QAI Labs · NOVA-3 platform

Designed,
not screened.

Two programs. One quantum-enhanced design platform. Eight to sixteen weeks from sequence to in-vitro PoC; in-vivo timeline partner-lab dependent.

Live in your browser — real ESMFold + Mol*, no account or login required.

8–16 wk
Target · seq → in-vitro PoC
>60%
Target PoC success rate
40+
Validated VH/VL sequences · 3 targets
0.861
ipTM · validated multimer fold

Design targets and in-silico / modeled figures — not yet demonstrated in vivo. Library size is current. Measured results publish on Benchmarks as programs mature.

A five-layer stack for multi-specific antibody design.

Quantum-enhanced AI fused with a wet-lab data flywheel. Each layer feeds the next; each candidate carries a cryptographically anchored evidence trail.

01
Layer · Data

Module Library

40+ validated VH/VL sequences across 3 active-program targets in oncology. Plus a curated library of linkers, hinges, and effectors. Each module is provenance-stamped, partner-IP-segregated, and schema-typed.
40+ VH/VL sequences 3 targets Partner-IP carveouts
02
Layer · Compute

NOVA-Compute

AWS GPU for classical inference; VQE / CVaR-QAOA validated on simulators today, with targeted IBM Quantum (Heron r3) and Quantinuum (Helios) hardware access in progress. Modal & Runpod for burst. Every job logs backend, shots, and cost.
Quantum-hardware-explicit Simulator fallback Cost ledger
03
Layer · Model

Generators & Heads

Best-of-breed open foundations wrapped for multi-specific design: Boltz-2 (MIT license; commercial use permitted) and ESM-3 / ESMC (EvolutionaryScale / CZ Biohub) under evaluation for future integration — not used in the current product, RFdiffusion (de-novo protein binders; Watson et al., Science 2023). AlphaFold 3 used for internal research benchmarking only under non-commercial research-use terms; production design runs use Boltz-2 / Chai-1. Program-specific heads on top: ranking, structural confidence, in-silico Kd.
Three heads Mol* viewer Top-24 ranked
04
Layer · DBTL

Wet-lab Loop

Partner-lab adapters with IP-carveout enforcement. SPR/BLI, ADCC dose-response, in vivo efficacy. Every assay result flows back into the Module Library; wet-lab results re-enter the corpus with each cycle — the corpus improves with each completed DBTL round.
compounding performance SPR · BLI · ADCC In-vivo PoC
05
Layer · Evidence

NOVA-Evidence

Cryptographic provenance on every result. SHA-256 root committed to Bitcoin via OpenTimestamps. Provenance and IP references recorded in the bundle at design time. Every claim — Kd, EC50, pTM, ADCC — reproducible from the bundle.
OpenTimestamps SHA-256 root Notary-grade

Two in-licensed programs.

Multi-specific antibody programs in oncology — each on the same eight-to-sixteen-week path from sequence to in-vitro PoC; in-vivo schedule partner-lab dependent.

NOVA-3 · P1 — IMT030122

EpCAM × CD3 × 4-1BB
trispecific TCE

EpCAM-positive epithelial tumors. Tumor-targeted T-cell engagement with 4-1BB costimulation designed to mitigate T-cell exhaustion from sustained CD3 engagement; conditional costimulation mechanism requires functional validation. In-licensed program.

EpCAM — tumor targeting
CD3ε — TCR engagement
4-1BB — costimulation gate
In silico PoC In-licensed · Sch. B
NOVA-3 · P2 — IMB030202

EpCAM × 4-1BB × HSA

EpCAM-positive epithelial tumors. Tumor-localized 4-1BB costimulation (no CD3) designed to concentrate agonism in EpCAM-positive tissue while limiting systemic exposure; a human serum albumin (HSA) module extends half-life. Mechanism requires functional validation. In-licensed program.

EpCAM — tumor targeting
4-1BB — conditional costimulation
HSA — half-life extension
In vitro PoC In-licensed · Sch. B

Evidence, not assertions.

On raw folding accuracy, AlphaFold 3 and Chai-1 set the bar; NOVA-3 wraps them. Our differentiation is upstream — multi-specific composability via the Module Library — and downstream — quantum-corrected refinement, cryptographic provenance, and a wet-lab flywheel. Every result is reproducible from an Evidence Bundle.

Positioning map — predict vs. compose, with provenance as the second axis QUALITATIVE PLACEMENT · NO METRICS · STRATEGIC VIEW WHERE WE PLAY PREDICT one structure COMPOSE multi-specifics from parts CRYPTOGRAPHIC PROVENANCE NO PROVENANCE General folding models AF3 · Chai · ESMFold Classical screening / CRO workflow NOVA-3 compose + signed provenance LEGEND Folding models Classical screening NOVA-3 our position Target space Position is qualitative — no axis is numeric.
Figure — Where we play. Two axes that matter: do you predict a single structure or compose a multi-specific from validated parts, and can you prove how the design was made. General folding tools and classical CRO screening cluster in the lower band — useful, but unsigned and structure-first. NOVA-3 sits alone in the upper-right: compositional design with cryptographic provenance. Placement is strategic and qualitative; the axes carry no numbers.
Sample bundleillustrative · verify a real bundle at /predict
Bundle IDEVB-P1-2026-0517-3A21
ProgramNOVA-3 · P1 (EpCAM × CD3 × 4-1BB)
CandidateCAND-P1-LEAD-04
SHA-256 root0x9c4b8e21a3f7d24c81b6e5f9a2e4c7d5...
OTS anchorConfirmed · block 944,517
Anchored at2026-05-17 14:22:08 UTC
IP referencein-licensed (Schedule B)
ReproducibleYes · cmd attached

Multi-specific composability.

Curated, schema-typed Module Library across binders / linkers / hinges / effectors. Folding models (Chai-1, Boltz-2) predict a structure from a sequence; NOVA-3 composes a multi-arm molecule from validated parts, then wraps those folders to evaluate it. Different layer of the stack — we compose, they predict.

Quantum active-space corrections.

VQE active-space corrections for the hardest, strongly-correlated chemistry — validated on simulators today, with hardware access in progress; the hardware fraction of every job is reported. No claim of demonstrated quantum advantage in ground-state chemistry — we engage with the open question rather than assert it.

Cryptographic provenance — verify it yourself.

Every candidate ships an OpenTimestamps-anchored Evidence Bundle. You don't have to take our word: paste any bundle's SHA-256 root into the verifier and confirm the Bitcoin anchor and invention date independently. Verify a bundle →

Built in Texas. Global by design.

QAI Labs Ltd. is a Delaware corporation headquartered in Sugar Land, Texas, building at the intersection of pharma business development, quantum hardware partnerships, and multi-specific antibody engineering — with collaborators across North America, Europe, and Asia-Pacific.

F
Dr. Daniel Feng
Co-founder · Strategy & Partnerships

Drug developer and entrepreneur with a background in therapeutic antibody engineering at Medarex and Bristol-Myers Squibb, where he contributed to programs advancing through Phase I/II. At QAI Labs he leads company strategy, platform commercialization, and partnerships — including the IBM Quantum and Quantinuum integrations. Brings pharma-grade evidentiary discipline to every platform claim.

G
Dr. Xin Gao
Co-founder · Platform & Programs

Physician-scientist and co-inventor of the XFab multi-specific antibody platform, whose IP is owned by a third-party licensor and licensed to QAI Labs (patent assignments in progress; structure available under NDA). Brings direct experience advancing multi-specific antibody candidates through preclinical and early clinical development. Leads program strategy and platform architecture — each program is evaluated from inception against what a clinical development team would require.

W
Dr. Min Wang
Chief Scientific Officer · Quantum AI Lead

Computational scientist and co-inventor of the XFab quantum-augmented molecular simulation platform, owned by a third-party licensor and licensed to QAI Labs (patent assignments in progress). Architects and operates the NOVA-3 quantum compute layer — VQE active-space corrections, QAOA assignment optimization, and the hardware interface to IBM Quantum and Quantinuum. Reports hardware fraction on every job; makes no claim of demonstrated quantum advantage.

Eight to sixteen weeks. Two programs. One platform.

Pharma BD, partner labs, and quantum hardware collaborations. The first conversation usually starts with a program walkthrough and an Evidence Bundle review. Or submit a target antigen below and we'll scope a design in 48 hours.

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