Initiative

Predictive Phenomics

Predictive Phenomics will address the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems.

Predictive Phenomics

Illustration by Stephanie King

The Predictive Phenomics Initiative (PPI) is an internal investment at the Pacific Northwest National Laboratory (PNNL) that’s focused on unraveling the mysteries of molecular function in complex biological systems. 

How can we harness microbes to create new products in the bioeconomy? Use artificial intelligence and automation to advance phenotyping? Develop computational methods to predict and control the phenome?

These are big questions with intricate answers, and we begin answering them by identifying a phenotype.

Phenomenal Phenomes

A researcher takes a sample from a bioreactor.

Predictive phenomics is a scientific superpower—by understanding phenotypes, we can do phenomenal things.
Explore the possibilities

A phenome is a collection of phenotypes—characteristics or traits of a system or organism. Within PPI, researchers are identifying desirable phenotypes, or functions, in a biological system (e.g., improving robustness of microbial systems for biomanufacturing), developing sophisticated models to help us understand how those functions change when the environment is subjected to change, and incorporating artificial intelligence and automation into our experimental design to accelerate scientific discovery.

The research requires a fine-tuned understanding across many scales of the cellular systems, including an organism’s proteins, metabolites, genes, and more. It also marks a move toward a "post-genomic world" where we can overcome the trial-and-error limitations of current genetic engineering efforts by precisely predicting the effects of genetic and environmental changes on an organism.

PPI leadership and principal investigators are collaborating with other PNNL-led efforts such as the Foundational Autonomy Investment (FAI) and the Environmental Molecular Sciences Laboratory’s (EMSL’s) forthcoming Microbial Molecular Phenotyping Capability (M2PC) to “close the experimental loop.” 

While scientists focus on what they do best, robots and AI agents—modified and trained by PPI scientists—will expedite experimental design, prep, and analysis at an exponential rate. 

Taking the Initiative 

Now in its fifth year, PPI is an umbrella for 11 interwoven research projects aimed at fostering energy abundance, advancing the bioeconomy, improving human health, and bolstering national security.

The project teams include researchers with varied scientific disciplines, and they rely on PNNL's expertise in molecular measurements, bioscience, artificial intelligence, chemistry, engineering, data analytics, and modeling to realize the power of predictive phenomics.

Related Divisions

Key Capabilities

Facilities