Artificial Intelligence

DeepCyte Raises US$1.5M to Use AI and Single-Cell Analysis to Predict Drug Toxicity

A new approach examines how individual cells respond to drugs, aiming to identify risks earlier in development.

Updated

April 15, 2026 6:01 PM

Close up of a capsule blister pack. PHOTO: UNSPLASH

DeepCyte, a startup in the drug development space, is focusing on a long-standing problem: why drugs that appear safe in early testing still fail in clinical trials or are withdrawn later due to toxicity. DeepCyte has launched with US$1.5 million in seed funding to build tools that detect and explain the harmful effects of drugs at much earlier stages.

The startup’s approach focuses on how individual cells respond to a drug. Instead of analysing cells in bulk, it studies them one by one. This helps capture differences in how cells react, which are often missed in traditional testing methods.

Drug toxicity remains one of the main reasons for failure in drug development. Methods such as animal testing and bulk cell analysis do not always reflect how human cells behave. This gap has pushed the industry to look for more reliable and human-relevant ways to test drug safety.

DeepCyte combines cell-level data with artificial intelligence. Its platform, MetaCore, studies what is happening inside individual cells by capturing detailed molecular information. This data is used to build large datasets that can train AI models.

Additionally, the company has developed an AI system called DeeImmuno. It is designed to predict whether a drug could be toxic and identify the biological reasons behind it. In internal testing on 100 drugs, the system identified different types of toxicity and their underlying mechanisms with a reported accuracy of 94 percent.

The focus on explaining why a drug is toxic, not just whether it is, reflects a broader shift in the industry. Regulators such as the U.S. Food and Drug Administration and the European Medicines Agency have been encouraging methods that rely more on human cell data and clearer biological evidence. The seed funding will be used to develop and scale these tools. The company aims to help drug developers make earlier decisions, which could reduce costly failures in later stages. Whether tools like this become widely used will depend on how they perform in real-world settings. For now, DeepCyte’s approach highlights a growing effort to make drug testing more precise by focusing on how drugs affect cells at the most detailed level.

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Deep Tech

How a South Korean University Team Is Turning Industrial Air Into Power

A turbine-inspired generator shows how overlooked industrial airflow could quietly become a new source of usable power

Updated

February 12, 2026 4:43 PM

Campus building of Chung-Ang University. PHOTO: CHUNG-ANG UNIVERSITY

Compressed air is used across factories, data centers and industrial plants to move materials, cool systems and power tools. Once it has done that job, the air is usually released — and its remaining energy goes unused.

That everyday waste is what caught the attention of a research team at Chung-Ang University in South Korea. They are investigating how this overlooked airflow can be harnessed to generate electricity instead of disappearing into the background.

Most of the world’s power today comes from systems like turbines, which turn moving fluids into energy or solar cells, which convert sunlight into electricity. The Chung-Ang team has built a device that uses compressed air to generate electricity without relying on traditional blades or sunlight.

At the center of the work is a simple question: what happens when high-pressure air spins through a specially shaped device at very high speed?  The answer lies in the air itself. The researchers found that tiny particles naturally present in the air carry an electric charge. When that air moves rapidly across certain surfaces, it can transfer charge without physical contact. This creates electricity through a process known as the “particulate static effect.”

To use that effect, the team designed a generator based on a Tesla turbine. Unlike conventional turbines with blades, a Tesla turbine uses smooth rotating disks and relies on the viscosity of air to create motion. Compressed air enters the device, spins the disks at high speed and triggers charge buildup on specially layered surfaces inside.

What makes this approach different is that the system does not depend on friction between parts rubbing together. Instead, the charge comes from particles in the air interacting with the surfaces as they move past. This reduces wear and allows the generator to operate at very high speeds. And those speeds translate into real output.

In lab tests, the device produced strong electrical power. The researchers also showed that this energy could be used in practical ways. It ran small electronic devices, helped pull moisture from the air and removed dust particles from its surroundings.

The problem this research is addressing is straightforward.
Compressed air is already everywhere in industry, but its leftover energy is usually ignored. This system is designed to capture part of that unused motion and convert it into electricity without adding complex equipment or major safety risks.

Earlier methods of harvesting static electricity from particles showed promise, but they came with dangers. Uncontrolled discharge could cause sparks or even ignition. By using a sealed, turbine-based structure, the Chung-Ang University team offers a safer and more stable way to apply the same physical effect.

As a result, the technology is still in the research stage, but its direction is easy to see. It points toward a future where energy is not only generated in power plants or stored in batteries, but also recovered from everyday industrial processes.