Our Approach

mRNA Lightning™ is a novel platform at the intersection of mRNA biology and AI.

Our differentiated approach is based on breakthrough mRNA biology imaging technologies that visualize the biology of mRNA across its life cycle in cells. The mRNA Lightning platform builds on this unique capability with image neural networks that recognize disease signatures and together with our large language model and AI co-pilot rapidly decode the mRNA biology signature underlying the disease, identify active compounds against it, and uncover their mechanisms of action and molecular targets.

Our automated tera-scale mRNA biology lab ran millions of experimental data points where it generated billions of mRNA biology images in dozens of disease models, resulting in the world’s largest dataset of mRNA biology visualizations.

Our disease-specific mRNA image analysis neural networks are trained with this data, thereby growing the ability to visually recognize mRNA regulatory pathways that differentiate healthy from diseased cells. This elucidates a unique mRNA biology signature underlying the disease and determines the best pathway to target to achieve a therapeutic effect.

Once the mRNA biology disease signature is determined, it is used to guide the design of a disease-specific compound library to be used in an automated high-content screen. To achieve this, the system generates variations around compounds whose chemical structures have already shown activity in the signature selected pathway. This results in an optimized library that is focused on a chemical space selective to the mechanisms we are trying to target.

Using this library, we run a high-content screen where we conduct millions of experiments where library compounds are tested for their effect on the selected mRNA biology pathway.

The effect of compounds is observed in the images as they go through the mRNA image network, looking for compounds that visually appear to modify the image from a diseased to a healthy state for the chosen mRNA biology signature.

These hit compounds are considered promising candidates for further progression since they target a disease-relevant pathway phenotype with a strong rationale for their mechanisms of action.

Along the way we have amassed a tremendous amount of mRNA biology expertise and knowledge that is continuously updated in our mRNA biology LLM, an augmented large language model that is used by the Lightning AI co-pilot, an mRNA AI biologist that works hand in hand with scientists along the drug discovery process, suggesting hypotheses for MOAs and molecular targets along with validation experiments.

Our platform has been validated in the discovery of small molecule mRNA drugs in our wholly-owned pipeline across several therapeutic areas and in our large-scale collaborations with Lilly, Takeda, and AbbVie.