The Future of Biomanufacturing: AI-Driven Cell Line Development and Bioprocess Design

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Traditional approaches to biologics production—relying on one-size-fits-all expression vectors and empirical process optimization—have led to inefficiencies in expression, scalability, and manufacturability. While incremental improvements in cell line engineering and bioprocess modeling have driven progress, the rapid evolution of AI and digital tools is poised to reshape biopharmaceutical process development and manufacturing.

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In this GEN webinar, Thibault Laurent, an expert in cell line development and genome engineering, shares a data-driven vision for the future of biologics production and discusses progress toward holistic optimal design of cell lines, genetic systems, and bioprocesses. He will discuss how Kernel, a software design tool that powers Asimov’s CHO Edge system, can accelerate timelines and improve titers for cell line and process development. The webinar will cover case studies that demonstrate how this system delivers high-titer clones (8–11 g/L) in less than four months for monoclonal and bispecific antibodies. Finally, he will discuss broader capabilities for integrating multi-omics and bioreactor-scale models to further optimize growth, productivity, and quality.

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Highlights

Virtual Private Network (VPN): Users connect to the cluster, provide some credentials and are then able to access internal tools.

Single Sign-On: A tool like Kerberos allows you to use the same account across various components.

Home-grown user accounts: You implement an authentication system and users have a separate username/password for your computing infrastructure.

Asimov, the synthetic biology company building a full-stack platform to program living cells, announced today it has been awarded a contract as part of the Defense Advanced Research Projects Agency (DARPA) Automating Scientific Knowledge Extraction (ASKE) opportunity.

Through ASKE, Asimov will work to develop a physics-based artificial intelligence (AI) design engine for biology. The goal of the initiative is to improve the reliability of programming complex cellular behaviors.

“To achieve truly predictive engineering of biology, we require dramatic advances in computer-aided design. Machine learning will be critical to bridge genome-scale experimental data with computational models that accurately capture the underlying biophysics. As genetically engineered systems grow in complexity, they become difficult for humans to design and understand. For simple genetic systems with only a couple of genes, synthetic biologists typically use high-throughput screening and basic optimization algorithms. But to engineer more complex applications in health, materials, and manufacturing, we need radically new algorithms to intelligently design the DNA and simulate cell behavior.”

Alec Nielsen, Phd, Asimov CEO

Over the past 50 years, DARPA has been a world leader in spurring innovation across the field of AI, including statistical-learning and rule-based approaches. We are proud to work with DARPA to advance the state-of-the-art in AI-assisted genetic engineering.

Asimov’s founders previously built a hybrid genetic engineering and computer-aided design platform called Cello to program logic circuit behaviors in cells. The ASKE opportunity will seek to support an ambitious expansion in the types of biological behaviors that can be engineered.
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Asimov’s approach will leverage “multi-omics” cellular measurements, structured biological metadata, and novel AI architectures that combine deep learning, reinforcement learning, and mechanistic modeling. Over the past year, the company has ramped up hiring in experimental synthetic biology, machine learning, and data science to accelerate development of their genetic design platform.

Highlights

Headering 3

DARPA recently announced a multi-year investment of $2B into innovative artificial intelligence research called the AI Next campaign. A part of this wide-ranging AI strategy is DARPA’s Artificial Intelligence Exploration program, which was developed to help expeditiously move pioneering AI research from idea to exploration in fewer than 90 days. DARPA’s ASKE opportunity is part of this program and is focused on developing AI technologies that can reason over rich models of complex systems.

“Over the past 50 years, DARPA has been a world leader in spurring innovation across the field of AI, including statistical-learning and rule-based approaches. We are proud to work with DARPA to advance the state-of-the-art in AI-assisted genetic engineering.”

Alec Nielsen, PhD, Asimov CEO