构建可预测编程生命的多尺度AI生物系统
Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels
- 用模块化多尺度基础模型构建数字生命体
- 实现从分子到个体的生物系统仿真与编程
- 适合生物工程、药物研发等领域的高效探索
我们提出一种利用AI建模和模拟生物学的方法。为何重要？因为医学、药学、公共卫生、长寿、农业与粮食安全、环境保护及清洁能源的核心都是生物学。现实中的生物系统过于复杂，难以操控，且实验成本高、风险大。为此，我们提出构建人工智能驱动的数字生物体（AIDO），由集成的多尺度基础模型组成，以模块化、可连接、整体化的方式反映生物的尺度、关联性与复杂性。AIDO提供了一种安全、低成本、高通量的平台，可在分子、细胞、个体等所有层面实现生物学的预测、仿真与编程。我们预期，AIDO将推动更精准的湿实验设计与更可靠的原理性推理，最终帮助我们更好地解码并优化生命。
原文摘要 · Abstract (English)
We present an approach of using AI to model and simulate biology and life. Why is it important? Because at the core of medicine, pharmacy, public health, longevity, agriculture and food security, environmental protection, and clean energy, it is biology at work. Biology in the physical world is too complex to manipulate and always expensive and risky to tamper with. In this perspective, we layout an engineering viable approach to address this challenge by constructing an AI-Driven Digital Organism (AIDO), a system of integrated multiscale foundation models, in a modular, connectable, and holistic fashion to reflect biological scales, connectedness, and complexities. An AIDO opens up a safe, affordable and high-throughput alternative platform for predicting, simulating and programming biology at all levels from molecules to cells to individuals. We envision that an AIDO is poised to trigger a new wave of better-guided wet-lab experimentation and better-informed first-principle reasoning, which can eventually help us better decode and improve life.
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