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Research · head to head

Schrodinger vs TetraScience

Schrodinger logo

Schrodinger

Research

Physics based molecular modelling and drug discovery software, licensed by token pool

From
On request
Rated
-
Full reviewWebsite
TetraScience logo

TetraScience

Research

Scientific data cloud that harmonises instrument output across the lab estate

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Schrodinger licences are sold as token pools rather than unlimited module access, so a department can be blocked mid campaign because colleagues are consuming concurrency, and expanding the pool is a new commercial negotiation rather than a setting.; TetraScience pricing is scoped on connected instruments and data engineering effort rather than a published unit, so the cost of adding a new laboratory or an acquired site is impossible to forecast without going back to the vendor.
  • They diverge on capability: Schrodinger covers Maestro, TetraScience covers Instrument connectors.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Schrodinger and TetraScience actually diverge.

Attributes where Schrodinger and TetraScience differ
AttributeSchrodingerTetraScience
PlatformsLinux, macOS, Windows, WebWeb, Cloud, API

Identical on both: starting price (On request), pricing model (quote), free tier (No), user rating (Not yet rated), category (Research).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Schrodinger

  • Maestro
  • Glide
  • FEP+
  • Desmond
  • Jaguar
  • LiveDesign
  • Materials Science suite

Only in TetraScience

  • Instrument connectors
  • Tetra Data harmonisation
  • Cloud-native data platform
  • GxP package
  • Scientific applications
  • Data provenance
  • Open access
  • AWS Marketplace availability

What people use each for

The jobs each tool is most often brought in to do.

Schrodinger

  • A medicinal chemistry programme using FEP+ to prioritise which analogues to synthesise, where avoiding a handful of wasted syntheses pays for the licencenot TetraScience
  • A structure based design campaign that needs docking at scale against a target with a good crystal structurenot TetraScience
  • A materials group modelling polymer or electrolyte properties before committing to formulation experimentsnot TetraScience
  • A university modelling group that qualifies for the published academic site licence and needs Maestro across a teaching and research cohortnot TetraScience

TetraScience

  • A pharmaceutical company trying to make twenty years of chromatography data usable for modelling rather than trapped on instrument workstationsnot Schrodinger
  • A biotech building machine learning models on assay data that currently requires manual export from every instrumentnot Schrodinger
  • A quality control laboratory needing instrument data captured with provenance and audit trail for regulated usenot Schrodinger
  • A company consolidating data from acquired sites where each site runs a different instrument vendor and informatics stacknot Schrodinger

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Schrodinger

  • Licences are sold as token pools rather than unlimited module access, so a department can be blocked mid campaign because colleagues are consuming concurrency, and expanding the pool is a new commercial negotiation rather than a setting.
  • Commercial pricing is not published and is negotiated against modules, cores and term, so two companies of similar size can pay very different amounts and neither can benchmark the other.
  • FEP+ needs substantial GPU capacity that is not included in the licence, so the real annual cost includes cloud or on premise hardware that often rivals the software line item.
  • The tools require trained computational chemists to produce trustworthy results, and an organisation without that function will generate predictions it cannot interpret or defend to its own medicinal chemists.
  • Schrodinger runs its own internal drug discovery pipeline alongside selling software to discovery companies, and some prospective customers treat that dual role as a conflict when discussing proprietary targets, which slows procurement even where contractual separation exists.

TetraScience

  • Pricing is scoped on connected instruments and data engineering effort rather than a published unit, so the cost of adding a new laboratory or an acquired site is impossible to forecast without going back to the vendor.
  • Value depends entirely on connector coverage for your actual instrument estate; an instrument type without an existing productised connector becomes a services engagement with its own timeline and cost.
  • The GxP package is a separate annual subscription rather than an included capability, so a company that starts in research and later needs regulated use faces an additional commercial line and a validation exercise.
  • It is infrastructure with no end-user application of its own, so the business case rests on downstream analytics and AI work that has to be resourced and delivered separately before anyone sees a benefit.
  • Deployment is a multi-year programme touching instruments, networks, validated systems and site IT, and organisations consistently underestimate the internal effort required from people who also have day jobs running the laboratory.

Pricing, plan by plan

Schrodinger

On request
  • Commercial licence$undefined/year
    • Quoted per customer against modules, cores and licence term
    • Applications draw from a shared token pool that caps concurrency
    • GPU compute for FEP+ and Desmond is a separate cost, on premise or cloud
  • Academic site licence$undefined/year
    • Published academic entry around 7,500 USD a year for a premium package with a token allocation
    • Restricted to academic and research use, not work supporting a commercial enterprise
    • Maestro generally unrestricted with tokens shared for compute heavy applications

TetraScience

On request
  • Tetra Scientific Data Cloud$undefined/year
    • Priced on number of instruments connected and scope of data engineering
    • Contract entitles a specified quantity of use for its duration
    • Multi-year enterprise agreements are the norm
  • Tetra GxP package$undefined/year
    • Separate annual subscription executed within the licence agreement
    • Audit trail, data provenance, control matrices and software hazard analysis
    • Disaster recovery provisions

Which should you pick?

Choose Schrodinger if

  • You need maestro.
  • You work on Linux, macOS, Windows, Web.
  • You also want glide.
Schrodinger review

Choose TetraScience if

  • You need instrument connectors.
  • You work on Web, Cloud, API.
  • You also want tetra data harmonisation.
TetraScience review

Questions people ask

Is Schrodinger or TetraScience better?
Neither clearly leads. Schrodinger starts at On request and TetraScience at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Schrodinger or TetraScience?
Schrodinger starts at On request and TetraScience at On request.
Does Schrodinger or TetraScience run on more platforms?
Schrodinger runs on Linux, macOS, Windows, Web. TetraScience runs on Web, Cloud, API.
What is Schrodinger best used for?
Schrodinger is most often used for a medicinal chemistry programme using fep+ to prioritise which analogues to synthesise, where avoiding a handful of wasted syntheses pays for the licence, a structure based design campaign that needs docking at scale against a target with a good crystal structure, a materials group modelling polymer or electrolyte properties before committing to formulation experiments, a university modelling group that qualifies for the published academic site licence and needs maestro across a teaching and research cohort. Of those, a medicinal chemistry programme using fep+ to prioritise which analogues to synthesise, where avoiding a handful of wasted syntheses pays for the licence and a structure based design campaign that needs docking at scale against a target with a good crystal structure are not what TetraScience is typically brought in for.
What can Schrodinger do that TetraScience cannot?
Schrodinger covers Maestro, Glide, FEP+, Desmond. TetraScience covers Instrument connectors, Tetra Data harmonisation, Cloud-native data platform, GxP package.

Answered from the vendors’ own pages

Schrodinger: How is Schrodinger software licensed?

Annual licences with a shared token pool. Tokens cap how much you can run at once rather than which modules you own outright.

TetraScience: What is the pricing unit?

Connected instruments and the scope of data engineering, over a fixed contract term. There is no published per-seat or per-gigabyte rate.

Schrodinger: Is there published pricing?

Only for academic site licences, which start around 7,500 USD a year for a premium package. Commercial pricing is quoted.

TetraScience: Does it replace my ELN or LIMS?

No. It sits underneath them, harmonising instrument data and making it available to whatever applications you already run.

Schrodinger: Do I need my own GPUs?

For FEP+ and Desmond in practice yes, or cloud GPU capacity. Compute is not included in the licence.

TetraScience: Is it usable in a GxP environment?

Yes, with the separately subscribed Tetra GxP package. It reduces validation effort substantially but does not eliminate your validation obligation.

Schrodinger: Does Schrodinger compete with its customers?

It runs its own drug pipeline as well as selling software. It manages this through contractual separation, but buyers with sensitive targets should raise it during procurement.

TetraScience: Can I get the harmonised data out?

Yes. Tetra Data is designed to be accessible to your own analytics tools rather than confined to the platform.

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