What Meta-Flux does

Meta-Flux is a Dublin-based biotech AI company, founded in 2020-2021 by Lee Sherlock (CEO, immunologist) and Brendan Martin (CTO, AI/bioinformatician), that sells an enterprise software platform called the "AI Biologist" to pharmaceutical and biotechnology R&D teams. The platform simulates disease biology by integrating multi-omic datasets (genomics, proteomics, metabolomics, transcriptomics, single-cell), scientific literature, and clinical data through proprietary Structured Neural Networks (SNNs) and feedback-loop knowledge graphs, then runs billions of multi-scale simulations to generate ranked, interpretable hypotheses for target discovery, biomarker identification, drug repurposing, and preclinical go/no-go decisions.

The product is organized into five integrated modules — Database (structured biological/chemical datasets), Networks (multi-omic cross-therapeutic graphs), Reporting Engine (ranked hypotheses with toxicity flags), Simulation Technology (billions of SNN simulations), and Knowledge Graph (encoded biological relationships) — and the company claims 20T+ data points processed, 10x improved multi-modal throughput, 5x faster hypothesis-to-insight turnaround, and 20-30% timeline reduction in discovery, with benchmarked results including 97% sepsis diagnostic accuracy and ROC AUC 0.994 in lung cancer biomarkers.

The business model is a subscription/recurring enterprise SaaS motion targeting large pharma R&D, biotechs, CROs, and academic researchers through demo-driven, quote-based sales, with global distribution from Dublin and a US office in Cambridge, MA. The company raised €1.8M (~$2M) in seed funding in October 2025 from executives at Pfizer, Merck, Gilead, Google, Amazon, and Indeed, participated in the MassBio Drive Accelerator, and announced a strategic co-development partnership with Mercury Bio in December 2025 to apply the platform to Parkinson's and Alzheimer's therapeutics.

Name

Meta-Flux

Legal name

Meta-Flux

Website

https://meta-flux.com

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

1–10 employees

Short description

Meta-Flux is an Ireland-based AI biotech company whose AI Biologist platform simulates disease biology from multi-omic and literature data to help pharmaceutical and biotech R&D teams accelerate target discovery, biomarker identification, and preclinical go/no-go decisions.

Ownership category

akta.pro rank

Product category

AI Drug Discovery Software

NAICS

Research and Development in Biotechnology (except Nanobiotechnology) (541714), Research and Development in the Physical, Engineering, and Life Sciences (54171), Scientific Research and Development Services (5417)

SIC

Services-Prepackaged Software (7372), Services-Commercial Physical & Biological Research (8731)

akta.pro primary industry

AI/ML Platforms for Drug Discovery & Experiment Optimization (HLAGAJAO)

akta.pro secondary industries

Bioinformatics & Multi-omics Analysis Software (HLAGAJAD), AI/ML-Enabled Biologic Discovery Platforms (computational design, in silico screening) (HLAAAIAE), Target Identification & Validation Platforms (omics-driven, chemoproteomics, genetic validation) (HLAAAIAI), Multi-Omics Precision Medicine Platforms (genomics/proteomics/metabolomics) (HLAAANAF), In Silico / Computational Toxicology & PK/PD Modeling (HLAGAFAM)

Keywords

• Drug discovery platform
• AI drug development
• Preclinical research tools
• Disease biology simulation
• Multi-omics analytics

Headquarters

HQ city

Dublin

HQ country

Ireland

HQ region

Europe

Offices2 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales, Infrastructure

Revenue model

1. AI Platform Services for Pharma: Providing AI-driven decision-support platform for preclinical drug development to pharmaceutical and biotech companies, enabling faster go/no-go decisions and reducing development costs.

Go-to-market motion1 record

Distribution channels1 record

Marketing channels4 records

Core offering

Meta-Flux builds and sells the AI Biologist Platform, an AI-driven preclinical drug development platform that uses Structured Neural Networks to integrate multi-omic (genomic, proteomic, metabolomic, transcriptomic) and clinical data into dynamic knowledge graphs and run billions of simulations. The platform produces ranked, interpretable hypotheses to help pharmaceutical and biotech teams accelerate target discovery, identify drug repurposing opportunities, and make faster go/no-go decisions in early-stage R&D.

Product overview

Meta-Flux offers the AI Biologist Platform as its core product — a structured neural network platform that integrates multi-omic data (genomics, proteomics, metabolomics, transcriptomics) with biological knowledge graphs and simulation engines to model disease biology and predict drug behavior. The platform comprises five integrated modules: the Database Module (structured biological and chemical datasets), Networks Module (dynamic disease-level graphs), Reporting Engine (ranked hypotheses and toxicity flags), Simulation Technology (multi-scale models running billions of simulations), and Knowledge Graph (encoded biological relationships). Together, these enable pharma teams to accelerate target discovery, identify drug repurposing opportunities, and make faster go/no-go decisions from idea to clinical success.

Differentiator

Problem solved

Functional benefit

Brands

• AI Biologist: Meta-Flux's structured neural network platform that simulates disease biology by integrating genetic, protein, and metabolic data for drug development decision support

Products and services

• AI Biologist Platform A structured neural network platform that simulates disease biology by integrating genetic, protein, metabolic, and multi-omic data to help pharmaceutical teams accelerate target discovery, predict drug behavior, and make faster go/no-go decisions in preclinical drug development. It is sold to large pharma R&D departments and biotech firms under a subscription-based enterprise model.

Quantifiable outcome

• 97% diagnostic accuracy across all sepsis clusters using deep graph neural networks, identifying 2/2 key markers vs 0/2 with traditional methods
• +5 more outcomes

Named customers2 records

Segments4 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability7 records

Feature5 records

Partnerships

Three partnerships are on record, tiered core.

• Mercury BiocoreStrategic or Co-development Partner · 19 December 2025Strategic collaboration to develop therapeutics for Parkinson's and Alzheimer's diseases. Partnership combines Mercury Bio's yEV technology with Meta-Flux's computational modeling platform to address challenges including blood-brain barrier crossing and intracellular drug delivery. Focus on improving target selection, pathway prioritization, and early development decision-making.
• Dogpatch LabscoreOthersLeading European startup accelerator providing workspace at The CHQ Building in Dublin and entrepreneurship support.
• MassBiocoreGTM or Marketing PartnerMassachusetts Biotechnology Council partnership through Drive Accelerator program, providing mentorship, curriculum, and industry connections across the life sciences ecosystem. Meta-Flux presenting at MassBio Align Summit.

Scale indicators8 records

Recent moves6 records

Expansion highlights6 records

Emerging players

• Owkin: AI biotech combining multimodal patient data, multi-omics, and federated learning to advance drug development and precision medicine. Comparable on multi-omics AI and pharma collaboration model, though with stronger orientation toward clinical/oncology data.
• Lantern Pharma: AI-driven oncology drug developer using machine learning on multi-omic data to identify responders and accelerate clinical development. Comparable on AI + multi-omics + oncology, though Lantern Pharma is asset-owning rather than software-only.
• Standigm: AI-driven drug discovery company applying workflow AI to target identification, lead generation, and repurposing across multiple disease areas. Comparable as a pharma-facing AI biology platform with a similar partnership/enterprise business model.
• Xaira Therapeutics: Well-funded AI drug discovery startup applying generative AI and biological foundation models to pharmaceutical R&D. Comparable as a venture-backed AI biology platform, though more recently launched and focused on generative model methods.

Broad incumbents

• Schrödinger: Publicly listed computational chemistry and predictive software company serving pharma with molecular simulation and predictive analytics for drug discovery. Comparable as a software/SaaS provider to pharma R&D, but with broader focus on computational chemistry rather than disease-biology simulation.
• Isomorphic Labs: Alphabet-backed AI drug discovery company leveraging DeepMind's protein structure prediction and biological modeling to partner with pharma on novel therapeutics. Comparable as a deep-tech AI biology platform targeting pharma R&D, with substantially more capital and compute.
• Recursion Pharmaceuticals: Publicly traded AI-driven drug discovery company combining high-throughput biology, phenomics, and machine learning to identify novel therapeutics. Directly comparable as an end-to-end AI biology platform serving pharma R&D, though larger and more capital-intensive than Meta-Flux.

Direct peers

• Exscientia: AI-driven drug design company using machine learning to accelerate small-molecule discovery from target identification through preclinical. Comparable as a pharma-facing AI drug discovery platform, though with a chemistry-first rather than multi-omics-first orientation.
• Insitro: Machine learning-driven drug discovery platform combining high-throughput biology data with AI models to predict therapeutic outcomes. Closest functional analog to Meta-Flux: a venture-backed AI biology company selling computational decision support to pharma R&D.
• BenevolentAI: AI-driven drug discovery company that uses knowledge graphs and machine learning to identify new drug targets and indications. Closely comparable to Meta-Flux's knowledge-graph + multi-omic approach and its pharma partnership model.

Market position

Strengths5 records

Weaknesses1 record

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• LinkedInlinkedin.com/company/meta-flux

Revenue estimate

Valuation estimate

Number of profiles

Profiles5 records

Funding overview

Funding rounds3 records

Investors1 record

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Meta-Flux