The Drug Discovery Funnel
Drug discovery and development is a long, costly, and high-risk process:
It takes 10–15 years and costs $1–2 billion for each new drug approval.
Over 90% of drug candidates fail during clinical trials, primarily due to lack of efficacy.
These failures are directly linked to the lack of predictive validity in preclinical models.
Can AI solve this problem alone?
We don’t think so.
Bad experimental models → Bad Data → Bad Targets → Bad Therapeutics → Failures in Drug Discovery
Key Opportunity:
Improving the predictive validity of preclinical and experimental models is the most powerful way to increase drug discovery success.
AI unlocks a new frontier in drug discovery, but its potential is only realized when paired with human-centric, translational in-vitro models.
Reshaping The Drug Discovery Funnel
At VALID, we create complex, disease-relevant hiPSC-based in-vitro models with increased predictive validity at scale.
By connecting human genetics with VALID's physiologically relevant experimental models, we generate meaningful "OMICs-AI data." This powerful combination enables novel insights into human disease, therapeutic targets, and drug discovery.
We are moving advanced efficacy models with improved predictive validity into the earliest stages of drug discovery.
This is VALIDity at Scale.
Our automated experimental platform reshapes the drug discovery funnel, improving success rates, enabling faster, more reliable, and cost-effective therapeutic development.
Our Mission: To dramatically increase the success of drug discovery by combining the predictive validity of industrial-scale advanced human pluripotent stem cell disease models with AI-enabled experimental data generation.