• End-to-end RNA optimization: Platform combines proprietary AI sequence optimization, novel genetic parts, and lab validation in application-relevant cell models to improve expression and half-life, delivering top candidates in weeks.
  • Broad therapeutic applicability: Supports linear mRNA and circular RNA, including applications in cell therapy, genome editing, and vaccines.
  • Proven performance: Validated in large biopharma programs, with 9x expression and 4x half-life improvement for CAR-T; 2x expression increase for Cas9.

Boston, MA, March 19, 2026–Asimov, the synthetic biology company advancing the design and manufacture of therapeutics, today announced the launch of its RNA Edge System, an integrated AI, synthetic biology, and laboratory platform to optimize RNA therapies. RNA Edge enables developers to move from a starting sequence to validated, high-performance candidates in weeks. The platform integrates data-driven models, proprietary genetic parts, and in vitro screening in application-relevant cell models.

Designing effective RNA therapies remains a significant scientific and clinical challenge. With a massive design space of possible sequences, many therapies still rely on single-variable codon optimization and legacy genetic parts, an approach that leaves substantial performance gains unrealized and contributes to clinical failures. Achieving the desired expression and durability requires simultaneous balancing of translation elongation dynamics, RNA secondary structure, and genetic part interactions, a multi-dimensional problem that necessitates an integrated approach across sequence design and lab validation.

RNA Edge is a lab-in-the-loop system built to solve this multi-dimensional design problem. The platform integrates computational design, high-performance genetic parts, and experimental validation to optimize RNA performance:

  • Multi-objective codon optimization: A novel algorithm enables up to 9x higher expression by optimizing multiple factors influencing translation efficiency, RNA structure, synthesizability, and more.
  • Genetic parts: Proprietary off-the-shelf internal ribosome entry site (IRES) elements deliver 4x higher expression than industry standards, supporting circular RNA and multi-gene constructs. Additionally, AI design and screening capabilities for untranslated regions (UTRs) provide a lever to optimize linear mRNA expression.
  • Validation in application-relevant cells: Integrated in vitro screening in application-relevant cell models provides greater insight into real-world therapeutic performance than generic cell lines.

Together, these capabilities enable systematic exploration of RNA design space and rapid validation of promising sequences, accelerating the path to high-performing therapeutic candidates.

“It’s been a rollercoaster few years for RNA therapies. The industry ramped up first-in-class vaccines globally in record-breaking time, but commercial adoption has since slowed. At the same time, promising new RNA applications in cell therapy and genome editing have come into view. But too often these therapies don’t work as well as they could in the clinic,” said Alec Nielsen, co-founder and CEO of Asimov. “Realizing the full potential of this modality requires a better design-to-data cycle. RNA Edge helps developers identify high-performing RNA candidates faster by optimizing every lever that drives expression and durability.”

Ahead of this launch, the platform has successfully delivered on two large biopharma programs. For a chimeric antigen receptor (CAR) requiring sustained expression, RNA Edge delivered sequences with 9x expression over benchmark and 4x longer half-life. For Cas9 requiring high burst expression, optimized sequences achieved up to 2x improvement over benchmark at 24 hours. Both programs were validated by the partner in application-relevant LNP formulations.

RNA Edge joins Asimov’s growing suite of genetic medicine platforms, alongside LV Edge for lentiviral vectors and AAV Edge for adeno-associated virus design and production. RNA Edge is available now for partnership engagements. Learn more at asimov.com/rna-edge-system.

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.

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
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