Accelerate every stage of discovery, built for Biopharma

One platform for every research workflow. Your team focuses on decisions, Vecura runs the computation.

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Target & Translational Biology

Target Identification

High-confidence targets with full literature and omics evidence.

Challenge

Relevant evidence is scattered across hundreds of publications and omics datasets.

Vecura

Vecura mines literature and multi-omic data to build structured evidence maps, surfacing high-confidence targets with full citation trails.

Associated Diseases — GSK-3β · 908 associations

Associated Diseases · GSK-3β

● mining
Lit.
GWAS
Omics
Clinical
Safety
Alzheimer's disease
Bipolar disorder
Type 2 diabetes
Colorectal cancer
Parkinson's disease
Schizophrenia
Low
High908 associations

Pathway & Biomarker Analysis

Full omics and pathway analysis in one command.

Challenge

Bioinformatics pipelines require specialist time and extended timelines.

Vecura

Full omics and pathway analysis in one command. Identify patient stratification biomarkers without waiting on a dedicated bioinformatician.

Pathway & Biomarker Analysis
PI3K-Akt signaling
3.1e-887g
2.41
Tau protein binding
1.2e-734g
2.18
Neurotrophin signaling
4.8e-662g
1.95
MAPK signaling pathway
9.2e-5108g
1.73
Wnt/β-catenin signaling
2.1e-445g
1.52

NES = normalized enrichment score

Hit Discovery

Virtual Screening

Dock millions of compounds against any target in hours.

Challenge

Screening large libraries manually takes weeks and significant compute setup.

Vecura

Dock millions of compounds against any target in hours. Vecura orchestrates GPU-accelerated docking automatically — no infrastructure work required.

Virtual Screening — GSK-3β · 500 compounds

Chemical Space · GSK-3β · 500 compounds

CNS+CNS−
-5-7-9270320370420MW (Da)ΔGHit zone
500 screened · 31 hits · Best ΔG: −9.4 kcal/mol · 4 CNS-penetrant

Binder Design

Generate high-affinity binders across small molecules, peptides, proteins, and biologics using generative AI.

Challenge

Generative binder design tools — RFdiffusion, BoltzGen, ProteinMPNN — each require separate compute pipelines and specialist expertise. Running multi-modality campaigns means stitching together incompatible toolchains, delaying the first ranked candidate by weeks.

Vecura

Vecura orchestrates generative design across all modalities from a single interface. Specify your target pocket and binding constraints, and Vecura generates, scores, and ranks candidates — from macrocycles to nanobodies — with no infrastructure overhead.

Binder Design — GSK-3β · Multi-modality

Generative Binder Design — GSK-3β

● generating

Small molecule

BoltzGen

128 candidates · best ΔG −9.8 kcal/mol

Linear peptide

RFdiffusion

64 candidates · best Kd 85 nM

Macrocycle

BoltzGen

32 generated · ranking…

Nanobody

ProteinMPNN

Top ranked

MC-0007Macrocycle12 nM91% novel
SM-0041Small molecule−9.8 kcal94% novel
PEP-012Linear peptide85 nM87% novel

ADMET Profiling

Safety liabilities attached to every hit at screening time.

Challenge

Safety liabilities found after synthesis waste months of lab time.

Vecura

Vecura auto-attaches key safety and ADMET profiles to every hit at screening time, so your team only advances compounds worth synthesizing.

ADMET Profiling — NYB-0041823

ADMET Profile — NYB-0041823

6 / 8 Pass
hERG inhibition
IC₅₀ > 30 µMPass
Ames mutagenicity
NegativePass
Aqueous solubility
87 µg/mLPass
BBB penetration
LogBB 0.31High
LogP (lipophilicity)
2.1Pass
Plasma protein binding
94%Pass
CYP3A4 inhibition
IC₅₀ 4.2 µMCaution
Caco-2 permeability
18 nm/sCaution

Lead Optimization

Enumerate analogs and predict SAR across your chemical space.

Challenge

Analog iteration cycles bottleneck the path from hit to candidate.

Vecura

Enumerate analogs and predict SAR across your chemical space in one run, with selectivity constraints and IP exclusions baked in.

Lead Optimization — GSK-3β Series

Analog Series · GSK-3β · 5 of 128

Best: −10.1
1823Parent hit
-9.412.1×Parent
18314-F substitution
-9.818.4×↑ Better
1847N-methyl
-9.114.2×≈ Similar
18523-Cl, 4-F
-10.122.7×↑ Better
1869Morpholine
-8.79.8×↓ Worse
128 analogs enumerated · selectivity + IP constraints applied
Regulatory & Safety

Safety Assessment

Tissue liability, essentiality scoring, and adverse signal extraction — automated.

Challenge

Toxicology synthesis across published data takes months of manual review.

Vecura

Vecura covers tissue liability, target essentiality, and adverse event signal extraction in a single automated run — well ahead of your submission deadline.

Safety Assessment — NYB-0041823

Risk Matrix — NYB-0041823

4 / 5 assessed
Likelihood →Severity →High riskAcceptable
Mining 847 FAERS reports · hover findings for detail

Regulatory Reporting

Structured data packages and slide decks generated automatically.

Challenge

Formatting results for partners, investors, or regulators is slow and error-prone.

Vecura

Generate structured data packages, dashboards, and presentation-ready slide decks in the format your audience needs.

Regulatory Reporting — Package Builder

NYB-0041823 · Pre-IND Package

3 / 6 generated

Overall Risk

Low–Mod

Mutagenicity

Negative

Cardiac safety

Pass

Executive Summary

PDF

Tissue Liability Report

PDF

ADMET Data Appendix

CSV

Regulatory Slide Deck

PPTX

FDA Cover Sheet

DOCX

Partner Data Package

ZIP
Rendering slide deck — export-ready in ~40 s

From the people running the experiments

Our team spans medicinal chemistry, biology, and comp chem. Vecura is the first tool that actually works for all three without specialised setup. We've gone from hand-rolling pipelines to running entire campaigns through one workspace.

Head of Discovery

Series A biotech

I used to spend half my day formatting outputs between tools. Vecura just handles it — I describe the experiment and get back ranked hits with safety flags already attached.

Computational Chemist

Oncology biotech

The ADMET integration alone saves us from wasted screening cycles. We know which leads are viable before we ever touch the bench.

Drug Discovery Scientist

Mid-size pharma

What used to take a week of script-wrangling — fetching structures, running docking, filtering, summarizing — Vecura does in an afternoon.

Structural Biologist

Academic lab

The agent doesn't just run models — it reasons about which model to use and why. That's the part that surprised me most.

Bioinformatics Lead

Research institute

I can ask it to screen a target, generate a brief, and flag literature conflicts — all in one conversation. It's like having a computational collaborator available at 2am.

Principal Scientist

Drug repurposing startup

Supercharge your scientific productivity.
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