The US biotech sector is seeing a long-awaited resurgence of risk appetite in August.
On August 19th local time, Moderna and Merck announced positive results from their Phase III study of a personalized mRNA cancer vaccine in combination with Keytruda. This marks the first time an mRNA cancer vaccine has demonstrated statistically and clinically significant benefits in a late-stage clinical trial.
Following the announcement, Moderna’s stock price surged by approximately 160% intraday, Merck rose by about 12%, and the SPDR S&P Biotech ETF rose nearly 5%, quickly boosting the entire innovative drug sector.
More importantly, this is not a one-day phenomenon. JPMorgan Chase statistics show that as of the end of June 2026, the XBI, representing small and medium-sized US biotech companies, has already risen 30.2% year-to-date, significantly outperforming the S&P 500 index over the same period. Biotech companies, which have endured high interest rates, tightened financing, and compressed valuations in recent years, are regaining investor attention.
Against this market backdrop, a previously unremarkable SPAC suddenly became the focus of the after-hours market.
This SPAC, ticker symbol RFAI, closed at $12.73, up 13.71% from the previous trading day, but the real dramatic movement was just beginning.
After-hours trading saw RFAI’s price quickly deviate from the closing price, surging to as high as $78, representing a more than 500% increase within hours; another market data agency recorded an average after-hours trading price approaching $79.80.
For a SPAC that had long been on the fringes of market attention, this was no longer a typical merger and acquisition announcement. The almost abrupt repricing in after-hours trading indicated that some funds were aggressively betting on the expected value of its merged business.
What truly ignited market sentiment was that RFAI was only one step away from completing a $1.5 billion AI pharmaceutical deal.
A SPAC deal that caught the market wave
RFAI’s proposed merger target was Singaporean biotechnology company Nanyang Biologics, or NYB for short.
In October 2025, the two parties formally signed a business merger agreement. The transaction valued NYB at approximately $1.5 billion pre-transactionally. Existing NYB shareholders, in principle, transferred all their shares to the merged publicly traded company and continued to hold the majority stake. Upon completion of the transaction, the new company planned to list on Nasdaq under the ticker symbol NYB.
This deal accelerated significantly in the summer of 2026. On July 23, NYB Holdings’ F-4 registration statement officially became effective; on August 19, RFAI held a special shareholders’ meeting, where the business merger resolution was approved with 6.766 million votes in favor and 441,000 votes against.
At this point, the shareholder approval risk, which had been the market’s biggest concern, was largely eliminated, which was the most direct factor triggering the SPAC company’s after-hours surge in its stock price.
If calculated statically based on the after-hours trading price of nearly $80 on August 20th, the combined NYB Holdings’ equity value could have been pushed up to $12.3 billion. This would have resulted in a book value of nearly $12 billion for the 150 million shares held by existing NYB shareholders, almost eight times the $1.5 billion valuation in the transaction agreement.
This dramatic valuation jump reflects more than just short-term sentiment from a SPAC acquisition; it reflects a concentrated reassessment of NYB’s asset quality and growth potential by US stock market investors.
Amidst the current global capital’s renewed pursuit of innovative drugs, AI-driven pharmaceuticals, and highly volatile biotechnology assets, NYB’s dual attributes of “AI + innovative drugs” clearly hit the mark precisely in terms of the market’s willingness to pay a high premium. US stock market investors are expressing strong optimism about its future value with a price far exceeding the acquisition price.
A Rare Full-Stack AI Pharmaceutical Company
In recent years, AI has become one of the hottest technological directions in the global innovative drug industry, and the US stock market is not lacking in companies with AI pharmaceutical concepts.
In fact, after rounds of conceptual expansion, AI technology itself is rapidly becoming more widespread. The barriers to acquiring algorithms, computing power, and even some basic models are decreasing. A single AI narrative is no longer sufficient to differentiate a company.
The key reason NYB was able to quickly generate enthusiasm among US stock market investors after this transaction is that the market saw not just another AI tool company relying on algorithms to tell a story, but a complete AI-driven innovative drug development system that organically integrates scarce source data, a globally leading AI technology platform, and has already begun to translate into real drug assets.
NYB’s currently disclosed Vecurate natural compound library covers more than 1.5 million natural compounds, originating from more than 50,000 diverse species.
NYB’s unique data resource originated from a joint laboratory established in collaboration with Nanyang Technological University. The two parties initially conducted systematic research on abundant traditional medicinal plants in Southeast Asia, establishing chemical fingerprints for the plants. Subsequently, they used machine learning and data mining for screening, then isolated the selected candidate compounds for in vitro and in vivo validation, and further studied their mechanisms of action and structural optimization, ultimately forming one of the world’s largest proprietary natural compound resource libraries.
In today’s world of increasingly widespread AI computing power and algorithms, a typical AI-driven pharmaceutical company can invest heavily in GPUs to develop new models by utilizing increasingly mature foundational models. However, it cannot replicate the natural biological resources accumulated over many years by another company in a short period.
Based on this highly scarce database of natural compounds and the company’s AI infrastructure spanning the entire early drug discovery process, NYB has now entered the most exciting stage of innovative drug molecule production.
Business consolidation filings with the SEC show that the company has developed multiple proprietary innovative drug pipelines, including NB-A002, NB-B101, NB-C201, and NB-C301, covering multiple disease treatment areas.
Among them, NB-A002 is positioned by the company as a potential first-in-class DNA damage response therapy candidate, targeting ILF2, which previously lacked mature drug development pathways, and attempting to utilize synthetic lethal mechanisms to treat HRD-related tumors. NB-B101 targets solid tumors, and other naturally derived candidate molecules in the cardiovascular and mental health fields are also in preclinical development.
This also creates a clear dividing line between NYB and ordinary AI concept companies: In NYB’s business system, the AI drug discovery technology platform is not only a standalone commercially viable end product, but also a fundamental infrastructure embedded in the company’s core drug discovery process. Its value can ultimately be realized and amplified through innovative drug assets.
RFAI’s astonishing after-hours stock performance after the merger entered its final stage can, to some extent, be seen as the most direct price feedback from the US stock market to this model: what capital truly pursues is the valuation space opened up after AI capabilities are ultimately transformed into high-value drug assets.
As the AI pharmaceutical industry gradually moves from technology demonstration to asset realization, companies that can simultaneously master data, algorithms, and independent innovative drug pipelines are expected to receive a significantly higher valuation premium than pure technology platform companies. NYB is becoming a highly representative company under this new valuation logic.
Triple Sources of Commercial Value
NYB’s comprehensive capabilities, encompassing source data, AI drug discovery technology, preclinical development, and intellectual property commercialization, enable its business model to cover multiple value realization methods.
The most fundamental layer is the commercialization of the AI platform itself. NYB provides molecular screening, activity prediction, and drug discovery services to pharmaceutical companies, research institutions, and life science clients, directly converting its algorithmic capabilities into software revenue, technical service revenue, and platform usage revenue. This layer addresses the issue of whether the platform itself can generate independent cash flow, and it forms the relatively certain value foundation of NYB’s business model.
Furthermore, NYB can deeply participate in the entire value chain of a drug from discovery to commercialization through joint R&D with partners, intellectual property sharing, and technology licensing. The company’s role also shifts from a technology supplier to a co-creator and value sharer of drug assets.
The layer with the greatest commercial value elasticity comes from its own pipeline. For high-potential molecules screened by the platform, NYB can choose to retain core rights and independently advance preclinical research, IND applications, and even clinical development.
As a project moves from early discovery to the clinical research stage, its pricing logic undergoes a fundamental change. A truly innovative drug project with first-in-class potential, once it enters the critical development stage, may experience an explosive increase in the potential transaction value of its single asset, potentially even exceeding the software revenue accumulated by the entire AI platform over many years.
Therefore, NYB’s business model is neither a traditional AI SaaS model nor a simple biotech model relying on a few innovative drug pipelines. Its greater commercial potential lies in utilizing the same data and algorithm infrastructure to simultaneously cover multiple value levels of the innovative drug R&D industry chain, and selecting different asset operation models based on the potential of each project to maximize value.
Chinese Element: The9’s Long-Term Investment
Among NYB’s shareholders is a highly recognizable Chinese capital player—The9. More importantly, for The9, this is not a short-term financial investment chasing the AI hype, but an early-stage bet that has been ongoing for six years.
According to The9’s SEC filings over the years, as early as 2020, The9 began providing funding to Nanyang Herbs and continued investing in 2021.
At that time, generative AI had not yet entered the core narrative of the global capital market, and AI drug development was far from the valuation frenzy it enjoys today. This investment was clearly quite forward-thinking.
According to a disclosure by NineCity on August 11, if the merger between NYB and RFAI is successfully completed, its wholly-owned subsidiary is expected to hold approximately 15% to 16% of the shares in the merged listed company.
This transaction will give existing NYB shareholders 150 million shares. Based on after-hours trading prices, NYB’s market capitalization after its official listing is close to $12 billion. NineCity’s stake is valued at approximately $1.8 billion to $1.92 billion, a remarkably high return.
If NYB successfully completes its listing, this investment may be far more significant for NineCity than simply adding a tradable financial asset.
Since NineCity’s stake is less than 20% of NYB’s total share capital, under US accounting standards, this investment will be recognized at fair market value. NineCity is expected to recognize an investment profit of $1.8 billion to $1.92 billion. Given NineCity’s current market capitalization of tens of millions of dollars in the US stock market, its current market value is severely inverted.
On August 21, The9’s stock price in the US stock market had already risen by 33%, which likely indicates that funds sensitive to market news had already entered the market.
AI is becoming crowded, but combining proprietary data, drug pipelines, and AI infrastructure is a different story.