ADC discovery & positioning
In which indications is my payload / ADC most effective?
How selective is my ADC?
What are the predictive biomarkers of sensitivity / resistance?
THE VIRTUAL LAB
Simulate experiments at computational scale, and generate decision-ready data packages to improve drug discovery.
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vLAB®
Turbine's virtual lab enables scientists to run and interpret virtual experiments and generate structured, decision-ready data, allowing teams to explore hypotheses and move seamlessly from question to answer, in silico to wet lab.
50M+
Virtual experiments simulated per day
80%
FASTER TO DECISION
(2 vs. 12 months)
(2 vs. 12 months)
100+
Validated hypotheses across 30+ CUSTOMERS
50%
fewer wet lab experiments needed for a validated hypothesis
Answer Every Question
at Every Stage of Drug Discovery
Virtual Assays digitize experiments across millions of conditions in parallel,
predicting detailed, in silico outputs, from cellular phenotypes
to molecular states, before any physical experiment is run.
predicting detailed, in silico outputs, from cellular phenotypes
to molecular states, before any physical experiment is run.
Payload synergy & combinations
Which payload pairs are the most synergistic?
Which ADC – small molecule pairs are the most synergistic?
Which genes should I target alongside my drug to improve efficacy?
ADC clinical translation
How translatable are my in vitro ADC efficacy results into PDX models?
What clinically-relevant biomarkers can I identify early to inform patient inclusion/exclusion criteria?
Target ID & positioning
Which genes when inhibited cause disease cell death?
What are the predictive biomarkers of sensitivity / resistance?
In which indications is my target the most effective?
Mechanistic
insight
What is the functional impact of inhibiting my gene of interest?
Combinations
Which new or known drug targets can my target be combined with?
Is this a good target in the background of a treatment e.g, standard-of-care?
Oncology
Immunology
Neurology
Dermatology
How it works
Virtual Cell
System-level model of how disease biology behaves under drug stimulus.
Turbine’s proprietary, licensed & public data
- 1400 cell lines
- 50+ immune cell types
- 1000+ PDX models & perturbations
- 200+ drugs and & combinations, incl. SoC, payloads, PROTACs & full ADCs
- 100,000 patient profiles & clinical response data
Virtual Assays
In silico experiments that simulate cellular response to drug and genetic perturbations at computational scale.
Virtual Lab
Where teams design, run, and interpret virtual experiments that generate decision-ready outputs, making simulation part of the discovery workflow.
Lab-in-the-Loop
Virtual experiments guide what goes to the wet lab and their results identify data needs and are used to refine future assays so that every experiment that reaches the bench is more likely to succeed. Predictions can be validated in your own laboratory, a CRO partner or Turbine’s own facility.
Simulation-guided data generation
- 50,000 data points / month for mono & drug combinations
- 10,000 data points / month for drug + siRNA combinations
- Viability, growth inhibition, brightfield microscopy images
- Transcriptomics & proteomics assay readout
- Biobank of cancer cell lines & immortalized healthy cell lines
