Pharmaceuticals make bigger bets on fewer projects with AI-powered drug discovery

Pills are being manufactured in this file image [GETTY IMAGES]

 
AI is rapidly reshaping the global pharmaceutical and biotech industry, with companies funneling bigger bets into fewer, high-stakes partnerships to improve drug development success rates.
 
The past model — where pharmaceutical firms spent billions of dollars on speculative lines of research without a guarantee of success — is giving way to a more concentrated and technology-driven process that cuts costs and shortens timelines.
 

Related Article

• U.S. unlikely to impose tariffs on generic drugs, easing concerns of Korean pharma companies

• Korean pharma, biotech companies on alert after Trump vows 100% drug tariffs

• Gov't to invest 750 billion won in next 2 years to commercialize AI-enabled products

Projects down, but value up
 
The total value of global joint research and development deals among pharmaceutical and biotech companies reached $86.7 billion in 2025 — up 49 percent from a year earlier, according to health care market research firm IQVIA on Tuesday, while also surging 47 percent to an average of about $1.16 billion per agreement, marking a record high.
 
The number of deals, however, has declined over the past five years — highlighting a shift toward fewer but larger, more targeted investments.
 
AI and machine learning have become core technologies in collaborative drug discovery, driving large-scale, technology-intensive partnerships, according to IQVIA.
 
Rather than expanding the number of partnerships, companies are concentrating capital on AI-driven drug discovery platforms that, for now, at least, appear to offer a surer chance of a product hitting the market.
 
Big Tech firms are increasingly forming alliances with pharmaceutical companies.
 

.

 
The AI drug discovery market is expected to grow from about $2.9 billion this year to $13.8 billion by 2033, according to market research firm Grand View Research.
 
Nvidia has partnered with Eli Lilly — the world’s largest pharmaceutical company — to invest $1 billion in building a next-generation research lab. Google-backed AI drug startup Isomorphic Labs has also signed large-scale joint development deals with Eli Lilly worth $1.7 billion and with Novartis worth $1.2 billion.
 
Chinese firms are also scaling up aggressively.
 
CSPC Pharmaceutical, which has developed its own AI platform, secured a $5.3 billion investment from AstraZeneca, and drug design company XtalPi has launched a large-scale project worth $6 billion with U.S. information technology firm DoveTree.
 
Korean companies such as JW Pharmaceutical, Daewoong Pharmaceutical and SK Biopharmaceuticals are also entering the race by developing their own platforms and pursuing external collaborations.
 

The Eli Lilly logo on one of the company's offices in San Diego, California, on Sept. 17, 2020 [REUTERS/YONHAP]

Will AI navigate drug development?
 
The appeal of AI lies in tackling the industry’s core bottleneck: time and cost.
 
Developing a single new drug typically takes 10 to 15 years and costs between 1 trillion won to 2 trillion won ($673 million to $1.3 billion). AI, however, can rapidly analyze vast datasets and identify promising candidate materials for new drugs from millions of possibilities with high precision.
 
Insilico Medicine, a leading AI drug discovery company, completed the process from molecular structure design to early validation in just two months.
 
“This was about 15 times faster than the conventional process, which usually takes two to three years,” the Korea Biotechnology Industry Organization said.
 
But transforming AI-discovered candidates into approved drugs remains a major hurdle.
 

Nvidia signage outside the Nvidia Corporation headquarters in Santa Clara, California, on Feb. 24 [EPA/YONHAP]

 
“While AI excels at identifying promising candidates, proving their effectiveness in the human body and overcoming complex regulatory systems in each country are entirely different challenges,” said Yeo Jae-cheon, an adjunct professor of biomedical science at the Catholic University of Korea.
 
Industry experts say this is driving a new model — pairing Big Tech’s algorithms with Big Pharma’s capital and clinical expertise.
 
“To overcome these hurdles, large-scale collaborations combining the technological capabilities of Big Tech and the capital of Big Pharma are becoming increasingly essential,” Yeo said.
 
In 2020, Britain-based Exscientia spurred expectations by identifying an anticancer candidate using AI, but the project was halted in 2023 during clinical trials and later sold to a competitor.
 
In Korea, the sector is still in its early stages, with calls growing for stronger policy support.
 
“Despite the potential of AI-driven drug development, the domestic industry is still in its early stages,” Yoon Hee-jung, a research fellow at the Korea Institute of S&T Evaluation and Planning, said. “Policy support is needed to expand investment and help Korean companies build strategic alliances in the global market.”


This article was originally written in Korean and translated by a bilingual reporter with the help of generative AI tools. It was then edited by a native English-speaking editor. All AI-assisted translations are reviewed and refined by our newsroom.
BY KIM SU-MIN [lim.jeongwon@joongang.co.kr]