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mRNA Lightning™ Platform Technologies

Visualizing and decoding mRNA biology

A decade of platform evolution

Over a decade ago, we introduced TranslationLight, a breakthrough patented technology that visualizes the translation of mRNAs into proteins. Since then, we have continued to innovate and lead the field of mRNA visualization technology.

mRNA Lightning 2.0 added TranscriptLight, the ability to visualize mRNA transcripts, along with dozens of mRNA MOA assays and MOAi, our AI-driven mechanism of action identification technology. We established the Tera-Scale mRNA Biology Lab, an automated high-content at high-throughput platform in mRNA research.

mRNA Lightning 3.0 is the latest generation of our platform. It combines computational and experimental biology under a single AI framework, establishing a new paradigm of visualizing and decoding mRNA biology with applications in mRNA drugs, targets, and vaccines discovery. PathwayLight technology enables a full-spectrum molecular pathway visualization. We created a proprietary dataset of over 2 billion mRNA biology images and trained disease-specific mRNA image neural networks to recognize and elucidate disease signatures, mRNA pathways that underly disease mechanisms. In applications of mRNA vaccines and RNA-based drugs, the network is trained to recognize and compare “visual design signatures”, ranking mRNA-based drug and vaccine designs for rapid data-driven optimization cycles.

mRNA biology imaging at this scale creates a visual drug-mine that was never accessible before. AI technology enables the decoding of this vast amount of data into our mRNA biology knowledge graph which is built from curated publications in mRNA research and thousands of experimental results from our projects across diseases, targets, and cell types. The Lightning AI co-pilot is used to query the knowledge graph, using the mRNA Biology LLM in based chat-based interface.

1.0
Translation Light
Dozens of mRNA
MOA assays
2.0
TranscriptLight
Proprietary mRNA Biology Data
3.0
PathwayLight
mRNA biology lab
Tera-scale operations
AI-driven MOA
elucidation
mRNA Image
Neural Network
mRNA Lightning
AI co-pilot
disease-specific
library design
mRNA AI technologies
mRNA Biology
LLM

mRNA Biology data

We have generated over 2 billion images of mRNA biology and a large-scale mRNA biology knowledge graph. We apply AI technologies over this extensive dataset to elucidate disease biology.

2B mRNA Biology Images

The world’s largest dataset of mRNA biology visualizations generated by our mRNA Biology technologies in multiple disease models and cell types, used for training the mRNA Image Network.

mRNA Biology data

We have generated over 2 billion images of mRNA biology and a large-scale mRNA biology knowledge graph. We apply AI technologies over this extensive dataset to elucidate disease biology.

mRNA Biology Knowledge Graph

Standing out as the world’s first mRNA biology knowledge graph and leveraging knowledge built over a decade of our deep diving into mRNA biology, the knowledge graph integrates multiple proprietary sources such as curated publications, analyses from mRNA Lightning’s dataset of over 2 billion mRNA biology images and thousands of experimental results from our projects, across diseases, targets, and cell types.


2B mRNA Biology images analysis
mRNA regulation
curated publications
OMICS
Cis-RNA elements
Thousands of
experimental results
Codon usage analyses

mRNA Imaging technologies

mRNA Lightning imaging technologies enable visualization of the entire mRNA life cycle. These technologies were used to create our proprietary dataset of over 2 billion mRNA biology images that have trained the mRNA image neural network.

TranslationLight

Visualize mRNA translation

Originally licensed from UPENN and developed over a decade by Anima, TranslationLight enables visualization of mRNA translation, with fluorescently labeled tRNA pairs that cause the ribosomes to emit light pulses as they assemble mRNAs into proteins.


mRNA Imaging technologies

mRNA Lightning imaging technologies enable visualization of the entire mRNA life cycle. These technologies were used to create our proprietary dataset of over 2 billion mRNA biology images that have trained the mRNA image neural network.

PathwayLight

mRNA Biology pathway visualizers

Our mRNA PathwayLight technology enables the visualization of dozens of mRNA regulatory events and pathways such as splicing, localization, modification, or decay/stability. Each of these “visualizers” is built as a high-content screening assay with the images acting as visual readouts of pathway biology.

  • Transcription
  • Splicing
  • Alternative splicing
  • Capping
  • Polyadenylation
  • Modification
  • Nuclear Export
  • Transport
  • Localization
  • Stability
  • Decay
  • Translation

mRNA Imaging technologies

mRNA Lightning imaging technologies enable visualization of the entire mRNA life cycle. These technologies were used to create our proprietary dataset of over 2 billion mRNA biology images that have trained the mRNA image neural network.

TranscriptLight

Visualize mRNA transcripts

A large number of imaging assays, enabling visualization of individual or multiple mRNA transcripts across their life cycle.


Dozens of mRNA MOA assays

mRNA biology experiments are executed in the wet lab while leveraging our proprietary mRNA imaging technologies, the LLM, and the co-pilot for experiment design, sequencing, and result analysis. They rapidly elucidate the mechanism of action of active compounds, confirming disease signatures and analyzing pathways.


mRNA AI technologies

Unlike approaches where AI is used in computational attempts to simulate and predict biology or to analyze publications, the mRNA Lightning platform is applying AI to analyze visual data that comes from millions of automated biology experiments in cellular systems of disease models. We combine this data with computational biology models and our mRNA knowledge graph to elucidate underlying disease mechanisms.

mRNA Biology Lab

Tera-scale Automation

Our mRNA biology lab runs high-content at high-throughput screening in a massively parallel architecture. With a screen-to-cloud architecture, billions of images are uploaded to our cloud servers for analysis. The fully automated lab uses robotics and high-resolution microscopy, incorporating our imaging and mRNA biology assays under a single framework.


mRNA AI technologies

Unlike approaches where AI is used in computational attempts to simulate and predict biology or to analyze publications, the mRNA Lightning platform is applying AI to analyze visual data that comes from millions of automated biology experiments in cellular systems of disease models. We combine this data with computational biology models and our mRNA knowledge graph to elucidate underlying disease mechanisms.

mRNA Image Neural Network

Trained with over 2 billion mRNA visualizations, the network recognizes “disease signatures”, the mRNA regulatory pathway underlying the difference in the images of healthy and diseased cells. The network can also be trained to recognize and compare “visual design signatures”, to rank mRNA-based drugs and vaccine variants for rapid visual, data-driven optimization cycles.


mRNA Image network training for mRNA biology signature identification

Diseased
Phenotype
mRNA Biology
Visualizers
Healthy
Phenotype

mRNA AI technologies

Unlike approaches where AI is used in computational attempts to simulate and predict biology or to analyze publications, the mRNA Lightning platform is applying AI to analyze visual data that comes from millions of automated biology experiments in cellular systems of disease models. We combine this data with computational biology models and our mRNA knowledge graph to elucidate underlying disease mechanisms.

mRNA Lightning AI co-pilot

The Lightning co-pilot provides a ChatGPT-like interface across the Lightning system, enabling biologists, chemists, and data analysts to interact with the system in a seamless user experience. Using the LLM, the co-pilot translates questions in natural language into knowledge graph queries that are saved along with their results, with each step further elucidating disease biology. It also acts as a way to ask the system to plan, execute, and monitor discovery activities.


mRNA AI technologies

Unlike approaches where AI is used in computational attempts to simulate and predict biology or to analyze publications, the mRNA Lightning platform is applying AI to analyze visual data that comes from millions of automated biology experiments in cellular systems of disease models. We combine this data with computational biology models and our mRNA knowledge graph to elucidate underlying disease mechanisms.

mRNA biology LLM

Standing out as the first language model specifically targeting mRNA biology, the LLM is augmented with Anima’s proprietary knowledge and data. It enables biologists to ask questions about pathways, targets, and mechanisms of action in mRNA biology. In an iterative process of suggesting hypotheses, prioritizing wet lab experiments, and analyzing their results, all with AI working alongside biologists.

mRNA AI technologies

Unlike approaches where AI is used in computational attempts to simulate and predict biology or to analyze publications, the mRNA Lightning platform is applying AI to analyze visual data that comes from millions of automated biology experiments in cellular systems of disease models. We combine this data with computational biology models and our mRNA knowledge graph to elucidate underlying disease mechanisms.

MOAi | AI-driven MOA elucidation

Our MOAi technology elucidates the mechanism of action and molecular targets of compounds. Molecules that were found to be active as disease signature modulators are iteratively studied using the knowledge graph, the LLM, and the mRNA image neural network. Unlike purely computational AI approaches, MOAi technology integrates the data coming back from all wet lab biology experiments. It starts with the knowledge graph, using the LLM to query the identified pathway. Taking into account the compound’s chemistry, it then devises an MOA elucidation strategy by optimally sequencing the execution of our dozens of proprietary MOA assays. Experimental biological results and their associated MOA visualizations are uploaded to the system. This enables MOAi to reconsider all new data for an adjusted ranking of MOAs and targets, driving the next iteration. Throughout this process, biologists interact with the system in a natural language through the Lightning co-pilot. This AI-driven, biologist-in-the-loop approach integrates computational and wet lab biology, rapidly converging to elucidate a compound’s MOAs and molecular target.


MOA elucidation strategy