Lightning.AI Platform Applications
From Biology to Targets to Drugs
From seeing and learning biology in action across millions of diseased cells, to discovering targets and then finding compounds that modulate those targets within their biological context, Lightning.AI is built to converge on what matters for effective drug discovery. Every step is grounded in real data - seen, understood, and actionable.
Target Discovery
Target discovery with Lightning.AI is not exploratory - it’s purpose-built to deliver novel druggable, mechanistically defined targets rooted in disease biology. At the heart of this is the PathwayLight Neural Network - the AI inside the biology.
Trained on billions of intracellular pathway images, PathwayLight Neural Network recognizes difference between healthy and diseased states. It identifies pathway dysregulation, patterns, and continuously refines the entire discovery loop to discover what truly drives disease.
Our proprietary method of Visual Pathway Knockouts validates these insights by disrupting the pathways and directly observing biological consequences at scale. The effect is seen, not inferred - providing robust, causal pathway and target in full biological context.
Lightning.AI delivers targets that are not only novel and actionable but backed by biological proof every step of the way.
Drug Discovery
Once a target is identified and linked to disease biology, the mRNA Biology Neural Network takes over. Trained on mRNA regulation across thousands of pathways, it analyses and learns the target’s mRNA biology to determine the optimal modulation strategy through mechanisms like splicing, RNA-binding proteins (RBPs), localization, degradation, or translation.
Armed with this mechanistic insight, Lightning.AI generates a focused small molecule mRNA modulators library, specifically designed to modulate the target through mRNA biology. As compounds are screened, the system sees their impact directly on disease pathways in real cells. This enables not just hit discovery, but it’s confirming that compounds modulate the biology as intended and optimizing small molecule mRNA drug candidates based on real phenotypic outcomes.
This is drug discovery driven by the biology of disease, not trial and error.