Absci

Absci is a clinical-stage biopharmaceutical company using an AI-native antibody discovery stack. Its core platform combines Origin-1, a generative design model, with lab-in-the-loop validation to design differentiated antibody therapeutics; the lead asset is ABS-201 (anti-PRLR) in alopecia/endometriosis, with ABS-202 added to the pipeline in 2026.

Absci is a clinical-stage biopharmaceutical company advancing antibody therapeutics designed with generative AI. Its platform pairs Origin-1 (de novo antibody design against novel epitopes) with a wet-lab, lab-in-the-loop validation cycle. The lead asset is ABS-201 (anti-PRLR) for pattern hair loss (PHL) and endometriosis; ABS-202 is a preclinical anti-PRLR program for an undisclosed indication.

Q2 2026 revenue $0.3M (XBRL RevenueFromContractWithCustomerIncludingAssessedTax = $318K for the quarter, $533K H1); R&D $22.6M; SG&A $9.2M; net loss $33.2M. Balance sheet at June 30, 2026: cash + equivalents $107.9M, current marketable securities $93.3M, total assets $268.9M, stockholders' equity $246.1M. Gross margin is not meaningful at pre-commercial scale; the company is entirely cash-funded via the June 2026 offering.

• monetization model: Collaboration/licensing revenue: upfront payments, funded research fees, milestones, royalties; no product sales. (10-K Business; sec.gov ; accession UNKNOWN)
• revenue mix: One reportable segment; collaboration/R&D services ~100% of revenue; product revenue 0%. (10-K Segment/Revenue notes; 10-Q Revenue; accession UNKNOWN)
• who pays: Pharma/biotech partners’ R&D budgets; not consumers, providers, or payers. (10-K Business)
• margin_value_capture: Negative gross margin and deeply negative operating margin; value expected from milestones, royalties, and internal pipeline, not current sales. (10-K MD&A/Revenue notes)

• customer classes: Pharma & Biotech

Absci Corporation (“Absci” or “the Company”) is a biotechnology company that combines synthetic biology, E. coli-based protein expression, and machine learning to discover and design biologic drugs, especially antibodies and other complex proteins. The Company went public in July 2021. Its ticker is ABSI.

The central commercial proposition is that Absci can reduce the time and cost of early drug discovery by generating, screening, and optimizing protein candidates in a high-throughput wet lab and then using the resulting internally generated data to train machine-learning models. Those models then propose new protein designs, including de novo antibody sequences, which are tested back in the wet lab. This creates a data flywheel.

The Company’s own regulatory filings should be treated as the authoritative source for segment reporting, customer concentration, and revenue recognition. The EDGAR company-search location for Absci is:

• SEC EDGAR — Absci Corporation filing index:

https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&company=Absci&type=10-K&dateb=&owner=include&count=40

Accessed 2026-05-09.

Exact accession number and filing date for the latest 10-K: needs primary source validation.

Absci does not appear to operate a diversified, multi-segment revenue structure in the way a large pharma or tools company might. The Company’s primary economic activity is research and development collaboration revenue from drug discovery partners. There may also be government grant revenue and immaterial product or technology-access fees, but the latest 10-K segment note is the controlling source.

Absci monetizes its platform primarily through collaboration agreements with pharmaceutical and biotechnology partners. The typical economic structure in AI-native drug discovery deals includes:

1. Upfront payment — cash paid upon signing.
2. Research and development funding — often paid to support Absci’s work on a partner target.
3. Milestone payments — paid when a program hits predefined discovery, preclinical, clinical, regulatory, or commercial milestones.
4. Royalties — paid on future net sales if a candidate becomes an approved medicine.
5. Option or license fees — paid when a partner licenses a program.

Absci’s publicly disclosed collaboration terms give a directional sense of this model, though the accounting treatment and revenue recognition timing must come from the 10-K.

Known public contract terms:

• AstraZeneca collaboration: Absci announced a strategic collaboration with AstraZeneca in December 2023. Publicly disclosed deal value was up to $247 million, including a $30 million upfront payment and up to $217 million in milestone payments, plus royalties on product sales.

Source: Absci press release dated on or around December 4, 2023.

Exact URL: needs primary source validation; navigate via https://www.absci.com/press-releases/.

Access date: 2026-05-09.

Tier: Tier 2 press release.

Cross-verification: needs primary source validation; would be strengthened by the 8-K or 10-Q revenue-recognition footnote.

• Merck collaboration: Absci announced a collaboration with Merck in January 2022. Publicly disclosed deal value was up to $610 million, including upfront and milestone payments, plus royalties.

Source: Absci press release dated on or around January 11, 2022.

Exact URL: needs primary source validation; navigate via https://www.absci.com/press-releases/.

Access date: 2026-05-09.

Tier: Tier 2 press release.

Cross-verification: needs primary source validation.

These disclosed headline values are not revenue. They are maximum potential payments if programs succeed. Revenue recognized in any period will be much smaller and will depend on progress toward milestones, cost-sharing arrangements, and contract duration.

Absci is an early-stage drug discovery platform company with high fixed costs in laboratory operations, personnel, and platform development. Reported gross margin is unlikely to be a useful profitability indicator because collaboration revenue is small while costs are substantial.

Absci sells primarily to:

1. Large pharmaceutical companies — these buyers have internal therapeutic targets but may seek external discovery technologies to access novel candidate space or improve speed.
2. Mid-cap and large-cap biotech companies — these buyers may lack internal protein engineering or AI capabilities and prefer an external partner.
3. Academic and nonprofit research institutions — possible but likely a smaller revenue source; may appear via grant revenue.
4. Government agencies — possible grant or public-health collaborations; revenue share likely small.

The economic buyer is typically:

• A VP or SVP of biologics discovery in a pharmaceutical company.
• A head of external innovation or search-and-evaluation group.
• A program leader for a difficult antibody or protein target.

The end user is the discovery scientist who needs better leads for a specific target, but the budget and contract authority sits higher in the organization.

The two clearest publicly disclosed counterparties are:

• Merck — collaboration announced January 2022.

Source: Absci press release, Tier 2.

URL: https://www.absci.com/press-releases/

Exact release URL: needs primary source validation

Access date: 2026-05-09.

• AstraZeneca — collaboration announced December 2023.

Source: Absci press release, Tier 2.

URL: https://www.absci.com/press-releases/

Exact release URL: needs primary source validation

Access date: 2026-05-09.

These are public deal counterparties, but the SEC filing itself is the authority on customer concentration. The latest 10-K may disclose that one or more of these companies accounted for more than 10% of revenue. That exact disclosure is needs primary source validation.

FY2025 revenue was $2.8M, down 38.24% from FY2024 revenue of $4.53M; gross margin was 100.00%, operating margin was -4,297.04%, and profit margin was -4,113.68% on StockAnalysis’ FY2025 view. In Q1 2026, revenue was $0.2M, R&D was $19.3M, SG&A was $9.1M, and net loss was $29.6M. Cash and marketable securities were $125.7M as of March 31, 2026.

Q2 2026 (ended June 30, 2026, 10-Q filed Aug 11, 2026) revenue was $0.3M vs $0.6M in Q2 2025 — the company is pre-commercial and earns only nominal collaboration revenue. R&D was $22.6M (vs $20.5M YoY) and SG&A $9.2M; net loss was $33.2M for the quarter and $62.8M for H1 2026. Cash, cash equivalents, and marketable securities were $201.1M at June 30, 2026, up from $125.7M at March 31, 2026.

The bottleneck is not “AI” in the abstract; it is whether Absci can repeatedly compress antibody discovery from target concept to IND with enough speed and capital efficiency to matter. Management’s own numbers imply a materially lower cost/time path than conventional discovery, which is the scarce economic lever in antibody platform biotech.

The investable bottleneck is whether Absci's generative-AI + wet-lab loop can repeatedly compress antibody discovery from target to IND (management's 10-K claim: ~2 years and ~$15M per program vs an industry 4–6 years and >$50M). If that compression is real and repeatable, it is a scarce economic lever in antibody platform biotech; the Q2 2026 quarter delivered a stronger external validation of exactly that claim.

• 10-K Item 1 says Absci advanced its first two programs from AI design to IND (or foreign equivalent) in around two years at approximately $15M per program, versus an industry average of 4–6 years and more than $50M per program.
• 10-Q / Q1 2026 results show $125.7M of cash + marketable securities at March 31, 2026, versus a $29.6M net loss for the quarter; at that pace, the current balance implies roughly 4.25 quarters of net-loss runway before any new financing.
• June 24, 2026 EX-99.1 says ABS-201’s estimated half-life is at least 65 days, supporting a potential dosing interval of two or three injections over a six-month period.
• June 24, 2026 EX-99.1 says the first MAD cohort of AGA participants was initiated and interim proof-of-concept data is expected in the second half of 2026, with full proof-of-concept in early 2027.
• May 7, 2026 EX-99.1 says all four planned SAD cohorts were dosed and emerging safety data remained favorable; preliminary PK modeling supported a targeted dosing interval of two or three injections over six months.

• Q2 2026 10-Q / EX-99.1 (Aug 11, 2026): cash, cash equivalents, and marketable securities of $201.1M; management states this is "sufficient to fund operations into the second half of 2028."
• EX-99.1: completed a $100M underwritten offering including a $40M strategic equity investment from Eli Lilly, alongside Adage, BVF Partners, Columbia Threadneedle, Invus, and Redmile.
• EX-99.1: the Lilly partnership "is tailored around the clinical development strategy for ABS-201, and does not confer any program rights to Eli Lilly"; a Lilly representative joined Absci's Endometriosis Advisory Board.
• EX-99.1: ABS-201 interim Phase 1 data show an estimated half-life of at least 65 days, supporting two-or-three injections over a six-month period.
• EX-99.1 catalysts: interim proof-of-concept (PoC) data for PHL expected H2 2026; full 26-week readout early 2027; Phase 2 endometriosis trial initiation Q4 2026 with potential PoC H2 2027.
• Origin-1 was presented at RosettaCon 2026 as "a Generative AI Platform for De Novo Antibody Design Against Novel Epitopes"; a mAbs 2026 paper covers "efficient inference of non-polyreactive antibody variants dependent on local fine-tuning."

Two calculations. (1) Runway: $201.1M cash + marketable securities ÷ $33.2M Q2 net loss = ~6.1 quarters ≈ 18 months, implying ~Dec 2027 at current burn; management's "into H2 2028" implies an effective burn nearer ~$25M/quarter, i.e. a ~25% moderation assumption that is not yet proven. (2) Platform economics (10-K): ~$15M per program vs industry >$50M, and ~2 years vs 4–6 years = roughly a 70% cost and 50–67% time compression. The binding constraint is efficacy, not financing: the entire thesis now hangs on the H2 2026 interim PoC and early 2027 full 26-week readout converting that compression into a durable efficacy signal.