De-Risk Discovery
One solution for all early-stage rare disease decisions
The first AI that solved pharma's low success rate
Explority — an LLM-based AI system trained on 1M+ outcome-linked papers that forecasts the likelihood of approval for early-stage drug candidates, outperforming traditional preclinical success rates and identifying the highest-potential orphan therapies for drug development, investment, and partnering.
our ai system
How it works
Our AI is not a ChatBot. It is a 1) state-of-the-art algorithm that structures published research and links it to clinical outcomes 2) LLMs trained as classifiers on this data to predict the likelihood of approval for novel therapy candidates.
1M drug discovery publications across 5,846 rare diseases, matched with outcomes as a training dataset.
10,000+ orphan designations and 1,200+ approvals as positive outcomes.
LLMs incorporate learnings from all previous drug discovery results into every new decision.
Understanding patterns that surpass human reasoning.
De-Risking Decisions
Frequently Asked Questions
How are results validated?
Explority AI was tested through a quasi-prospective validation of its LLM classifiers, which were trained on articles published up to the 2019 knowledge cutoff. The validation included 83,501 new drug candidates described in the literature and used new orphan drug designations (2019–2025) across 5,846 rare diseases as the outcome measure. As a result, Explority AI identified 50.7% of orphan therapies that would eventually reach approval – on average 2.5 years earlier and with greater precision than the industry’s average success rate, demonstrating the potential to increase early-stage pipeline success rates by 31%.
How can I get access to the Explority AI platform?
To get access, please book a demo meeting with our team. During the session, we will walk you through the platform and showcase personalized, highest-potential therapy candidates tailored to your pipeline or partnership focus areas.
How Explority AI is validated to assess the accuracy of early-stage forecasts, delivering precision that consistently exceeds industry success rates:
01
Quasi-prospective validation across 5,846 rare diseases
Trained on literature published up to 2019, we validated our LLMs on 83,501 new drug candidates mentioned in these texts and used new orphan drug designations (2019–2025) as positive outcomes.
02
Outperforming industry in precision
Explority AI identified 50.7% of orphan therapies that would reach approval – on average 2.5 years earlier and with greater precision than the industry’s average success rate.
03
Boosting early-stage success rates
With a validated +31% increase in average early-stage success rates, accelerating development timelines and improving decision-making across rare disease drug pipelines and partnerships.
