AI Autopilot for Computational Chemistry

AI Autopilot for Computational Chemistry on AWS

Fovus benchmarks every docking run and screening job, then auto-assigns the GPU fleet, Spot strategy, and scale to move through DMTA cycles in hours instead of weeks.

The challenges

Computational chemists spend as much time managing cloud logistics as they do on science. GPUs needed for docking and molecular dynamics are scarce and expensive, and a strategy tuned for one workload — a single ligand-receptor docking run — can be badly wrong for another, like a 500-million-compound virtual screen. Without the right HPC strategy, teams either pay for oversized GPU clusters sitting partially idle, or watch large-scale screening jobs take days when they should take hours. Scaling cluster size for GPU-heavy campaigns is especially hard without deep cloud expertise, capping the scale of screening a team can realistically attempt and stretching DMTA cycles that should be accelerating discovery, not slowing it down.

How we help

Fovus benchmarks every computational chemistry workload — docking with Vina GPU or MegaDock, molecular dynamics with GROMACS or OpenMM — against representative inputs, revealing exactly how GPU/CPU choice, memory, and storage affect runtime and cost, free of charge.

A strategy tuned for a single docking run and one tuned for a 500-million-compound screen look nothing alike — Fovus auto-determines the right one for each job, minimizing runtime and cost with zero manual tuning.

Fovus auto-scales cluster size and parallel tasks across multiple cloud regions and availability zones, launching clusters of thousands of nodes in minutes to massively parallelize large-scale virtual screening.

Fovus analyzes Spot pricing, availability, and interruption dynamics to automatically apply the best Spot strategy, cutting cost further while auto-requeuing any disrupted task to protect result integrity.

Fovus auto-updates benchmarking data and refines HPC strategy as new GPU generations and cloud infrastructure roll out, sustaining cost and performance gains as hardware evolves.

Deploy with a single command, a few clicks in the web UI, or integrate serverless HPC directly into in-house software with the Fovus Python API. No cloud management — pay only for runtime.

The numbers behind the Autopilot

What computational chemistry teams see running docking and screening on Fovus and AWS

112x


Faster time-to-insight for large-scale compound screening, benchmarked with Chemspace.

96x


Faster AI-augmented virtual screening predictions for Beren Therapeutics.

$0.95


Cost to screen 10,000 ligands with GPU-accelerated docking, benchmarked with Vina GPU.

$3.09


Cost per 1,000 antibody-antigen docking runs, benchmarked with MegaDock.

Business Impact

Computational chemistry teams running docking and screening on Fovus are seeing dramatic results: Chemspace cut time-to-insight for large-scale compound screening by 112x at 85% lower cost, while Beren Therapeutics accelerated DMTA cycles 4x at 5.5x lower cloud spend. Benchmarked separately, Fovus delivers GPU-accelerated docking for as little as $0.95 per 10,000 ligands screened, and molecular dynamics with GROMACS or OpenMM for as little as $6.59/µs.

Your next screen could be next.

Leading discovery service provider accelerated DMTA cycles and project delivery at reduced costs