By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel consensus is bearish on Absci (ABSI), citing high dilution risk due to repeated equity raises, uncertain timeline compression and success rates for AI-designed biologics, and potential regulatory hurdles.
Risk: High dilution risk due to repeated equity raises required to fund clinical development and potential regulatory hurdles.
Opportunity: Potential partnership expansion and market mispricing of nonlinear platform payoffs.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Absci uses generative AI to design protein drugs before they are tested in a lab.
Partnerships with Merck and Owkin validate Absci's hybrid AI-wet-lab drug platform.
Long-term upside with this ticker depends on clinical success, royalties, and AI platform scalability -- it is worth the risk.
If I had to pick one artificial intelligence (AI) stock to buy today, bury in a time capsule, and not peek at again until 2036, I wouldn't choose a chip designer or a model-maker. I wouldn't choose Nvidia, Nebius Group, or any other sexy, hot name right now. Those businesses are great, but they operate in a world where the technology frontier shifts every year and competition is relentless.
The one I'd pick is a company quietly trying to change how we discover medicines in the first place. That company is Absci Corp. (NASDAQ: ABSI).
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Absci bills itself as a "data-first generative AI drug creation company," which sounds like buzzword soup until you dig into what it actually does. Instead of starting with a promising molecule and then testing it endlessly in the lab, Absci starts with a disease target and uses generative AI to design potential protein-based drugs in silico -- on the computer -- before they ever hit a petri dish.
Its Integrated Drug Creation platform combines deep learning models with a high-throughput wet lab, enabling it to both design and experimentally validate its AI-created drug candidates. Absci's long-term vision is deceptively simple: Go from a target to a viable biologic drug sequence "with the click of a button," and then iterate until the candidate has the right mix of potency, safety, and manufacturability. To me, that's the kind of ambition that makes sense on a 10-year-plus timeline, not a 10-quarter one.
This isn't a new pivot. Years ago, Absci acquired Denovium, a deep-learning company that uses AI to accelerate advances in biopharmaceutical research and gene discovery and folded that technology into what is now its AI engine. The company has been building toward this moment for a while.
You can learn a lot about a small company by looking at who chooses to work with it. Absci's partner list is unusually strong for its size, spanning big pharma, technology-driven biology companies, and top-tier academic centers.
Back in 2022, Absci announced a research collaboration with Merck to apply its platform to new biologic candidates -- a vote of confidence from one of the most sophisticated research and development (R&D) organizations in the world. In 2023, it signed a strategic R&D partnership with PrecisionLife to co-develop potential therapeutics in complex chronic diseases, explicitly linking PrecisionLife's computational patient stratification with Absci's AI drug design engine.
In early 2025, Absci teamed up with Owkin, another technology-driven biology company using advanced AI to unlock difficult drug targets, to co-develop immuno-oncology and immunology candidates by combining both companies' platforms. Owkin describes its own work as "agentic AI" for biology, which makes this pairing feel less like a simple licensing deal and more like two specialized tools being welded together into a larger system.
Absci isn't just a services shop. It's also advancing its own pipeline of AI-designed biologic drug candidates as a clinical-stage biopharmaceutical and healthcare company. That dual identity matters as we look ahead to 2036: If even one homegrown program makes it through the clinical maze, the upside isn't just milestone payments from partners, it's potential royalty or product economics on a drug the platform designed from scratch.
The company's messaging has shifted toward "breakthrough therapeutics designed with generative AI," a subtle but important change from being just a discovery partner. It suggests management is deliberately keeping some of the best shots on goal in-house rather than monetizing everything through collaborations.
I'd be lying if I said there wasn't a real risk here. Drug discovery is brutal. Some of Absci's partnerships have their flaws, and many programs fail late. Regulatory standards are high, as they should be. And layering AI on top of biology doesn't magically remove any of that. Absci will likely issue more shares over time to fund its operations, and some investors will never be comfortable with that.
But this is exactly why I'd frame Absci as a time capsule stock. In my view, the market is structurally poor at valuing platforms whose payoffs are nonlinear and far in the future. It can price a single drug just fine; it struggles to price a system that could, in theory, generate dozens of drugs over a decade. Right now, Absci looks like a small, speculative AI biotech with an interesting story. By 2036, it will either be a much larger company with a network of royalty streams and owned products flowing from its platform, or an expensive lesson in why biology resisted another wave of technological optimism.
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Micah Zimmerman has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Merck and Nvidia. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"High clinical failure risk and ongoing dilution make ABSI unsuitable as a passive 2036 hold despite partnership headlines."
The article positions Absci (ABSI) as a long-horizon AI platform play in biologics, citing Merck and Owkin partnerships plus its Integrated Drug Creation model. Yet clinical-stage biotechs routinely burn cash for years before any royalty stream materializes, and generative-AI drug design still lacks Phase 3 proof that in-silico candidates outperform traditional discovery on attrition rates. ABSI will likely need repeated equity raises, diluting holders before 2036 payoffs. The 10-year framing masks near-term binary events around pipeline data and partnership expansion that the market prices harshly.
If Absci's AI-wet-lab loop demonstrably cuts discovery timelines by 50% and one in-house candidate reaches approval with meaningful royalties, the platform valuation could compound far beyond typical biotech multiples.
"Absci is a platform bet dressed up as a partnership validation story, but partnerships with pharma giants typically signal 'interesting but not core' rather than 'breakthrough,' and the company has zero clinical proof that AI actually de-risks or accelerates human drug development."
The article conflates platform potential with execution certainty. Absci's partnerships with Merck and Owkin are real validation, but the piece glosses over brutal biotech math: even with AI acceleration, clinical attrition rates remain ~90%. The 2036 framing is rhetorical cover for a speculative bet on a pre-revenue platform with no approved drugs. The dual model (services + pipeline) is sensible but creates two failure modes instead of one. Share dilution is mentioned dismissively but will likely be substantial. The article's strongest claim—that markets misprice nonlinear platform payoffs—is true. Its weakest: that Absci's platform is proven to compress timelines or improve success rates in humans, not just in silico.
If AI-designed biologics were truly transformative, Merck wouldn't need Absci as a partner—it would acquire them or build in-house; the fact that Merck licenses rather than owns the platform suggests even big pharma views this as unproven and optionality-cheap, not a must-have.
"Absci's long-term valuation is tethered to the unproven assumption that AI-designed biologics will face higher clinical success rates than industry-standard discovery pipelines."
Absci (ABSI) represents a classic 'platform-as-a-service' gamble in the high-stakes biotech sector. While the integration of generative AI with proprietary wet-lab validation is theoretically sound, the article glosses over the 'Valley of Death' inherent in clinical development. Even with Merck as a partner, Absci is essentially a cash-burn machine that will require significant capital raises before reaching any meaningful royalty inflection point. Investors are betting on the platform's efficiency, but biology remains notoriously non-linear and resistant to purely computational optimization. If the platform doesn't significantly shorten the time-to-clinic compared to traditional methods, the equity dilution will likely overwhelm any long-term upside.
The primary risk is that Absci's AI models may optimize for 'computational elegance' rather than actual biological efficacy, leading to high-tech failures that are just as expensive as traditional ones.
"Absci's long-term upside depends on a sequence of breakthroughs that may never materialize, making the 2036 payoff a high-variance bet."
Absci’s vision of 'programmable biology' via AI-assisted drug design paired with a wet-lab accelerator is compelling on paper, but the core KRI is still clinical success. The strongest risk the article glosses over is the chamber of biotech failure: most AI-designed biologics fail in late-stage trials or never reach profitability, and partnerships with Merck or Owkin may simply fund early exploration rather than deliver marketable products. Even if a program progresses, royalties and in-house products require long, expensive trials and regulatory approvals, with high dilution pressure from equity raises. In a 2036 world, the payoff hinges on a handful of breakthroughs that may never materialize.
The time horizon obscures near-term dilution risk and the reality that most AI-driven drug candidates never reach commercialization; even a few successes could be licensed away, capping upside for shareholders.
"Extra regulatory scrutiny on AI-designed candidates could nullify any discovery acceleration and intensify dilution."
Gemini's computational-elegance risk links directly to Grok's 50% timeline claim: regulators may demand extra preclinical or early-clinical validation for AI-generated sequences, erasing speed gains and extending cash burn. No one has flagged this FDA friction layer, which would compound the dilution all three already flagged even if Merck expands the collaboration.
"Regulatory validation demands for AI-designed drugs may negate computational speed gains, compounding dilution risk on Absci's in-house pipeline."
Grok's FDA friction layer is real but incomplete. The deeper issue: AI-designed biologics may face *comparative* scrutiny—regulators demanding head-to-head data versus traditional methods to justify the speed claim. That's not just timeline erosion; it's a validation tax Absci hasn't priced in. Merck partnership masks this because Merck absorbs regulatory risk. But Absci's in-house pipeline has no such buffer. One failed IND or CTA delay explodes the 2036 thesis.
"Absci faces severe human capital risk, as its platform's success depends on a specialized, expensive workforce that creates unsustainable burn rates."
Claude and Grok are focused on regulatory friction, but they miss the real bottleneck: talent attrition. AI-integrated biotech relies on a rare, expensive hybrid workforce—computational biologists who understand wet-lab constraints. If Absci’s burn rate is high, it’s likely tied to human capital, not just hardware. This isn't just about FDA validation; it’s about the 'key person' risk inherent in a platform company that hasn't yet institutionalized its proprietary knowledge into a truly autonomous, scalable engine.
"Absci's upside depends on turning tacit wet-lab know-how into a scalable moat; without that, it's a cash-burn services/pipeline bet, not a durable platform."
Grok is right to flag FDA/friction as a headwind, but the bigger stock-agnostic risk is the moat. Without codifying tacit wet-lab know-how into a scalable, self-improving engine, Absci remains a services-plus-pipeline bet, not a durable platform. Partnerships can delay dilution, but they don’t create a data flywheel or IP franchise that compounds revenue. In that setup, near-term rollups and equity raises stay probable even if INDs come through.
The panel consensus is bearish on Absci (ABSI), citing high dilution risk due to repeated equity raises, uncertain timeline compression and success rates for AI-designed biologics, and potential regulatory hurdles.
Potential partnership expansion and market mispricing of nonlinear platform payoffs.
High dilution risk due to repeated equity raises required to fund clinical development and potential regulatory hurdles.