Toward AI-Driven Digital Organism

This perspective proposes an 'AI-Driven Digital Organism' (AIDO) as a revolutionary framework for the biological and medical sciences. By moving away from task-specific models towards integrated, multiscale foundation models, the authors propose a blueprint for simulating biological complexity from molecules to entire organisms. The strategy is structured into three phases: 'divide and conquer' to build specialized model modules, 'connect the dots' to bridge modalities through novel architectures, and 'piece it all together' for holistic optimization and alignment. The document outlines technical requirements including the development of new biological tokenizers (e.g., hybrid DNA/RNA tokenization and VQ-VAEs for structure), novel architectures for handling high-dimensional and long-sequence data, and scalable computing infrastructure. Through examples like GluFormer for glucose monitoring and genomic foundation models, the authors demonstrate how this integrative approach can link genetic and phenotypic data, offering unprecedented predictive power for personalized medicine and biological engineering. Ultimately, the AIDO vision aims to create a virtual, affordable, and programmable environment for conducting biological experiments in silico. By fostering an open-source ecosystem, prioritizing explainability and safety, and leveraging large-scale cohorts, the authors envision a new paradigm where computational tools drive a breakthrough wave of understanding and manipulating life, mirroring the impact of foundation models in other domains.

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.

The paper concludes by emphasizing the transformative potential of an AIDO in biology, transitioning the field from a primarily empirical/experimental science to one rooted in computational rationalism. It discusses the necessity of explainability, trust, and safety, advocating for the open-sourcing of models, standardized data practices, and strong regulation of wet-lab synthesis to prevent misuse. The future outlook involves continuous, holistic development of multiscale foundation models that mirror life on a computer, facilitating an accelerated connectionist revolution in biological discovery.