Recursion PharmaceuticalsThe merger with Exscientia is undoubtedly one of the most significant moves in the field of AI-driven drug discovery.
From both sides, this merger is a strategic move. However, it is worth noting that the merger takes place against the backdrop of an uncertain future for artificial intelligence, with both companies' stock prices showing a downward trend.
Singapore-based AI pharmaceutical companyMagmoleThe founderYuguang MuIt is believed that the background of this merger cannot be ignored."The merger between Recursion and Exscientia may have some complementarity, but both companies are still under significant pressure; furthermore, whether the proposed 'end-to-end drug discovery platform' will yield results remains to be seen.""Because both teams need to spend a lot of time sharing knowledge, processes, etc., related to receptors, proteins, and RNA targets."
"The merger of Recursion and Exscientia appears to be both a strategic consolidation and a response to market pressures," said Artem Trotsyuk, partner at Longe VC. "It combines complementary AI approaches that could potentially accelerate drug discovery; however, it also reflects the need for scale and efficiency in a challenging market."
Recursion and Exscientia are not the only companies that have encountered setbacks; another leading company in the field, BenevolentAI, has also faced challenges.BenevolentAIThe market value also dropped significantly. BenevolentAI was once considered one of the most promising companies in the field. However, it has faced a series of challenges, including the failure of its atopic dermatitis candidate drug BEN-2293 in mid-stage clinical trials. The drug, developed using the company's AI platform, failed to outperform a placebo in improving eczema symptoms.
Against this backdrop, investors and industry observers have begun to question whether the promise of faster, cheaper, and more efficient drug discovery powered by AI can continue to deliver tangible results.In other words, is the bubble of AI-driven biotechnology bursting?
Is the Artificial Intelligence Bubble Bursting?
The latest episode of "Hard Fork," a podcast from The New York Times, explored the issue by drawing comparisons between the current AI crisis and the dot-com bubble.
The Internet Bubble was a period of extreme growth in the value of Internet companies, primarily occurring in the late 1990s. Driven by speculative investments in booming Internet-related companies, the bubble caused stock prices to soar, often without regard for their actual profitability or business models.
By March 2000, the Nasdaq had peaked, driven by irrational speculative investments. Companies with no clear revenue sources or sustainable business models achieved astronomical valuations solely based on their association with the internet. When investors began to realize that many internet companies would never turn a profit, the bubble burst, leading to a massive sell-off.
Similarly,In the field of artificial intelligence, there is a general expectation that AI can achieve breakthroughs in areas such as healthcare, which often leads to overvaluation.Just as the Internet bubble was driven by speculative investments in Internet companies, the artificial intelligence market is currently experiencing a similar influx of capital.
However, this comparison has its limitations. Kevin Roose, host of the Hard Fork podcast, pointed out that the status of now-bankrupt companies is different from that of companies during the internet bubble era. "Most of the bankrupt companies were private and not listed on stock exchanges. Publicly traded companies like Metas, Amazon, and Google, on the other hand, have large cash reserves. The latter also have other businesses that can subsidize their investments in artificial intelligence."
If the AI biotech bubble bursts, a large number of AI-focused companies may either go bankrupt or be acquired by larger, more established companies.
However,Just as the internet did not disappear after the dot-com bubble burst, artificial intelligence is likely to continue evolving and become an indispensable part of various industries.Although the bursting of the Internet bubble brought immediate negative effects, it ultimately propelled the maturation of the Internet industry, with surviving companies like Amazon and Google gradually becoming some of the most valuable companies in the world.Similarly, the failure of artificial intelligence may lead to a more sustainable and focused industry, where only companies with viable, proven technologies can survive.
Artificial Intelligence Is Undergoing Necessary Market Adjustments
People have high hopes for the AI + biotechnology field, hoping to revolutionize the drug development process by significantly reducing time and costs. However, as GPTZero's CEOEdward TianPointed out,The industry is currently working hard to bridge the significant gap between these high expectations and the reality of what AI can achieve.
Trotsyuk attributed the current challenges faced in the artificial intelligence field to several factors. "First, AI-driven discoveries are taking longer than initially expected to reach the clinical stage; second, broader economic pressures, such as the high cash burn rate of AI research and development, are straining resources; finally, there is a mismatch between the market’s expectation for short-term returns and the inherently long-term nature of drug discovery."
Yuguang Mu agrees with Trotsyuk's view that this decline is due to a lack ofCaused by the mismatch between significant scientific breakthroughs achieved through artificial intelligence and people's overly high expectations of AI."This may be part of a broader market adjustment. Artificial intelligence is a tool for complex data analysis, but it may not lead to scientific breakthroughs, especially in the medical field. People often have overly high expectations for AI in drug development, but it has proven that AI is not a panacea."As expectations and breakthroughs seek a new lower equilibrium, valuations may decline.”
Despite these challenges, there remains strong belief in the long-term potential of AI within the biotech sector. Henry Levy, President of Life Sciences and Healthcare at Clarivate, is optimistic about the development of AI in healthcare: "Companies like Exscientia are experimenting with AI-designed drugs, while innovations such as Google DeepMind's AlphaFold 3 can predict protein interactions, indicating that AI can accelerate research and discovery."
Lindus Health co-founder Meri Beckwith said there is no need to worry about these setbacks, as AI is delivering on its promises as expected. "The promise of AI is not just about making AI-designed drugs more likely to enter clinical trials. It’s also about creating a broader and more diverse pipeline and bringing them to the IND stage in a more cost-effective manner."
Beckwith added that recent advances indicate artificial intelligence can effectively support target identification and small molecule drug design, but there is still significant room for improvement. "Despite some progress, we are still a long way from 'letting go,' where scientists can sit back and let LLMs (large language models) do the work for them. There is an opportunity for AI to further optimize chemical reactions in drug discovery as the existing AI tools in this field are still in the early stages of development."
Most importantly, Beckwith believes that there are still many opportunities in artificial intelligence that have not been fully explored, as in drug discovery. "So far, most of the investment and deployment in AI has been concentrated in drug discovery or preclinical stages. However, the vast majority of drug development costs occur in the later-stage human clinical trials, where the adoption of AI is currently very low. This indicates significant room for growth in AI's potential. Nevertheless, the pharmaceutical industry is very late to adopt new technologies, especially in clinical trials, so I expect changes over the next decade to be slow."
Although it seems that the artificial intelligence bubble is bursting, industry experts are more optimistic. In their view,Incremental progress, rather than revolutionary breakthroughs, should be expected in the short term.The long-term potential remains enormous, but achieving this goal may take longer than initially anticipated.
Reference link:
https://www.labiotech.eu/trends-news/ai-biotech-bubble/
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