Synthetic biology is transforming the way we design and engineer biological systems. AI-driven solutions are accelerating advancements in genetic circuit design, metabolic pathway optimization, and bioinformatics automation, making bioengineering more precise and scalable than ever before.
But what challenges remain, and how can AI help overcome them?
What’s Inside This Whitepaper?
The role of AI in synthetic biology—from genetic engineering to enzyme optimization
Key challenges—data inconsistencies, experimental bottlenecks, and scalability issues
AI-driven solutions—automated circuit design, explainable AI models, and lab automation
Future considerations—ethics, regulatory hurdles, and AI generalizability
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