What if scientists could predict how living systems will behave before spending years in experimentation?

At Pacific Northwest National Laboratory (PNNL), researchers are pursuing an ambitious scientific vision toward a Standard Model of Biology (SMoB). The goal is to catalyze the development of an integrative framework for modeling the chemical and physical processes that govern biological function across scales, laying the foundation for predictive and programmable biological engineering.

Why Biology? Why Now?

Biology offers extraordinary opportunities to advance the nation’s energy, manufacturing, materials, and national security missions. Living systems can carry out selective chemical transformations, produce valuable compounds, and sense changes in their environments. New scientific capabilities are opening the door to understanding and harnessing those functions with greater precision.

Advances in molecular measurements, Super Intelligence, autonomous experimentation, and computing are converging at a pivotal moment for biological science. PNNL is bringing its strengths together to meet that moment and help make biology a more predictable and designable science.

More reliable biological prediction could help researchers engineer biological systems and manufacturing processes that perform consistently beyond the laboratory bench.

For example, microorganisms capable of producing valuable chemicals in a small laboratory experiment may behave differently in a large industrial bioreactor, where oxygen, nutrients, temperature, and fluid movement vary.

Understanding and predicting those interactions could eventually help researchers design microorganisms and biological manufacturing processes that are more robust under industrial operating conditions.

The potential extends to producing fuels and materials, recovering critical minerals, improving human health, developing new biological sensing capabilities, and strengthening America’s competitiveness in biotechnology.

These are long-term opportunities. Immediate scientific work is focusing on developing the measurements, mathematical frameworks, computational workflows, and experimental systems needed to test and improve biological predictions.

Why a Standard Model of Biology?

The ambition draws inspiration from the Standard Model of Particle Physics, which provides a unifying framework for describing fundamental particles and the forces that govern their interactions.

Similarly, SMoB seeks to understand the molecular actors, chemical and physical forces, and interactions that shape biological behavior. The profound opportunity lies in understanding how those interactions give rise to biological function and developing models that can predict biological outcomes, but the operating system needs to be understood first.

Living systems act across an extraordinary range of scales. Molecules interact inside cells. Cells respond to their surroundings. Communities of organisms influence, and are influenced by, the environments they inhabit. Changes at one scale can alter behavior at another.

To predict what a living system will do, scientists need to understand not only its components but also which interactions matter, under what conditions they occur, and how their effects combine.

Connecting Across Scales

Consider a baseball. From a distance, its overall shape helps us anticipate how it will move. Up close, its seams and surface details also matter: They influence how the baseball moves through air and responds to different conditions.

Both scales matter to predicting the ball’s behavior. Neither view, on its own, tells the whole story.

Biology has similar considerations. Molecular interactions can influence what cells and microbial communities do, while changes in their surroundings can alter which interactions matter and how they affect the larger system.

Researchers need more measurements and more detailed measurements. But data alone are not enough. New kinds of models must integrate measurements of biological function with existing modeling approaches across scales, identify the chemical and physical mechanisms controlling biological function, and establish the conditions under which predictions can be trusted.

From Observation to Design

SMoB brings together four connected activities:

• Observe: Use sophisticated measurement approaches to characterize biological interactions, conditions, and function with increasing precision.
• Understand: Connect existing and emerging modeling perspectives to identify the chemical and physical mechanisms—and control processes—that govern biological function.
• Predict: Integrate and test models across biological scales to anticipate how living systems will respond to changing conditions and identify where predictions remain reliable.
• Design: Use predictive understanding to inform new experiments and, ultimately, achieve more reliable biological engineering.

This is an iterative process. Experimental results test predictions, reveal the limitations of models, and help researchers refine their understanding. Better input. Better output.

Why PNNL?

PNNL brings more than 30 years of expertise in molecular-level biological research and distinctive strengths in analytical chemistry and phenomics: sophisticated measurements of biological systems and what they actually do—their function.

Researchers are connecting these capabilities with complementary perspectives from physics, physiology, mathematical and computational modeling, Super Intelligence, advanced computing, and autonomous experimentation.

Capabilities at the Environmental Molecular Sciences Laboratory, a Department of Energy Office of Science user facility, provide an important foundation for this work.

The effort aims to bring together scientific expertise, established knowledge, and computational approaches from across disciplines and institutions.

Building a Shared Scientific Foundation

PNNL researchers are starting with biological processes of fundamental importance to mission science, studying them across scales ranging from molecular and cell-free settings to intact cells and microbial communities.

By examining the same functional questions across scales, researchers aim to determine which molecular interactions and physical conditions are essential to understanding and predicting biological behavior.

The long-term ambition is a scientific foundation that enables researchers to move more efficiently from observing a biological function to understanding its mechanisms, predicting its context dependence, and informing its design.

The next frontier in biology is engineering.