AI Transforms Drug Manufacturing, but U.S. Lags
China in Scaling
A Bristol Myers Squibb plant that makes cancer
drugs was the only manufacturer in the U.S. recognized for innovation by the World
Economic Forum this year.
1. AI in
Biopharma Manufacturing
·
At Bristol Myers Squibb’s Devens facility, AI
monitors critical variables (temperature, oxygen, pH) in bioreactors.
·
Helps detect issues in real time, preventing batch
failures and drug shortages.
2. Shift
from Reactive to Predictive Production
·
Earlier: scientists identified problems after
batch failure.
·
Now: AI predicts deviations and suggests corrective
actions during production.
·
Result: ~40% increase in drug output.
3. AI in
Drug Discovery
·
AI analyzes large
datasets to identify promising molecules.
·
Enables “in silico” (virtual) testing before
physical trials.
·
Speeds up discovery and reduces costs, though
clinical success is still uncertain.
4. Global
Manufacturing Gap
·
World Economic Forum’s Global Lighthouse Network
highlights tech-leading factories:
o
China: 99 factories
o
U.S.: 14 factories
·
Key issue: China scales AI faster with more
in-factory tech talent.
5. Pharma
as a U.S. Bright Spot
·
Companies like Pfizer and Eli Lilly are investing
heavily in AI.
·
Aligns with policy push to boost domestic drug
manufacturing.
6.
Real-World Impact on Drugs
·
AI stabilized production of Orencia
(autoimmune drug).
·
Being applied to Breyanzi,
a personalized cancer therapy (currently limited capacity).
·
Potential to scale advanced treatments like cell
therapies.
7.
Productivity & Efficiency Gains
·
AI helps:
o
Optimize harvest timing
o
Adjust conditions based on past data
o
Improve consistency in complex biologics production
8.
Workforce Impact
·
Cost-cutting + AI adoption → job
reductions (1,000+ roles).
·
Company investing in reskilling employees
for AI-related roles.
9.
Strategic Pressures
·
Patent expiry of blockbuster drug Opdivo by
2028 is driving efficiency push.
·
Goal: reduce drug development time from 9 years
to ~6 years.
10.
Global AI Manufacturing Race
·
Chinese firms and factories rapidly adopting AI
across sectors.
·
AI-driven manufacturing seen as key to future
industrial competitiveness.
Bottom
Line
AI is revolutionizing drug manufacturing by making
it predictive, faster, and more efficient, but while U.S. pharma leads
in innovation, China is outpacing in large-scale industrial adoption,
shaping the global competition in advanced manufacturing.
In a sterile Bristol
Myers Squibb lab about an hour north of Boston, scientists in scrubs and hairnets
transfer living cells to a 2,000-liter stainless steel bioreactor that grows them
for weeks. The goal is to produce proteins that are genetically engineered to attack
cells that cause disease.
Tiny variations
in heat, light or pH level can stop the cells from growing, causing drug shortages
that endanger patients. Typically scientists would have
to wait to see what went wrong during that fragile process, but now artificial intelligence
is used to carefully monitor important variables — such as temperature and oxygen
levels — and alert technicians if there are problems.
Every year the World
Economic Forum and McKinsey recognize manufacturers that are on the cutting edge
of technology, including artificial intelligence. This year, the Bristol Myers Squibb
facility in Devens, Mass., was the only manufacturer in the United States that made
the list of 23.
While American companies
typically lead in artificial intelligence research and capital investment, U.S.
manufacturers often struggle to translate those breakthroughs into productivity
gains on the factory floor.
Of the 223 factories
that have made the World Economic Forum’s Global Lighthouse Network list since 2018,
14 have been in the United States, while 99 are in China. Of the American ones,
four are in the pharmaceutical and life sciences sector.
“China is scaling
faster,” said Rahul Shahani, a partner at McKinsey who works with the World Economic
Forum on the initiative. He added, “They have technologists in the factories — hundreds
of them — while in the U.S. we’re competing for that same talent with Silicon Valley.”
Large American pharmaceutical
companies have been a rare bright spot in the use of A.I. Many drugmakers, including
Pfizer and Eli Lilly, are investing billions in A.I. and related technologies to
accelerate drug discovery and streamline manufacturing. The trend coincides with
President Trump’s demands that drugmakers produce more drugs on U.S. soil.
Scientists at the
Devens facility use artificial intelligence to discover molecules that can target
cancer and other diseases with greater precision. A.I. can comb through data sets
from past experiments to identify possibilities that a human might not have considered.
Researchers then test those molecules in the virtual world — a process referred
to as “in silico.” Only the most promising are tested in a physical laboratory.
The company can run multiple “in silico” experiments at a time.
“Drug discovery
and bio-manufacturing are definitely areas where A.I. can have the most impact,”
said Kyle Chan, a fellow at the Brookings Institution’s John L. Thornton China Center. “These are areas where A.I. has some the largest advantages
over previous approaches given the need to process and synthesize large, complex
data sets.”
Still, there’s no
guarantee that technological advantages will instantly equate to benefits for patients.
The history of drug development is filled with failures, and it is unknown whether
molecules identified by A.I. will pass muster in clinical trials.
The Bristol Myers
Squibb facility sits on an 89-acre campus where buildings are decorated with portraits
of cancer survivors.
Previously, scientists
and technicians were never sure why some batches of cells produced a large amount
of proteins, while others failed completely. But now A.I. uses information from
past batches to identify what variables need to change. For example, if oxygen levels
are lower than previous batches, the system will suggest that oxygen be added. If
the pH levels are higher than previous batches, it will recommend a fix. It also
makes suggestions about the best time to harvest the cells.
These innovations
have boosted the volume of drugs produced for clinical trials and commercial use
at the facility by about 40 percent, according to a company spokeswoman.
“We are able to
now intervene in the batches during the manufacturing process and not have to wait
until we get to the end,” said Karin Shanahan, executive vice president, chief supply
chain and operations officer for the company.
These innovations
have helped stabilize production of Orencia, a drug that treats autoimmune conditions
such as rheumatoid arthritis using cells that are extremely difficult to grow. In
2024, manufacturing challenges resulted in a shortage in some parts of the world.
The company is just
beginning to use A.I. in its manufacturing process of another drug, Breyanzi, which turns a cancer patient’s own white blood cells
into a personalized therapy. Currently, the Devens plant is authorized by the Food
and Drug Administration to produce treatments for just 12 patients at a time.
Ms. Shanahan said
she hoped that eventually A.I. would increase production of the treatment, often
viewed as a last resort for people with blood cancers such as leukemia.
Bristol Myers Squibb
has embarked on a series of cost-cutting measures as the key patent for its cancer
drug Opdivo expires in 2028. The drug, which uses proteins that have been genetically
engineered to target cancer cells, generated more than $10 billion of the company’s
$48 billion in revenue last year.
The company is trimming
$2 billion in costs by the end of 2027 in addition to $1.5 billion in cuts announced
in 2024. More than 1,000 positions are being eliminated, many of them at a research
facility in Lawrenceville, N.J., heightening anxiety about A.I.’s taking jobs away
in the sector.
At the Semafor World
Economy summit last month, Bristol Myers Squibb’s chief executive, Chris Boerner,
said the company had a responsibility to use A.I. to further its mission but acknowledged
that it could adversely affect some employees.
“We are engaging
with those employees to make them more marketable around this technology — with
the company or elsewhere,” he said.
The facility in
Devens, which was completed in 2009 at a cost of $750 million, wasn’t designed with
A.I. in mind. As recently as 2020, employees used Excel spreadsheets for some tasks.
Batch records that document every step of production were filled out by hand. But
in recent years, the company has prioritized digitizing and automating its processes.
“We needed to make
sure that we could formulate our products faster, that we could commercially scale
them faster,” Ms. Shanahan said. “And so that’s really what forced us to to start to go down that path.”
Overall the company
aims to cut the time it takes to bring a drug to market to about six years, from
nine, she said.
Other factories
that received recognition from the World Economic Forum this year included Yueda Textile in Yancheng, China, which collects sensor data
to detect machine maintenance issues before they occur, reducing costs; and Midea,
a manufacturer of microwaves and air-conditioners in Thailand that uses A.I. to
investigate customer complaints, generating recommendations for corrective action
that cut resolution time from months to days.
Some of the factories
in China that received the award in previous years belong to American companies,
including Johnson & Johnson and Agilent, a California-based supplier of high-end
laboratory equipment. But Chinese drugmakers are expanding their uses of A.I. as
well.
“This is not just
a trend among American pharmaceutical firms,” said Mr. Chan, the Brookings Institution
fellow. “China’s biotech industry has been moving quickly to leverage A.I. to accelerate
progress.”