Turbine

What Turbine does

Turbine is a privately held AI-driven virtual biology company founded in 2015 in Budapest, Hungary (with a parallel London headquarters) that builds the Simulated Cell™ platform — a proprietary machine learning system that learns the parameters governing cell signaling from large-scale perturbation experiments and applies them to predict cellular responses across engineered cell lines, patient-derived organoids, patient-derived xenografts, and patient samples. The platform is delivered to pharmaceutical R&D teams through a tiered Virtual Lab product: vLab Core (self-serve access to public and Turbine proprietary datasets spanning 1,400+ oncology cell lines, 1,200+ payloads/drugs, and 8,500+ gene knockouts), vLab Custom (in silico predictions run against a partner's proprietary sample library and compounds), and vLab Collaborate (joint simulation work on virtual endogenous disease models). Specialized applications include ADC Intelligence for antibody-drug conjugate discovery and Target Discovery & De-risking Intelligence for novel target identification and synthetic lethality screening, with sub-initiatives such as PerMel-AI for melanoma biomarkers and an EU-funded Turbine Digital Laboratory project.

The company operates a B2B enterprise field-sales motion targeting major biopharmaceutical companies, monetizing through subscription/collaboration agreements structured around program scope rather than publicly disclosed pricing tiers. Named customers and partners include MSD (Merck & Co.), AstraZeneca, Bayer, Ono Pharmaceutical, Debiopharm, Cancer Research Horizons, and CRO Crown Bioscience. Turbine employs 80+ people (firmographic range 101–250) across Budapest, London, and other European and US locations, and has raised approximately $60M+ across seed, Series A (€25.5M, 2022–2023), a strategic Accenture Ventures investment (2024), and a $25M Series B (February 2026) led by Interactive Venture Partners with Beiersdorf AG, MSD Global Health Innovation, Accel, and Mercia.

Name

Turbine

Legal name

Turbine Hálózatelemző Kutatási Fejlesztési Kft.

Website

https://turbine.ai

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

101–250 employees

Short description

Turbine is an AI-driven virtual biology company that builds the Simulated Cell™ platform to predict cellular drug responses and run virtual experiments for biopharmaceutical R&D, serving enterprise pharma customers through its tiered Virtual Lab and specialized ADC and target discovery applications.

Ownership category

akta.pro rank

Product category

AI-powered drug discovery simulation software

NAICS

Research and Development in Biotechnology (except Nanobiotechnology) (541714), Scientific Research and Development Services (5417), Computer Systems Design and Related Services (5415)

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

AI/ML-Enabled Biologic Discovery Platforms (computational design, in silico screening) (HLAAAIAE), In Silico / Computational Toxicology & PK/PD Modeling (HLAGAFAM)

Keywords

• AI drug discovery
• Virtual cell simulation
• Computational biology platform
• Biopharma R&D software
• Cancer target discovery

Headquarters

HQ city

Budapest

HQ country

Hungary

HQ region

Europe

Offices3 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

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

Revenue model

1. Virtual Lab Subscriptions: B2B software platform providing virtual experiments to pharmaceutical companies, delivered through three tiers (vLab Core, Custom, Collaborate) with varying levels of data access and collaboration

Go-to-market motion1 record

Distribution channels4 records

Marketing channels9 records

Core offering

Turbine builds and sells an AI-powered Simulated Cell platform that learns the parameters governing cell signaling from large-scale experiments and predicts cellular responses across engineered cell lines, PDOs, PDXs, and patient samples. The platform is commercialized through the Virtual Lab product (vLab Core self-serve, vLab Custom partner-data engagement, vLab Collaborate joint disease modeling) and specialized applications including ADC Intelligence for antibody-drug conjugate development and Target Discovery & De-risking Intelligence for novel oncology targets. Customers are biopharmaceutical R&D teams that use the platform to run millions of virtual experiments, generate mechanistic hypotheses, and prioritize wet-lab validation, reducing timelines and data-generation spend.

Product overview

Turbine operates as a virtual biology company offering an AI-powered simulation platform for virtualizing biological experiments at computational scale. The core offering is the Simulated Cell Platform, a proprietary AI technology that learns cell signaling parameters to predict cellular behavior and generate mechanistic hypotheses. This platform is delivered through the Virtual Lab product tier (vLab Core for self-serve, vLab Custom for proprietary data integration, and vLab Collaborate for joint R&D). Specialized applications include ADC Intelligence for antibody-drug conjugate development and Target Discovery & De-risking for oncology pipeline expansion. Supporting initiatives include PerMel-AI for melanoma biomarker research and the EU-funded Turbine Digital Laboratory project.

Differentiator

Problem solved

Functional benefit

Brands

• Virtual Lab: A no-code platform for virtualizing biological experiments, enabling pharma researchers to run millions of virtual experiments and prioritize wet lab work.
• ADC Intelligence
• Target Discovery & De-risking Intelligence
• Simulated Cell

Products and services

• Virtual Lab No-code virtual biology platform for biopharma R&D that runs simulations on Turbine's proprietary and public datasets (1,400+ oncology cell lines, 1,200+ payloads/drugs, KO alterations across 8,500+ genes) and integrates in silico predictions with wet-lab validation in a continuous learning loop.
• ADC Intelligence AI-driven virtual assays for antibody-drug conjugate (ADC) discovery that extend cell line space for payload and ADC positioning, select cancer sub-indications or molecular biomarkers predictive of payload sensitivity, rank drug-drug combinations for dual-payload ADC design, and reveal ADC-specific biological insights including resistance mechanisms.
• Target Discovery & De-risking Intelligence Service identifying hidden and novel targets to diversify and de-risk partner pipelines, providing simulated modulation of undrugged targets in models inaccessible for conventional screens, mechanistic explanation of target perturbation effects, and synthetic lethality screening with predictive biomarker hypotheses.

Quantifiable outcome

• Timeline halved from scientific question to starting validation
• +4 more outcomes

Named customers7 records

Segments2 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability3 records

Feature5 records

Partnerships

Seven partnerships are on record, tiered strategic and core.

• Crown BiosciencestrategicStrategic or Co-development Partner · 21 April 2026Strategic partnership integrating Turbine's AI-driven in silico Virtual Assays with Crown Bioscience's tumor organoid assays based on HUB Organoid Technology. Creates a closed-loop approach linking predictive modeling with experimental validation to improve predictive accuracy and reduce development timelines.
• Top 10 Pharmaceutical Company (Immunology)coreStrategic or Co-development Partner · 24 February 2026Turbine's first immunology-focused partnership with a top 10 pharmaceutical company, announced alongside Series B. The collaboration will use Turbine's AI-driven virtual assays to model immune cell behavior and identify novel therapeutic combinations, expanding Turbine's platform from oncology into immunology.
• AstraZenecacoreStrategic or Co-development Partner · 9 October 2025Collaboration leveraging Turbine's virtual disease modeling platform for antibody-drug conjugate (ADC) discovery. The project aims to enhance discovery efficiency, predict responses, and provide mechanistic insights to accelerate ADC development for cancer treatments.
• BayercoreStrategic or Co-development Partner · 22 November 2022Pharmaceutical partner testing Turbine's cell simulation technology to improve cancer drug success rates. Bayer has been collaborating with Turbine as part of the company's pharma partnership strategy.
• Ono PharmaceuticalstrategicStrategic or Co-development PartnerOngoing collaboration where Turbine has provided multiple targets with first-in-class potential along with biology-driven insights necessary for rapid validation. Turbine achieved key milestone in this collaboration.
• Cancer Research HorizonsstrategicStrategic or Co-development PartnerPartner organization within Turbine's ecosystem of biopharma and research collaborations.
• DebiopharmstrategicStrategic or Co-development PartnerPartner pharmaceutical company in Turbine's collaboration network for oncology research.

Scale indicators14 records

Recent moves6 records

Expansion highlights6 records

Broad incumbents

• Recursion Pharmaceuticals: Publicly listed AI-driven drug discovery company combining high-throughput wet lab experimentation with machine learning. Directly comparable as an end-to-end AI discovery platform targeting biopharma pipelines, but with a broader internal pipeline strategy and substantially larger scale than Turbine.
• Schrödinger: Physics-based computational platform combining molecular simulation, ML and live design for drug discovery and materials science. Comparable as a software-anchored computational drug discovery vendor selling into the same enterprise pharma customer base, though more focused on molecular design than cell-level simulation.

Direct peers

• Exscientia: AI-driven precision medicine company using patient-derived data and automated drug design to accelerate small-molecule discovery. Highly comparable in offering AI-native discovery services to pharma, with overlapping target identification, combination design and translational use cases that map closely to Turbine's ADC Intelligence and Target Discovery offerings.
• Insitro: Machine learning-driven drug discovery company combining high-throughput biology with predictive models. Directly comparable as an AI-first discovery platform with proprietary wet lab data generation feeding ML models — a similar architectural approach to Turbine's wet lab-in-the-loop Simulated Cell.
• BenevolentAI: AI-driven drug discovery company using knowledge graphs and ML to identify novel targets and develop treatments. Comparable as an AI target-identification and drug-discovery platform serving biopharma with overlapping value propositions in target discovery and indication expansion.
• Atomwise: AI-driven small molecule drug discovery company using structure-based deep learning to predict binding and design compounds. Comparable as a machine learning drug discovery vendor selling to pharma, with adjacent (rather than identical) focus on molecular-level rather than cell-system-level predictions.
• Valo Health: AI-enabled drug discovery platform combining patient data, molecular simulation and lab automation to accelerate development. Comparable as a vertically integrated, AI-anchored discovery company targeting pharma with overlapping oncology and cardiovascular pipeline ambitions.

Emerging players

• Absci: AI generative biology company combining wet lab high-throughput screening with ML models for antibody and protein therapeutic design. Comparable as an AI-first biologic discovery platform; partial overlap given Turbine's ADC Intelligence work but a different core modality focus (de novo protein design).
• Owkin: AI biotech combining multimodal patient data with ML models to discover and develop therapeutics, with emphasis on federated learning across hospitals. Comparable as an AI-biopharma platform selling predictive analytics to pharma, though more focused on clinical/translational data than preclinical cell simulation.

Others

• Crown Bioscience: Global CRO specializing in preclinical oncology services including tumor organoid and patient-derived xenograft models. Already a Turbine strategic partner integrating Virtual Assays with organoid workflows; comparable as an adjacent translational oncology services provider rather than a direct AI-discovery competitor.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/Turbine_AI
• YouTubeyoutube.com/@turbine-simcell/videos
• Facebookfacebook.com/TurbineAI
• LinkedInlinkedin.com/company/turbine-inc
• Instagraminstagram.com/turbine.ai

Revenue estimate

Valuation estimate

Number of profiles

Profiles19 records

Funding overview

Funding rounds7 records

Investors14 records

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 Turbine