The economics of screening first.
When computational screening costs near zero, every dollar of experimental budget goes further. Here is the business case.
When computational screening costs near zero, every dollar of experimental budget goes further. Here is the business case.
Most R&D teams screen late. Candidates are designed, synthesized, and tested before safety or property viability is checked computationally. The result is predictable: a significant fraction of experimental investment goes toward candidates that could have been flagged computationally months earlier.
Typical cost to advance one compound through preclinical
of clinical failures are ADMET-related (pharmacokinetics, toxicity)
Typical DFT campaign for 200–500 candidate compositions
HPC cluster costs for a mid-size computational materials group
Every late-stage failure represents not just the cost of the failed experiment, but the opportunity cost of all the work that led to it. Computational pre-screening eliminates the most obvious failures before any bench time is spent.
Full ADMET panel: solubility, permeability, CYP inhibition, hERG, hepatotoxicity.
DFT estimate assumes a 64-core HPC cluster running continuously. Experimental estimate assumes synthesis + assay for each compound.
Annual cost for a team of 10 scientists running routine screening campaigns.
| Cost element | DFT suite | ML platform | FluxMateria |
|---|---|---|---|
| Software license | $150K–300K (per-seat pricing, 10 users) |
$50K–150K (platform + API access) |
€30K (team-wide, unlimited users) |
| Compute infrastructure | $50K–200K (HPC cluster or cloud GPU) |
$10K–30K (inference compute) |
Included (2,000 GPU-hours in Business plan) |
| Specialist FTEs | 1–3 dedicated (comp chem PhDs to run DFT) |
0.5–1 dedicated (ML engineer for retraining) |
0 (no specialist needed) |
| Model retraining / maintenance | N/A | $20K–50K/yr (data curation + retraining) |
N/A (no training data, no retraining) |
| Estimated annual total | $200K–500K+ | $80K–230K | ~€30K |
DFT suite costs based on published pricing for Schrödinger, BIOVIA, and VASP commercial licenses. ML platform costs based on typical SaaS pricing for cheminformatics platforms. All estimates are illustrative; actual costs vary by organization and usage.
One scientist with FluxMateria can do the screening work that previously required a computational chemistry team.
Any medicinal chemist, materials scientist, or bench researcher can run screenings directly. No computational chemistry expertise required.
Moving screening from the end of the pipeline to the beginning changes the economics of every downstream step.
Pre-screen eliminates candidates with ADMET liabilities before any bench work starts.
Screen the entire candidate space, not a curated subset. No promising candidates missed.
No retraining needed. New scaffolds, new compositions, new chemical spaces — all from day one.
The math
If synthesis + assay costs $5,000–$50,000 per compound, and a computational pre-screen eliminates even 10% of late-stage failures, the annual savings for a mid-size discovery program exceed the entire cost of FluxMateria by an order of magnitude. The platform pays for itself with a single avoided dead-end compound.
Traditional toolchains require separate licenses, separate infrastructure, and separate expertise for each domain.
| Capability | Traditional stack | FluxMateria |
|---|---|---|
| ADMET screening | Separate ML platform or vendor assays | Built-in (350 mol/sec) |
| Materials properties | VASP / Quantum ESPRESSO + HPC | Built-in (1,000+ materials) |
| Reaction mechanisms | Gaussian + specialist interpretation | Built-in (100% classification accuracy) |
| Spectroscopy | Separate spectroscopy suite | Built-in (IR, NMR, UV-Vis) |
| Synthesis planning | Separate retrosynthesis tool | Built-in (29 reaction types) |
| Target engagement | Separate docking / scoring platform | Built-in (91% MoA accuracy) |
Consolidating from 4–6 separate tools to one platform reduces license costs, integration effort, vendor management overhead, and the number of specialized FTEs required to operate the toolchain.
If you are building a business case for your procurement or budget committee, here are the points that matter:
The Pilot is a one-time €10K investment with defined success criteria and a validation report. Risk is bounded. If the pilot fails the decision gate, you stop.
No HPC cluster, no GPU procurement, no IT setup. SaaS delivery with API access. Time to first result: same day.
The Business plan covers your entire team for €30K/year. Traditional suites charge $15K–$30K per seat. For a team of 10, that is 5–10× the cost.
The 8-week pilot produces a validation report benchmarking FluxMateria against your own data. You know whether it works before committing to an annual plan.
Deterministic outputs, append-only audit logs, full provenance tracking. Every result is traceable and reproducible for regulatory and compliance review.
€10K, 8 weeks, defined success criteria. Validate on your data before committing.