Customer Stories / Life Sciences / Germany

2025
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Cambrium Advances Protein Design and Develops Sustainable Materials 5 Times Faster Using AWS

Biotech startup Cambrium is using Amazon SageMaker, AWS Batch, and more to design sustainable, high-performance materials through protein engineering powered by artificial intelligence.

100 milliseconds

to process queries across millions of proteins

5x

faster material development

20x

more cost-effective material development

95%

fewer emissions than traditional materials

Overview

Sustainability is becoming increasingly critical for businesses across industries, from manufacturing to consumer goods. As organizations look to reduce their environmental impact while maintaining or improving performance, they face the challenge of finding sustainable alternative materials.

That’s why Cambrium is combining biotechnology with artificial intelligence (AI) on Amazon Web Services (AWS). The startup is creating everything from skin care ingredients to industrial materials, proving that sustainability and superior performance can go hand in hand.

Opportunity | Transforming Materials Manufacturing

Founded in 2020, Cambrium set out to transform the materials industry. “Materials are everywhere around us,” says Pierre Salvy, chief technology officer of Cambrium. “They’re also responsible for 23 percent of global greenhouse gas emissions.”

To develop more sustainable alternatives, Cambrium requires a robust infrastructure that can handle complex protein design and analysis at scale. In early 2024, the startup migrated its protein vectorization engine to AWS to scale its protein design pipeline. Cambrium also participated in the NVIDIA Inception, program, gaining early access to deep-learning containers that are optimized for life sciences workloads.

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The real value add of AWS is scalability. We can ramp up our test dataset from 5 items to 5,000 to a million within 2 hours.”

Pierre Salvy
Chief Technology Officer, Cambrium

Solution | Processing Millions of Proteins in Milliseconds

In just one month, a single Cambrium team member can build an entirely new protein analysis pipeline on AWS. When new protein files are uploaded to Amazon Simple Storage Service (Amazon S3), an object storage service, the pipeline is automatically triggered. This initiates a job running on AWS Batch, a fully managed batch computing service, to prepare and clean the data.

These prepared files are then processed using NVIDIA-accelerated containers, which transform the proteins into vectors that are stored for future analysis. The company uses NVIDIA’s BioNeMo, a generative AI platform for chemistry and biology, for this. Using BioNeMo–provided ESM models makes it possible for Cambrium to seamlessly integrate optimized protein vectorization endpoints into the stack.

The startup also uses Amazon SageMaker, a fully managed machine learning service, to manage its machine learning operations and develop new AI models. Using Amazon SageMaker, Cambrium develops and trains its own foundation models for protein analysis.

“The real value add of AWS is scalability,” says Salvy. “We can ramp up our test dataset from 5 items to 5,000 toa million within 2 hours.” Using this pipeline, Cambrium can process queries across millions of proteins in less than 100 milliseconds.

Outcome | Delivering Results Today While Building Tomorrow’s Materials

With these capabilities, Cambrium can develop sustainable materials 5 times faster and 20 times more cost-effectively than with traditional industry methods. The startup has used its pipeline to develop NovaColl, a sustainable collagen created through precision fermentation rather than animal products. This bioidentical protein not only produces 95 percent fewer emissions than traditional collagen but also outperforms it in skin care applications.

But this is just the beginning. “With the other materials that we have planned, we have the potential to save 4,000 million tons of carbon emissions by 2050,” says Salvy.

Given Cambrium’s ambitious future plans, using the right technology is crucial—and the startup will continue to innovate on AWS. “The scalability and integrated AI services of AWS are exactly what we need,” says Salvy.

About Cambrium

Cambrium designs and manufactures novel material building blocks. Using biotechnology and artificial intelligence, the company’s team of scientists, engineers, designers, and business developers creates sustainable alternatives to traditional materials.

AWS Services Used

Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

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Amazon SageMaker

Amazon SageMaker is built on Amazon’s two decades of experience developing real-world ML applications, including product recommendations, personalization, intelligent shopping, robotics, and voice-assisted devices.

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AWS Batch

AWS Batch is a fully managed batch computing service that plans, schedules, and runs your containerized batch ML, simulation, and analytics workloads across the full range of AWS compute offerings, such as Amazon ECS, Amazon EKS, AWS Fargate, and Spot or On-Demand Instances.

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