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AI for life sciences

Life sciences. Done by the model.

Life sciences spans drug discovery, clinical development, and manufacturing — three workflows that traditionally use three software stacks with three governance regimes. Aether handles all three on one substrate. Drug-discovery agents propose and screen molecules. Clinical agents handle trial design and biostatistics. CMC and manufacturing agents handle process development, scale-up, and quality control.

Discovery → CMC
one substrate
ALCOA+ / 21 CFR 11
ready
GxP-compatible
deploys
The AI, animated

What the model actually computes.

These are the workloads the AI runs in life sciences — rendered live in SVG. Each panel is the geometry the model is reasoning about, the physics it solves for, and the validation it lands against measured reality.

01 · Live SVG
Drug discovery — docked ligand
ΔG = −9.2 kcal/mol · FEP-validated
The AI

Aether is the AI doing the life sciences work.

Three things to know about the AI underneath every workload on this page. We aren't building a chat surface for your team — we are training a foundation model that plans, runs and reports.

The AI does the discipline

Not a chat interface over your engineers. A foundation model that plans the study, picks the method, runs the agents, validates against measured reality and writes the report. The same shape an experienced practitioner would follow — done by the model.

One model, your context

We don't ship a sibling model per industry. The same Aether weights serve every discipline, but the agents on top are trained against your standards, your historical data and your regulatory posture.

Reality is the regulariser

We train on simulation, instrument and design data — not scraped text. The model gets better the more reality it touches. Reality is what tells it when it's wrong.

What the AI runs here

The work, done by Aether.

These are the workloads Aether already runs in life sciences. Not a wish-list. Each ships with validated benchmarks and traces a senior engineer can read end-to-end.

  • 01

    Drug discovery

    Docking, FEP, MD, QM, ADMET, generative chemistry, biologics — every workflow from target to lead.

  • 02

    Autonomous wet-lab

    Active-learning campaigns driving real instruments with ALCOA+ chain-of-custody.

  • 03

    Clinical development

    Adaptive trial design, virtual control arms, biostatistics, submission packaging.

  • 04

    CMC and process development

    Crystallisation, formulation, scale-up modelling. The same multiphysics agents that handle aerospace also handle pharmaceutical process work.

  • 05

    Quality control

    Spec-aware QC automation with deviation tracking, batch-record assembly, and audit-trail export.

  • 06

    Regulatory submissions

    eCTD-friendly outputs, traceable provenance from raw data to summary statistics, ready for FDA/EMA review.

AI for life sciences

“We are building the AI that does life sciences — not the one that talks about it. Aether doesn't ask your engineers to drive its solvers. It runs the work, validates the artefact and writes the memo.”

What it replaces

The stack today.

The typical stack in life sciences — a half-dozen seven-figure renewals stitched together with internal glue code. We replace the spine; we don't touch the niches that work.

Vendor-locked computational-chemistry stacks
Bespoke clinical-trial platforms
Legacy CMC and stability-modelling tools
Manual quality-control documentation
The specialists at play

The agents in the mix.

Aether coordinates these specialist agents for life sciences. Each is independently deployable, but the coordination — and the foundation model underneath — is what makes them more than a folder of scripts.

dockingFEPADMETbiostatisticsCMCQCregulatory
Regulatory & boundary

How we ship into regulated life sciences.

The pieces that matter to procurement, security review and the regulator. We ship into industries where the boundary is real and the audit is unforgiving.

  • GxP-grade chain-of-custody from compound to candidate

  • 21 CFR Part 11 audit-ready electronic records

  • FDA AI/ML guidance-aligned model lifecycle management

  • Biosecurity refusals and dual-use gating at the model layer

Other industries

The AI is also running here.

A foundation model that serves twenty-two industries today. The same weights, different agents, different pilot patterns. Browse the ones nearest yours.

FAQ

Questions about life sciences.

  • What does Aether replace in life sciences?

    The incumbent stack here — Vendor-locked computational-chemistry stacks, Bespoke clinical-trial platforms, Legacy CMC and stability-modelling tools, Manual quality-control documentation — collapses into one model and one project file, with Aether for drug discovery and Aether for autonomous labs doing the work under one safety story.

  • What outcomes should we expect?

    Discovery → CMC (one substrate); ALCOA+ / 21 CFR 11 (ready); GxP-compatible (deploys) — scoped to your workload and measured against your own acceptance criteria.

  • How does a pilot work?

    Three to eight weeks against a workload and a win condition you co-author. We run alongside your incumbent stack on real cases; if we aren't better on the metric by quarter end, the rest of the quarter is on us.

  • Can it deploy inside our boundary?

    Yes — managed, in your VPC, on-prem or fully air-gapped on Aether Cloud, with the audit trail and provenance the regulated parts of this work require.

The AI is ready for life sciences.

Send us the workload that hurts. We'll come back with a scoped pilot — three to eight weeks, win condition co-authored. If we aren't better on the metric by quarter end, the rest of the quarter is on us.