cancer vaccine market to surpass $23 billion
The global clinical trial plans of personalized mRNA cancer vaccines by biotechnology companies and international pharmaceutical companies do not stop at melanoma. The two parties have already launched phase II/III clinical trials in high-risk cancer categories such as non-small cell lung cancer (NSCLC), bladder cancer, and renal cell carcinoma (RCC). Since the market size of lung cancer and other cancers is much larger than that of melanoma, if subsequent trials are successful, the overall industry ceiling will rise exponentially. According to professional industry reports from BioSpace, Towards Healthcare and various authoritative organizations, the market for personalized cancer vaccines and mRNA tumor treatment is experiencing explosive growth and is estimated to reach US$4.2 billion in 2025. As technology matures and clinical demand surges, the market size is expected to rise to US$4.99 billion in 2026 and continue to flourish. It is expected to reach a peak of approximately US$23.32 billion in 2035, with a compound annual growth rate (CAGR) of as high as 18.7%, reflecting the global medical market's high confidence and huge demand for emerging cancer therapies.
The investment story of AI is gradually expanding from pure computing power to more industries. From the personalized cancer vaccines produced by biotechnology companies and international pharmaceutical companies, we can see that AI not only helps companies process more data, but also begins to intervene in more core production processes such as "how to discover drugs, how to choose treatment targets, and how to design treatment plans for different patients." Therefore, when the market is highly concentrated on GPUs, servers and data centers, the biotechnology industry provides another AI application direction worth observing. For long-term investors, it is worth paying attention to which industries can use AI to reduce R&D costs, shorten product development time, and create new business models that were difficult to achieve in the past. AI + biotechnology may become an alternative investment theme in the AI industrial revolution that is less discussed by the market but worthy of long-term tracking.
Lay out AI precision medicine and participate steadily with "Biotech ETF + leading stocks"
However, AI can improve research and development efficiency, but it does not mean that the risks of new drug development disappear. From the entry of candidate drugs into human trials, to the completion of Phase III clinical trials, and then to obtaining marketing authorization from regulatory agencies in various countries, there is still a long development cycle and high uncertainty. The aforementioned therapies are highly customized and are produced without inventory. From surgical sampling, gene sequencing, and biological information analysis to individual factory scheduling, quality inspection and release, the manufacturing process is complicated. The current market estimate is that the cost of a complete course of treatment for a single person is extremely high. Therefore, for investors, although AI biotechnology has high growth potential, it is also an investment field with high volatility and high research threshold. When investing in such high-growth biotech stocks, you should follow the principle of diversified investment. You can participate in this AI-driven precision medical anti-cancer revolution for humans through batch layout, or allocation of biotech index ETFs and large pharmaceutical leading stocks.
(The author is the discretionary account manager of Federal Investment Trust)
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