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focusing on a long-standing problem: why drugs that appear safe in early testing still fail in clinical trials or are withdrawn later due to toxicity.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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Strategy & Leadership

Why TIER IV Is Backing a Taiwan Startup to Push Autonomous Driving Forward

Inside a partnership showing how open-source platforms and startups are scaling autonomous driving beyond the lab.

Updated

January 8, 2026 6:30 PM

A Robotaxi prototype developed by TIER IV. PHOTO: TIER IV

Autonomous driving is often discussed in terms of futuristic cars and distant timelines. This investment is about something more immediate. Japan-based TIER IV has invested in Turing Drive, a Taiwan startup that builds autonomous driving systems designed for controlled, everyday environments such as factories, ports, airports and industrial campuses. The investment establishes a capital and business alliance between the two companies, with a shared focus on developing autonomous driving technology and expanding operations across Asia.

Rather than targeting open roads and city traffic, Turing Drive’s work centres on places where vehicles follow fixed routes and move at low speeds. These include logistics hubs, manufacturing facilities and commercial sites where automation is already part of daily operations. According to the release, Turing Drive has deployments across Taiwan, Japan and other regions and works closely with vehicle manufacturers to integrate autonomous systems into special-purpose vehicles.

The investment also connects Turing Drive more closely with Autoware, an open-source autonomous driving software ecosystem supported by TIER IV. Turing Drive joined the Autoware Foundation in September 2024 and develops its systems using this shared software framework. TIER IV’s own Pilot.Auto platform, which is built around Autoware, is used across applications such as factory transport, public transit, freight movement and autonomous mobility services.

Through the alliance, TIER IV plans to work with Turing Drive to further develop autonomous driving systems for these controlled environments, while strengthening its presence in Taiwan and the broader Asia-Pacific region. The collaboration brings together software development and on-the-ground deployment experience within markets where autonomous driving is already being tested in real operational settings.

“This partnership with Turing Drive represents a significant step forward in accelerating the deployment of autonomous driving across Asia”, said TIER IV CEO Shinpei Kato. “At TIER IV, our mission has always been to make autonomous driving accessible to all. By collaborating with Turing Drive, which has demonstrated remarkable achievements in real-world deployments in Taiwan, we aim to deliver autonomous driving that enables a safer, more sustainable and more inclusive society”.  

“We are thrilled to establish this strategic alliance with TIER IV, a global leader in open-source autonomous driving”, said Weilung Chen, chairman of Turing Drive. “In Taiwan, autonomous driving deployment is gaining significant momentum, particularly across logistics hubs, ports, airports and industrial campuses. By combining our field expertise with TIER IV's world-class Pilot.Auto platform, we aim to accelerate the development of practical, commercially viable mobility services powered by autonomous driving”. Overall, the investment highlights how autonomous driving in Asia is being shaped by operational needs and gradual integration, rather than headline-grabbing demonstrations.