Asimov

For adeno-associated viral gene therapies to scale, scientists must first address safety and manufacturability challenges. Improving payload design and optimizing production systems can help scientists address those challenges and ensure the safety, efficacy, and scalability of their therapies.

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In this GEN webinar, Mark Stockdale will discuss how the application of synthetic biology and artificial intelligence can be used to improve the safety, potency and manufacturability of gene therapies, and introduce AAV Edge, a comprehensive platform for end-to-end gene therapy optimization—from payload design to production cell lines and model-guided processes.

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Key topics that will be covered in the webinar include:

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- How an in-house transformer-based model is used to design tissue-specific promoters, resulting in a more than 200-fold dynamic range in expression between on-target vs. off-target tissues.

- How sequence optimization boosts expression for clinically relevant transgenes up to 7-fold.- How silencing of transgene expression in the production cell line can reduce cellular stress and toxicity during the manufacturing process.

- How the combination of Asimov’s clonal HEK293 cell line, optimized two-plasmid system, and model-driven process development achieves unconcentrated titers of up to 1E12 viral genomes per milliliter across multiple serotypes.

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

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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

Improving Gene Therapy Design and Manufacturability Using Synthetic Biology and AI

Highlights

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