Insilico Medicine pricing

About

Insilico Medicine is an end-to-end, generative-AI drug-discovery company headquartered in Hong Kong with a major presence in New York and R&D in mainland China. It is unusual in the AI-biotech field because it runs three businesses at once: (1) Pharma.AI, a software platform that pharma companies license to discover and design drugs; (2) an internal drug pipeline of AI-discovered, AI-designed molecules it advances through the clinic; and (3) a network of outcome-based partnerships in which it co-develops or out-licenses programs to larger pharma in exchange for upfront fees, milestones and royalties. A 6th-generation fully-automated “Life Star” robotics lab in Suzhou’s BioBAY closes the loop between AI prediction and wet-lab validation.

That three-headed model produces a genuinely hybrid pricing posture, which is what makes this page different from the rest of the embodied/physical-AI cohort (most of which — see Physical Intelligence or Essential AI — publish nothing at all). Insilico’s headline software products (PandaOmics for target discovery, Chemistry42 for generative chemistry, inClinico for clinical-trial-outcome prediction) are sales-led and quote-only: there is no company-wide rate card, insilico.com/pricing returns a 404, and each module’s only call-to-action on pharma.ai is “Contact Us” (pharma.ai@insilicomedicine.com). But one product breaks the pattern — Science42:DORA, an AI scientific-writing assistant, ships with a public price grid and a free trial you can buy self-serve.

Commercially, Insilico is now a public company. It completed Hong Kong’s largest biotech IPO of 2025 (~US$293M, listed 30 December 2025) and reported US$56.24M of 2025 revenue with software revenue up 23.8% YoY and subscription customers up 18.3% YoY — while its cumulative partnership value reached US$4.6 billion, dwarfing current revenue and signalling that the real economics live in future milestones. Its lead drug, Rentosertib (ISM001-055), a TNIK inhibitor for idiopathic pulmonary fibrosis, became the first medicine with both an AI-discovered target and an AI-designed molecule to post positive Phase IIa data (published in Nature Medicine). This page documents what Insilico actually publishes — the DORA price grid, the quote-only platform, and the milestone-shaped partnership economics — and never invents the prices it keeps behind sales.

Pricing summary : a gated platform, one self-serve SKU, and milestone pharma deals

Insilico runs three pricing models in parallel, which is why it lands as gated rather than fully sales-only:

• Core Pharma.AI software (quote-only / sales-led) — PandaOmics, Chemistry42 and inClinico are licensed to pharma and biotech R&D teams with no public price. pharma.ai describes “flexible business models — stand-alone technology access or combine our software with Pharma.ai collaborations,” and routes every module to “Contact Us.” This is the platform’s main subscription-revenue surface (software revenue grew 23.8% YoY in 2025), but the rate card is private.
• Science42:DORA (self-serve subscription) — the one product with a public price: a free 7-day / 3-document trial (no card), Professional at $35/mo or $350/yr (often shown at a promo $17/$175, up to 10 generations/month), Advanced at $500/yr (promo $250, unlimited generation), and a custom Enterprise tier (“Let’s Connect”). An open-source self-host build is on GitHub for teams who bring their own LLM keys.
• Drug-discovery partnerships (outcome-based) — the pipeline and out-licensing deals are priced as upfront + milestones + royalties, not subscriptions. Named terms include Sanofi (US$32M upfront, up to ~US$888M total) and pipeline out-licensing to Fosun Pharma, Exelixis and Menarini collectively valued over US$2.1 billion.

What makes this different: unlike a pure AI-biotech research lab such as Isomorphic Labs — which sells nothing self-serve and lives entirely on partnership milestones — Insilico straddles two worlds: a real (if mostly quote-only) SaaS subscription business and an outcome-based pharma model. The price you can read is DORA’s; the prices you can’t are the platform license and the milestone schedule.

Pricing by product

Sales motions across products: sales-led for the core platform and partnerships (the bulk of value); self-serve for Science42:DORA Free/Professional/Advanced. The open-source DORA build is a self-host download governed by its license, not a commercial SKU.

Hidden costs : What Insilico Medicine users actually pay

Because only one product has a public price, the “real bill” depends entirely on which door you walk through.

Path 1 — licensing the platform (PandaOmics / Chemistry42 / inClinico). Everything is in the quote. There is no published floor, no per-seat sticker, and no worked example, so a buyer cannot estimate cost without a sales conversation. The hidden cost is evaluation friction: scoping, a custom contract, and likely a services/collaboration component. Insilico explicitly offers “stand-alone technology access or combine our software with Pharma.ai collaborations,” meaning the line between a software subscription and a co-development deal is itself negotiated.

Path 2 — buying Science42:DORA. Here the costs are visible: $35/mo (or $350/yr) for Professional, $500/yr for Advanced, free trial up front. The one wrinkle is the generation cap — Professional includes up to 10 generations/month, so heavy users are pushed to Advanced’s unlimited tier. If you take the open-source self-host route instead, DORA itself is free but you pay your own LLM API bill (your model provider’s per-token cost), which lives entirely outside Insilico’s pricing.

Path 3 — a drug-discovery partnership. The “cost” is structurally different: a partner pays an upfront fee plus milestones that trigger as a molecule advances (R&D, regulatory, commercial) plus royalties. The headline “up to $888M” figures are potential — most of that value only lands if the drug succeeds, so the effective price is contingent on outcomes.

Want to model the moving parts? DORA’s per-seat tiers are public, but the platform and milestone economics aren’t — sketch scenarios with the Insilico Medicine pricing calculator, and if you’re self-hosting DORA on your own model, compare hosted token rates in the AI token pricing tracker.

Pricing evolution : Insilico Medicine pricing history and changes

Insilico’s pricing story is one of a quote-only platform that slowly added a single self-serve SKU (DORA) while its real value migrated into partnership milestones. The milestones below are reconstructed from primary announcements and a live 2026-06-14 site check.

Cadence

Tracked range: 2024 Q3–2026 Q2. The core platform has never carried a public price; the only published-price event is DORA’s launch. Quarters not listed had no relevant public pricing event.

Notable changes

• 2024-07 — Science42:DORA launches as Insilico’s first self-serve-priced product, with a free trial and a public Professional/Advanced/Enterprise grid (news-medical).
• 2025-03 — $110M Series E; the core Pharma.AI modules remain quote-only (PR Newswire).
• 2025-12-30 — Hong Kong IPO (~US$293M), largest HK biotech listing of 2025; FY2025 software revenue +23.8% YoY, subscription customers +18.3% YoY, US$4.6B cumulative collaboration value (FY2025 results).
• 2026-06-14 — Live check confirms the hybrid posture: insilico.com/pricing 404s; PandaOmics/Chemistry42/inClinico are “Contact Us”; DORA still publishes Free / $35-mo Professional / $500-yr Advanced / custom Enterprise with self-serve checkout.

What’s unique : Insilico Medicine’s distinctive pricing mechanics

1. One company, three pricing models. Insilico simultaneously runs a quote-only software subscription (PandaOmics/Chemistry42/inClinico), a self-serve subscription (Science42:DORA), and an outcome-based partnership model (upfront + milestones + royalties). Few companies in any corpus span subscription and outcome-based pricing this cleanly — the choice of model tracks the fungibility of the thing being sold: a writing tool is a commodity (publish a price), a drug-discovery engine is bespoke (quote it), a future molecule is contingent (price it on outcomes).

2. The published price is the least valuable product. DORA — the one SKU with a sticker — is a scientific-writing assistant, a peripheral tool. The crown jewels (the discovery platform and the pipeline) carry no public price at all. The visible price ($35/mo) is two-and-a-half orders of magnitude below the invisible one (an ~$888M Sanofi deal). The transparency is inversely correlated with the value.

3. Value lives in milestones, not revenue. With US$4.6B of cumulative collaboration value against US$56.24M of 2025 revenue, Insilico’s “price” is overwhelmingly future-contingent — money that only arrives if AI-designed molecules clear clinical and regulatory bars. This is the defining feature of outcome-based AI-biotech economics: you don’t sell a unit, you sell a share of a future result. (For how to choose a metric when the deliverable is an outcome rather than a unit, see choosing the right usage metric.)

Strengths & weaknesses

Billing UX : Insilico Medicine billing controls and transparency

• Billing controls — Public only for Science42:DORA, which has self-serve sign-up, a free trial, and “Get now” checkout for Professional/Advanced. The core platform has no self-serve dashboard or public billing portal; commercial terms run through sales.
• Usage visibility — DORA exposes a clear meter (Professional includes up to 10 generations/month; Advanced is unlimited), so users can see when they’re hitting the cap. Platform usage metering for PandaOmics/Chemistry42/inClinico is handled inside the licensed product and contract, not on a public surface.
• Payment options — DORA takes self-serve payment (card) for its monthly/annual plans. Platform licenses and partnerships are invoiced under custom enterprise contracts negotiated with sales.
• Transparency — Mixed by design: high for DORA (full public grid + free trial), low for the platform (Contact Us, no rate card), and disclosed-in-aggregate for partnerships (deal totals are press-released, but per-deal milestone schedules are not).

Strategic wins : Why Insilico Medicine’s pricing decisions worked

1. Match the model to the fungibility of the product

Insilico publishes a price for the commodity (a writing assistant) and quotes the bespoke (a discovery platform, a drug program). That discipline lets DORA capture self-serve demand without forcing the platform into a rate card that would invite line-by-line comparison with cheaper point tools. It’s a textbook application of matching transparency to fungibility.

2. Outcome-based deals align price with proof

By pricing partnerships as upfront + milestones + royalties, Insilico shares risk with pharma partners and only captures the big numbers when molecules actually advance. The Sanofi structure (US$32M upfront, up to ~US$888M total) is the model in miniature: a modest guaranteed payment plus a large contingent upside. This is exactly the outcome-based shift reshaping AI monetization, applied to drug discovery.

3. A self-serve on-ramp inside a sales-led company

DORA gives Insilico something most AI-biotech peers (Isomorphic Labs) lack: a product a stranger can buy without a meeting. A free trial and a $35/mo tier seed the funnel with researchers who may later pull the platform into their org — a low-cost distribution flywheel layered on top of an otherwise enterprise sales motion. Related: how AI companies are rethinking what they meter.

Areas to improve : Gaps in Insilico Medicine’s pricing approach

1. Give the platform a public anchor

A 404 pricing page for the flagship products maximizes evaluation friction. Even a “starts at” figure, a worked example, or a one-line description of how PandaOmics/Chemistry42 licenses are structured (per seat? per target? per program?) would let mid-market biotechs self-qualify instead of bouncing to a sales call. Total opacity invites the cost-unpredictability anxiety that slows enterprise buyers.

2. Clarify the DORA self-host cost story

The open-source self-host build is a genuine asset, but “free” quietly relocates cost onto the user’s own LLM API bill. Clear guidance on expected token cost (or a first-party hosted option with a published rate) would make the open release more usable and convert more self-hosters into paid seats.

3. Separate “collaboration value” from realized revenue

Headline figures like US$4.6B cumulative collaboration value mix booked revenue with contingent milestones. More explicit disclosure of realized vs potential value would help buyers and investors understand the true price-to-outcome ratio — and reduce the gap between a US$56.24M revenue line and billions in announced deals.

Key takeaways

1. It’s a true hybrid, not sales-only. Insilico is gated, not fully opaque: PandaOmics/Chemistry42/inClinico are quote-only, but Science42:DORA publishes real self-serve prices (free trial, $35/mo Professional, $500/yr Advanced).
2. The published price is the peripheral product. The one SKU with a sticker is a writing assistant; the valuable platform and pipeline carry no public price — transparency is inversely correlated with strategic value.
3. Real money is in milestones, not subscriptions. US$4.6B of cumulative collaboration value dwarfs US$56.24M of 2025 revenue; the effective “price” is contingent on AI-designed molecules succeeding in the clinic.
4. Outcome-based deals share risk. Partnerships pay upfront + milestones + royalties (e.g. Sanofi $32M upfront, up to ~$888M total) — the buyer pays as the molecule proves out.
5. A self-serve SKU is a distribution flywheel. DORA’s free trial and low monthly price give an enterprise-sales-led company a rare bottom-up on-ramp into research teams.

UBP implications

1. Match transparency to fungibility. Insilico publishes a price for the commodity (DORA) and quotes the bespoke (platform, pipeline). UBP designers should meter-and-publish fungible products and quote-and-conceal bespoke outcomes — the same company can do both.
2. Outcome-based pricing turns “price” into a milestone schedule. When the deliverable is a future result (a drug that works), the right “meter” is regulatory and commercial milestones plus royalties, not seats or tokens. Aligning payment with proof is the core of outcome-based monetization.
3. “Free” relocates cost; say where it lands. DORA’s open-source self-host is free to Insilico but bills the user’s own LLM API. UBP practitioners should be explicit about where a $0 headline’s real cost actually sits, or risk eroding trust when the buyer’s model invoice arrives.

Sources

• Insilico Medicine — official site (accessed 2026-06-14)
• insilico.com/pricing — returns HTTP 404 (no company-wide rate card) (accessed 2026-06-14)
• Pharma.AI platform hub — PandaOmics / Chemistry42 / inClinico, “Contact Us” CTAs (accessed 2026-06-14)
• Science42:DORA — public price grid (free trial, Professional, Advanced, Enterprise) (accessed 2026-06-14)
• Insilico Medicine — FY2025 annual results (revenue, software growth, collaboration value) (accessed 2026-06-14)
• Insilico ends 2025 with $293m Hong Kong IPO (pharmaphorum) (accessed 2026-06-14)
• Insilico adds Sanofi to partnership roster with $888m deal (pharmaphorum) (accessed 2026-06-14)
• Rentosertib Phase IIa IPF results in Nature Medicine (PR Newswire) (accessed 2026-06-14)
• Insilico Medicine unveils Science42:DORA (news-medical) (accessed 2026-06-14)
• Browse the pricing blueprint corpus

Bottom line

Insilico Medicine is the embodied/physical-AI cohort’s clearest hybrid: a generative-AI drug-discovery company that prices three ways at once. Its flagship Pharma.AI software (PandaOmics, Chemistry42, inClinico) is quote-only — insilico.com/pricing 404s and every module says “Contact Us” — yet one product, Science42:DORA, breaks ranks with a fully public, self-serve grid (free trial, $35/mo Professional, $500/yr Advanced). Meanwhile the real economics live in outcome-based pharma deals (upfront + milestones + royalties), where cumulative collaboration value of US$4.6B dwarfs US$56.24M of 2025 revenue. The published price is the peripheral one; the valuable products stay behind sales and the pipeline pays out only on success — a textbook case of matching the pricing model to the fungibility of what’s being sold.

Want to compare Insilico against the AI-biotech peer that publishes nothing? See Isomorphic Labs, or browse the full pricing blueprint.