Xenobots (Living Robots) and Synthetic Morphology

Abstract

The fields of developmental biology and robotics are converging on a profound question: can we design and build completely novel, living machines from biological parts? The creation of "Xenobots"—multicellular, autonomous agents assembled from frog stem cells—has opened the door to synthetic morphology. This Masters in Computer Science proposal outlines a fundamental research agenda to explore the principles that govern how cells cooperate to build complex structures. Instead of focusing on a specific application, this research aims to develop a computational framework for predicting and directing multicellular self-assembly, using Xenobots as a model system. The long-term vision is to establish a "biological compiler" that can translate a desired form or function into a set of initial cellular conditions.

Key Research Questions in Synthetic Morphology

1. The Morphogenetic Code: What are the rules that govern how collections of cells decide what to build? How do they begin, direct, and terminate construction? This involves investigating the interplay between genetic programs and the bioelectric and biomechanical signals that cells use to communicate.
2. Predictive Modeling of Self-Assembly: Can we create a high-fidelity, in-silico simulation that accurately predicts the 3D structure and collective behavior that will emerge from a given arrangement of different cell types (e.g., skin cells and heart muscle cells)?
3. AI-Driven Design: Can a machine learning model, particularly an evolutionary algorithm or a generative model, be used to *discover* novel Xenobot designs that exhibit desired behaviors (e.g., efficient locomotion, targeted cargo delivery, or self-repair) that a human designer would not have conceived?
4. Controlling Collective Behavior: How can we externally guide the behavior of these living robots? This could involve using light (optogenetics) or chemical gradients to direct their movement or to switch their collective behaviors on and off.

Proposed Masters in Computer Science Research: An AI-Driven Platform for Xenobot Design

This thesis will focus on building a closed-loop "design-build-test" platform for creating functional Xenobots.

• Develop a Physics-Based Simulator: Create a simulation environment that models the key physical properties of frog cells, including their adhesion, stiffness, and the contractile force of heart muscle cells. This simulator will be the "sandbox" for testing designs.
• Implement an Evolutionary Design Algorithm: An AI will be developed to automatically design Xenobots. The AI will start with random configurations of cells, test their behavior in the simulator, and "evolve" the most successful designs over many generations to optimize for a specific task (e.g., moving a tiny particle to a target location).
• Experimental Validation: In collaboration with a developmental biology lab, the most promising designs generated by the AI will be physically constructed from real frog stem cells. Their actual behavior will be recorded and compared against the simulation's predictions.
• Model Refinement: The experimental data will be used to refine and improve the accuracy of the physics-based simulator, creating a tighter feedback loop between the AI designer and the real-world biological system.

Impact for Ghana and Africa

While fundamental in nature, this research has profound long-term implications. Understanding the principles of biological construction could lead to revolutionary advances in regenerative medicine, such as instructing cells to repair damaged organs or regrow limbs. In an African context, this could one day lead to treatments for conditions like severe burns or diabetic ulcers. More broadly, mastering biological construction could enable the creation of "living machines" for environmental cleanup (e.g., collecting microplastics from waterways like the Volta River) or targeted drug delivery in the body. By engaging in this frontier research, Ghana can become a hub for a completely new field of technology, one that blurs the line between the living and the artificial, and which may hold the key to solving some of humanity's most complex challenges.