Biology has traditionally been treated as a field focused on observation and slow experimentation. Work in this area has relied on manual laboratory processes, where experiments are carried out step by step, and results are produced over extended periods. This structure limits how quickly biological ideas can be tested, compared, and refined.

Ginkgo Bioworks was founded in 2008 by scientists from MIT, including Tom Knight, Jason Kelly, Barry Canton, and Reshma Shetty. The group shared a belief that biology could be treated as an engineering discipline. Instead of viewing cells only as natural systems to study, they can be designed to perform defined functions in a controlled and repeatable way.

The company was built around this idea of biological engineering at scale. Rather than relying on isolated experiments, the focus was placed on building infrastructure that supports large volumes of biological design work. This includes automated systems that allow experiments to be run continuously, with software coordinating experimental design and robotics handling execution.

In this structure, cells are treated as programmable units. Scientists define biological goals, and automated systems carry out the experimental work needed to test and refine those goals. This reduces dependence on manual laboratory workflows and increases the volume of experimentation that can be performed.

Automated Laboratories and Biological Testing

Traditional biological research depends heavily on manual work such as preparing samples, running tests, and recording results. Each step must be performed individually, which limits both speed and scale. This makes it difficult to explore many variations of a biological design at the same time.

Ginkgo replaces much of this manual work with automated laboratory systems. Robotics performs repetitive physical tasks, while software coordinates the flow of experiments. Scientists design what needs to be tested, and machines execute the process.

This structure allows multiple experiments to run in parallel. It also reduces delays caused by manual handling. As a result, more biological data can be generated within the same timeframe.

The role of scientists changes within this system. Instead of spending most of their time performing laboratory tasks, they focus on designing experiments and analyzing results. Execution is handled by automated systems, while interpretation remains a human responsibility.

This setup is used across several industries, including pharmaceuticals, agriculture, and industrial biotechnology. Each sector applies biological engineering differently, but the underlying system for experimentation remains consistent.

Designing Cells for Industrial Use

Ginkgo works on the principle that cells can be engineered to perform specific industrial tasks. These tasks include producing chemicals, enzymes, and other biological materials used in manufacturing and healthcare.

Instead of relying entirely on traditional chemical production methods, biological systems are designed to produce outputs through engineered organisms. This is done by modifying genetic structures and testing different biological configurations.

The development process is iterative. Scientists design a biological system, run experiments, evaluate results, and refine the design. This cycle repeats until the desired performance is achieved. Automated systems support this process by running large numbers of experiments and generating detailed datasets.

Organizations that do not have internal laboratory infrastructure can use Ginkgo’s platform to develop biological systems. This allows them to test designs without building their own experimental facilities. Ginkgo provides the infrastructure, while external partners apply results within their industries.

This separation allows biological design and industrial application to operate as distinct layers within the same system.

Platform Structure and Industry Collaboration

Ginkgo operates as a platform that supports biological engineering across multiple industries. Instead of focusing on a single product, the company provides infrastructure that can be used for a wide range of biological development work.

Clients include pharmaceutical companies, industrial manufacturers, and other organizations working with biological systems. Each client uses the platform for different goals, such as drug development, material production, or organism engineering.

The platform includes automated laboratories, software systems, and data infrastructure. These components allow external organizations to conduct biological experiments without building their own facilities.

Data generated from experiments is collected and analyzed to improve future designs. Each round of testing feeds into the next stage of development, creating a continuous cycle of experimentation and refinement.

This structure allows biological engineering to be accessed as a service rather than an internal capability that must be built from scratch.

Scaling Biology Through Automation and Data

A central part of Ginkgo’s system is the use of automation to increase the scale of biological experimentation. Robotics handles physical laboratory tasks, while software manages planning, coordination, and analysis.

This allows thousands of experiments to be run at the same time. Manual laboratory methods cannot match this level of throughput due to time and labor constraints.

Data plays a key role in improving biological design. Experimental results are collected and analyzed to identify patterns and guide future work. Instead of relying on individual experiments in isolation, the system uses large datasets to refine biological systems over time.

This creates a structured cycle of design, testing, and analysis. Each experiment contributes information that informs the next stage of development.

Redefining How Biology is Used in Industry

Ginkgo’s work changes how biology is applied in industrial settings. Biological research is no longer limited to small-scale manual experiments. It is carried out through automated systems that support large volumes of parallel testing.

This allows many biological variations to be explored at once. Results are produced faster, and designs can be refined through repeated cycles of experimentation.

Biology becomes organized around engineering principles. Systems are designed, tested, and improved in a structured way supported by automation and data.

Dr. Jason Kelly, Co-Founder & CEO, Ginkgo Bioworks