AI drug discovery: what’s funding like now?

All funding deals in the AI in drug discovery market over the last 24 months

Below is the table listing all the deals. You can find our methodology at the end of this page.

If you want a deeper understanding of the market and its current dynamics, get our report covering the AI In Drug Discovery Market.

Is AI drug discovery funding actually stronger right now?

Yes: AI drug discovery funding is clearly stronger today on capital and round size, even though the number of companies getting funded has barely moved.

We counted 58 financings in the latest 12 months, up from 54, while the number of funded companies increased from 51 to 53. That is modest growth. The money changed much more dramatically: disclosed and estimated capital went from $1.95 billion to at least $4.84 billion, and the median round climbed from $11 million to $18.5 million.

The market can support much larger financings than it did a year ago. The average round more than doubled as well, although that figure is heavily pushed up by a handful of huge deals.

Breadth is the weaker part of the story. A 148% jump in capital alongside only 4% growth in funded companies means investors are concentrating much more money into each successful company. Today, AI drug discovery looks better funded and more mature, without looking like a broad startup boom.

Metric	Current L12M	Previous 12M	Change
Deals	58	54	+7.4%
Unique funded companies	53	51	+3.9%
Total capital	≥$4.84B	$1.95B	≥+148%
Median round	$18.5M	$11.0M	+68%
Average round	$83.4M	$36.8M	+127%
Largest round	$2.10B	$600M	+250%
Early-stage deal share	67.2%	74.1%	-6.8 pp
Later-stage deal share	20.7%	16.7%	+4.0 pp

Would AI drug discovery still look strong without the megadeals?

Yes. Even after stripping out the biggest AI drug discovery rounds, underlying funding is still up materially.

Removing every financing above $50 million leaves $831 million of current-period capital versus $596 million previously, an increase of about 40%. If we exclude rounds above $100 million instead, funding still rises from $840 million to $1.27 billion.

That makes the upswing much more credible. Isomorphic Labs' $2.1 billion Series B is obviously enormous, and Earendil Labs' $787 million financing disclosure and Chai Discovery's $400 million Series C push the headline much higher. Still, the market below those rounds has strengthened too.

Concentration has become extreme at the same time. The top three financings absorb nearly 68% of current capital, compared with 45% a year earlier. Average monthly funding jumped to roughly $403 million, while the median month reached only about $136 million. Deal activity itself stayed fairly steady throughout the year; the wild swings came from the size of a few financing events.

So two things are happening at once: normal rounds are getting larger, and the very top of the market has become much more winner-heavy.

Are more AI drug discovery startups actually getting funded?

Barely. AI drug discovery is funding almost the same number of companies as a year ago, while fewer startups are entering the market through a first financing.

Unique funded companies increased from 51 to 53. Four additional deals across a full year also amount to fairly small growth. We are nowhere near the kind of expansion the headline dollar figure might suggest.

The bigger concern is at the entry point. First financings dropped from 16 to 12, and their share of all deals fell from 29.6% to 20.7%. The median first financing also moved down from $10 million to $7.45 million.

More capital is available today, but new companies are capturing less of it. Looking only at total funding would miss that deterioration in startup formation.

Are investors mostly backing the same AI drug discovery winners now?

Yes. The biggest structural change in AI drug discovery is the amount of money flowing to companies that have already raised before.

Follow-on deals increased from 38 to 45, and they attracted about $4.61 billion in the latest period, compared with $1.17 billion previously. The typical follow-on also became much larger, with the median rising from $13.15 million to $23.2 million.

Some of the beneficiaries are remarkably young. Chai Discovery, founded in 2024, went through a rapid sequence of large rounds and reached a $400 million Series C in 2026. Aureka Biotechnologies, founded in 2023, also completed several financings in quick succession and closed a $100 million Series B. The median age of all funded companies actually fell from roughly four years to three.

So an "existing winner" is not necessarily an old company. Often it is a young AI-native business that has already accumulated enough technical results, pharmaceutical relationships or pipeline progress to raise repeatedly.

Metric	Current L12M	Previous 12M
First financings	12	16
First-financing share	20.7%	29.6%
Capital in first financings	$175M	$781M
Median first financing	$7.45M	$10.0M
Follow-on financings	45	38
Follow-on share	77.6%	70.4%
Capital in follow-ons	$4.61B	$1.17B
Median follow-on financing	$23.2M	$13.15M

Why are AI drug discovery rounds getting so much bigger?

AI drug discovery rounds are getting bigger because the whole middle of the market has moved upward alongside the megadeals.

The clearest change appears in the round-size distribution. Deals below $5 million dropped from 29.6% of financings to 17.2%. At the same time, $20 million-to-$50 million rounds jumped from 18.5% to 31%.

A year ago, a much larger part of the market consisted of small experimental financings. These days, eight-figure rounds in the $20 million-to-$50 million range are far more common.

We can see that in companies such as AI Proteins with its $41.5 million Series A, Tahoe Therapeutics with $30 million, Turbine with $25 million and several other financings sitting well below the giant headline rounds. The middle is simply thicker now, which is why the median moved so sharply even after we account for outliers.

Is Series B where the AI drug discovery money is now?

Yes. Series B has become the main scaling point for AI drug discovery capital.

Series B represented just 3.7% of deals in the previous period. It now accounts for 17.2% and captures 56.2% of current capital. That is an unusually large change for a single financing stage.

Isomorphic Labs accounts for a huge part of those dollars, yet the Series B wave extends well beyond Isomorphic. Syneron Bio closed a $150 million Series B, Aureka raised $100 million, Superluminal Medicines raised $60 million, Turbine raised $25 million, and Arpeggio Biosciences recorded roughly $20 million.

Seed and Series A activity remain substantial by deal count, so early-stage investing is still alive. The difference is the amount of capital companies can access once they reach the next scaling phase.

Series D+ deals, meanwhile, disappeared from this year's sample. The center of gravity has shifted specifically toward B-stage companies building pipelines, expanding platforms and trying to prove that their technology can become a repeatable drug-development engine.

Stage	Current deal share	Previous deal share	Current capital share
Seed	34.5%	42.6%	5.3%
Series A	32.8%	31.5%	11.7%
Series B	17.2%	3.7%	56.2%
Series C	1.7%	3.7%	8.3%
Series D+	0%	7.4%	0%
Growth Equity	1.7%	1.9%	~0%
Unknown	12.1%	9.3%	18.5%

Is de novo design really taking over AI drug discovery?

De novo design is dominating AI drug discovery dollars today, while its share of actual deals looks much less extreme.

We counted 26 current-period financings in de novo design. Deal share barely changed from the previous year, yet the category's share of capital surged to roughly 85%. Its median round also more than doubled to $28.5 million.

The size of Isomorphic's financing explains part of that gap, but plenty of other companies are raising serious money too. AI Proteins closed a $41.5 million Series A, Boltz launched with a $28 million seed round, Aureka closed a $100 million Series B, and Superluminal raised another $60 million.

What investors seem to like right now is the combination of generative design and a path toward actual therapeutics. The better-funded companies usually connect their models to proprietary experimental systems, molecule generation, drug programs or pharmaceutical partnerships.

Deal share is stable. Capital is piling in much faster.

Which AI drug discovery niches are actually gaining momentum?

AI lead generation is the cleanest breadth winner in AI drug discovery, while lead optimization has clearly cooled.

Lead generation increased from six deals to ten, and its median round rose from about $11.4 million to $20 million. Both activity and typical check size improved.

Preclinical prediction AI grew in a very different way. Deals doubled from four to eight, yet the median financing fell from $31.5 million to only $4.6 million. More companies are being tried, but investors are doing it with much smaller checks.

AI lead optimization went from nine financings to three, making it the clearest drop in company-level activity. Target discovery also lost some deal share, while drug repurposing remains a small corner of the market.

As seen above, de novo design has the largest capital pool. Lead generation gives us a cleaner read on broadening demand because its improvement does not depend on one or two billion-dollar financings.

Category	Current deals	Deal-share change	Current median	Funding intensity
De Novo Design	26	+0.4 pp	$28.5M	1.89x
AI Lead Generation	10	+6.1 pp	$20.0M	0.50x
AI Target Discovery	9	-3.0 pp	$12.0M	0.16x
Preclinical Prediction AI	8	+6.4 pp	$4.6M	0.14x
AI Lead Optimization	3	-11.5 pp	$12.3M	0.16x
AI Drug Repurposing	2	+1.6 pp	$33.5M	0.40x
Market overall	58	—	$18.5M	1.00x

Are AI drug discovery companies raising again faster now?

There is no convincing acceleration. The AI drug discovery companies we can track are actually taking a little longer to come back for another round.

For 18 current follow-on deals where we could reconstruct a previous financing from the same market history, the median gap was 13.6 months. The equivalent figure was 9.8 months for the previous period.

The old-period sample contains only eight usable companies, so we would not put much weight on the difference itself. The more interesting result is the size of the next check.

Current repeat raisers came back with a median financing around 2.01 times the size of their previous recorded round. The previous-period figure was only 1.16 times. Half of the current sample raised more than twice the prior amount.

Chai is the obvious example. It moved through roughly $70 million, then $130 million, then $400 million financings within a remarkably short period. The broader pattern is milder, but it points the same way: companies do not necessarily return faster, yet successful ones can come back for a much larger round.

Are investors getting pickier about AI drug discovery startups?

Yes. AI drug discovery investors look pickier at the entry point and far more willing to scale companies once they have proof.

The median first financing fell to $7.45 million, while the median follow-on moved above $23 million. That gap has widened sharply. Investors appear more cautious when a company first enters the funded market and much more aggressive once it survives that first test.

Investor breadth itself has held up reasonably well. After normalizing obvious name variants, we found roughly 60 unique disclosed lead investors in the latest period versus 54 previously, despite slightly worse lead-investor disclosure coverage. Only three lead investors appeared more than once in current deals.

So the concentration of capital does not seem to come from the exact same venture firms controlling every round. A fairly wide investor pool is choosing a narrow group of companies for very large commitments.

That is a tougher market for a brand-new startup and a very attractive one for a company that has already produced convincing evidence.

What proof do AI drug discovery companies need to raise big rounds now?

For the biggest AI drug discovery rounds today, investors increasingly want the model tied to real drug programs, experiments, partnerships or clinical progress.

Isomorphic Labs said its $2.1 billion financing would support the expansion of its AI drug-design engine, global scaling and movement of therapeutic programs toward the clinic. Earendil linked its $787 million financing disclosure to its AI R&D platform, team expansion and biologics pipeline.

Iambic raised more than $100 million after reporting human clinical data for IAM1363 and announcing a collaboration with Jazz Pharmaceuticals. Chai has built relationships with several major pharmaceutical groups while moving rapidly through successive rounds.

Aureka is another useful example of where the market is going. Its $100 million Series B was attached to biological foundation models and a closed-loop approach connecting AI with high-throughput experimental work. Superluminal's latest $60 million Series B is tied to moving its lead program toward the clinic.

We cannot turn those examples into a precise market-wide percentage because companies do not report milestones or use of funds in a standardized way. Still, the companies winning the largest rounds these days tend to show investors something beyond a promising algorithm.

Are pharma and tech companies putting more money into AI drug discovery?

Yes. Strategic capital is showing up more often in AI drug discovery, and the checks are much larger than they were a year ago.

Strategic-backed financings increased from roughly 22% to 28% of deals. Their median financing went from around $24 million to almost $54 million.

The names involved also show how AI drug discovery is moving closer to mainstream pharmaceutical R&D. AstraZeneca has backed Syneron Bio and other companies in the ecosystem. Eli Lilly and NVIDIA appear around several companies and partnerships. Merck-linked capital, Pfizer-linked investors and other pharmaceutical groups also show up across the market.

One of the clearest outside signals came when NVIDIA and Lilly announced that they would invest up to $1 billion over five years in a joint AI drug discovery lab. The plan connects AI models, compute, data generation and wet-lab experimentation inside one research system.

That kind of commitment helps explain the current venture pattern. Strategic companies increasingly see AI drug discovery as infrastructure they may use directly, rather than a distant technology to watch from the sidelines.

Is China becoming a real AI drug discovery funding hub?

Yes. China has become much more important in AI drug discovery funding, although a few huge rounds still drive a large part of the dollar jump.

China went from three deals to six. Its share of market capital increased from less than 1% to roughly 22%.

Earendil is the biggest reason. The company disclosed $787 million in financing rounds, immediately making it one of the largest transactions in our entire dataset. Syneron Bio added close to $100 million across its Series A and A+ financing and later closed a $150 million Series B.

There is genuine breadth behind those large figures because deal count doubled as well. Across Asia-Pacific, deal share moved from 13% to 24.1%.

North America still accounts for almost half of current deals, so it remains the largest region by company activity. Europe continues to attract huge amounts of capital too, especially because of Isomorphic. The geographic story today is less about one region replacing another and more about China becoming a serious third pool of AI drug discovery financing.

What are AI drug discovery companies actually raising money to do now?

The biggest AI drug discovery rounds are increasingly paying for full drug-development systems: stronger models, proprietary data, wet-lab loops, pipelines, clinical work and pharma deployment.

Isomorphic is scaling both its AI engine and drug pipeline. Earendil is expanding its platform while advancing biologics. Iambic is funding additional therapeutic programs after reaching the clinic. Tahoe Therapeutics raised $30 million around the creation of a huge perturbation dataset intended to train virtual-cell models and support precision drug discovery.

Boltz offers another version of the same trend. Its $28 million seed round came alongside a platform built around real biology and chemistry workflows and a multi-year Pfizer partnership. The funding proposition increasingly combines software, proprietary science, experimental feedback and a route into pharmaceutical R&D.

A few years ago, a company could attract attention mainly around a novel AI capability. Today, the strongest financings increasingly come with an answer to the next question: what drugs, experiments or pharmaceutical workflows does that AI actually produce?

We still have to be careful with this conclusion because use-of-funds disclosure is uneven across companies. The direction is much clearer among the large winners than across every financing in the market.

What really changed in AI drug discovery funding over the last 12 months?

AI drug discovery funding is stronger today, but the gains are concentrated around companies that have already shown they can turn AI into a serious drug-development platform.

The first major change is depth. Typical rounds are much larger, the $20 million-to-$50 million segment has expanded, and even an outlier-adjusted view shows meaningful funding growth. Investors are writing bigger checks across more than just the famous billion-dollar rounds.

The second change is who gets those checks. New-company formation has weakened while follow-on financing has become much more important. As pointed out above, first rounds are smaller and less frequent, whereas companies with existing funding histories can raise much larger amounts.

The third change is the Series B wave. This stage has become the main bridge between an interesting AI platform and a heavily financed drug-development company. That is where we now see some of the sharpest increases in both deal activity and capital.

The fourth change is where investors are placing their bets. De novo design absorbs most of the dollars, AI lead generation is gaining broader momentum, and lead optimization has lost a large amount of deal activity.

Finally, investors increasingly reward evidence that connects computation to the physical drug-development process. Pipelines, experimental loops, pharmaceutical collaborations and clinical progress appear repeatedly around the current winners.

The misleading headline would be that AI drug discovery funding simply exploded by 148%. The market has strengthened, but the better conclusion is narrower: far more money is available today for companies that have already convinced investors they can move from AI research toward actual medicines.