The first discovery platform where Computational and Experimental AI work in a continuous loop to uncover biology, discover targets and drugs, and accelerate breakthrough therapies.
The Future of Drug Discovery Isn’t Predicted - It’s Seen
Biology speaks in pathways - not endpoints or clusters.
Lightning AI visualizes disease in motion, inside real cells - revealing what drives it and how to intervene.
Two AIs. One Discovery Loop.
Not a lab in a loop.
Lightning AI connects Computational and Experimental AI in a continuous feedback loop - each generating and refining insight.
Iterative discovery that learns, improves, and converges on what matters.
Computational AIHypotheses at Scale
Our Computational AI integrates multi-omics, literature, and customer data to generate thousands of mechanistic hypotheses per disease.
It prioritizes pathways likely to drive disease and frames the key questions for exploration.
Experimental AIVisualizing, Learning, Refining
Experimental AI doesn’t test - it sees.
It visualizes each hypothesis across millions of healthy and diseased cells, revealing pathway behavior, functional phenotypes, and biological signals.
It learns from what it sees - and feeds that insight back into the loop.
From 1,000 Hypotheses to 1 Billion Experiments. Instantly.
Thousands of hypotheses. Millions of patient-derived cells.
Every hypothesis explored in parallel - over a billion experiments in a single run.
Discovery at AI scale.
PathwayLight™ - Biology You Can See.
PathwayLight™ visualizes how thousands of pathways behave inside real cells.
Not morphology. Not surface phenotype.
This is imaging at the level of biological function - pathways, not shapes.
Morphology is sign language. Pathways are the native language of biology.
PathwayLight Neural Network - The AI Inside the Biology.
Trained on billions of images, this neural network compares healthy and diseased cells millions of times for every hypothesis.
It identifies dysregulation, recognizes phenotypes, and drives the discovery loop forward.
Visualizing the Full Complexity of Disease
Diseases live in systems, not single cells. Lightning AI visualizes biology from tissue context to individual cells, adapting to each disease model.
Complexity, captured at the right resolution.
A Discovery Loop That Delivers Novel, Yet Druggable Targets
This isn’t biology for exploration’s sake.
The loop is built to deliver druggable targets - novel, mechanistically defined, and directly linked to disease biology.
Targets the system sees, understands, and enables you to act on.
Validating Targets with Visual Pathway Knockouts
Target confidence matters.
Lightning AI applies a proprietary method of Visual Pathway Knockouts - disrupting the target’s pathway and observing biological consequences at scale.
The effect is seen, not inferred - validating both pathway and target in full biological context.
The mRNA Biology Neural Network – From Target to Modulation Strategy
A second neural network trained on mRNA regulation across thousands of pathways.
It explores each target’s mRNA biology - uncovering how to modulate it through splicing, RBPs, localization, degradation, or translation.
Modulation by mechanism, not guesswork.
Chemistry That Targets the Target
Once a modulation strategy is identified, Lightning AI generates a focused small molecule library designed to act through the specific biology of the target.
As compounds are screened, the neural network visualizes their effect on disease pathways in real cells - confirming impact and optimizing intervention.
Drugging the biology, not just the target.
A Proprietary Data Engine: The Visual Biology of Disease
Lightning AI generates a new class of biological data: functional, spatial, and visual.
This data doesn’t exist in omics.
It becomes your exclusive, proprietary advantage.
Our Partners
We work with pharma and technology leaders to transform how new drugs are discovered.
If you build platforms, run infrastructure, or drive pipelines write to [email protected].
Let’s talk!
Let’s Redefine What’s Possible
Not predicted. Not validated. Discovered.
Two AIs. One loop. From biology to targets to drugs.
The mRNA Biology Community
As the leader in mRNA biology research with a platform that spans multiple applications, Anima has initiated the LightON mRNA Community, which now includes over 5,000 mRNA biology experts and enthusiasts from industry and the academy.
Our running webinar series provides free valuable educational insights, covering the applications of researching mRNA biology for target discovery, drug discovery, and optimization of mRNA vaccines and RNA-based drugs.
mRNA Biology Modulators Pipeline
Anima's wholly-owned pipeline of mRNA biology modulators is in Immunology (Lung fibrosis candidate advancing in preclinical stage), in Oncology (Solid tumors lead compounds entering preclinical stage and additional programs against Lymphoma and Neuroblastoma), in Neuroscience (Alzheimer's disease and Pain). In addition to our own pipeline, we established strategic collaborations with Pharma in partnered programs including our collaborations with Lilly, Takeda Pharmaceuticals, and Abbvie.
| Indication | Target | Discovery |
Optimization |
Preclinical |
|
|---|---|---|---|---|---|
Immunology |
|||||
| Lung fibrosis | 1 | ||||
| Multiple fibrosis | 2 | ||||
| Multiple fibrosis | 3 | ||||
| Undisclosed | |
4 | |||
Oncology |
|||||
| Solid tumors | 5 | ||||
| Solid tumors | 6 | ||||
| Leukemia | 7 | ||||
| Neuroblastoma | 8 | ||||
| Solid tumors | 9 | ||||
| Undisclosed | |
10 | |||
| Undisclosed | 11 | ||||
Neuroscience |
|||||
| Alzheimer | 12 | ||||
| Pain | 13 | ||||
| Undisclosed | 14 | ||||
| Undisclosed | |
15 | |||
| Undisclosed | 16 | ||||
| Huntington | 17 | ||||
| Undisclosed | |
18 | |||
| Undisclosed | 19 | ||||
| Undisclosed | 20 | ||||
| Area | Indication | Target | Discovery |
Optimization |
Preclinical |
||
|---|---|---|---|---|---|---|---|
| Immunology | Lung fibrosis | 1 | |||||
| Multiple fibrosis | 2 | ||||||
| Multiple fibrosis | 3 | ||||||
| Undisclosed | |
4 | |||||
| Oncology | Solid tumors | 5 | |||||
| Solid tumors | 6 | ||||||
| Leukemia | 7 | ||||||
| Neuroblastoma | 8 | ||||||
| Solid tumors | 9 | ||||||
| Undisclosed | |
10 | |||||
| Undisclosed | 11 | ||||||
| Neuroscience | Alzheimer | 12 | |||||
| Pain | 13 | ||||||
| Undisclosed | 14 | ||||||
| Undisclosed | |
15 | |||||
| Undisclosed | 16 | ||||||
| Huntington | 17 | ||||||
| Undisclosed | |
18 | |||||
| Undisclosed | 19 | ||||||
| Undisclosed | 20 | ||||||
17 Scientific Collaborations
16 Peer Reviewed Publications
-
Virtual plates: Getting the best out of high content screens
SLAS Discov (2023) Nov 29:S2472-5552(23) -
Measuring mRNA translation in neuronal processes and somata by tRNA-FRET
Nucleic Acids Res. 2020 ;46(6):e32 -
A heterogeneous tRNA granule structure exhibiting rapid, bi-directional neuritictransport
Eur J Cell Biol (2018) ; 97 : 168-179. -
Monitoring protein synthesis in single live cancer cells
Integr Biol (2016); 8 :645-53
Coverage
News & Events
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RNA Leaders Europe Congress 2024
When:
Where: Basel, SwitzerlandAnima’s Vice President of Business Development, Gal Gur, Ph.D., will participate in the upcoming congress during in two roundtable sessions, both focused on the topic of, “Target selection – lessons learned from small molecules RNA Biology,” to discuss her learnings from working on target selection in...
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Anima Biotech Announces Preclinical Data of Candidate in Idiopathic Pulmonary Fibrosis
When:
Anima Biotech, the Tech.Bio leader bringing AI to mRNA biology, announced today positive preclinical data of its lung fibrosis candidate. This drug operates through a novel mRNA biology mechanism of action, opening new avenues for treating Idiopathic Pulmonary Fibrosis (IPF) patients.
Utilizing its mRNA Lightning™... -
6th Annual RNA-Targeted Drug Discovery and Development Summit
When:
Where: Boston, MAAnima Biotech will participate in the 6th Annual RNA-Targeted Drug Discovery and Development Summit taking place in Boston, MA from December 12-14, 2024. Our Vice President of Business Development, Gal Gur, Ph.D., will participate on a panel titled, “Overcoming Key Challenges to Improve Drug Design & Discovery...