Computer scientists at the John A. Paulson School of Engineering and Applied Sciences (SEAS) just announced a thrilling breakthrough. To address these challenges, they created a new computational framework that reveals the genetic rules governing how cells self-organize during growth. This pioneering work, released in Nature Computational Science, seeks to discover the collective functions that emerge from cellular interactions. It helps move the needle in the field of computational bioengineering.
The framework uses a new approach called differentiable programming to uncover underlying principles that govern how cells behave. Authors Ramya Deshpande, Francesco Mottes, and others, co-led the study. Their work represents a huge step forward in our understanding of morphogenesis, the biological process that determines an organism’s form and structure as it develops. Michael Brenner, the study’s senior author, is the Catalyst Professor of Applied Mathematics and Applied Physics at SEAS. He was very clear that this research is foundational for helping to guide the self-organization of these cells.
Understanding the Framework
The new computational framework opens up new opportunities for researchers to model, visualize and analyze the dynamic interactions between individual cells. Using differentiable programming, the team can use the same algorithms to solve different biological problems outside of classic neural networks. This capacity for diverse use and application is extremely important. For example, it enables scientists to better understand and control cell culture, customize proteins for pharmaceutical drugs and vaccines, and develop self-forming colloidal structures.
His interpretation of automatic differentiation’s power through this framework, as articulated by Francesco Mottes. He thinks that it unlocks thrilling opportunities to gain predictive control over cellular behavior. This new ability provides the opportunity to inspire innovative approaches for modulating cellular behaviors and arrangements. This innovation may eventually play an important role in the field of tissue engineering and regenerative medicine.
Applications Beyond Cell Growth
The broader impacts of this research touch upon much more than just knowing how cells are organized. The algorithms produced with this framework can be used to design self-assembling colloidal materials, which would represent a paradigm shift in material science. Furthermore, the framework is quite powerful for augmenting fluid dynamics simulations to gain physical and other insights into a variety of physical phenomena.
This work allows for better calibrated simulations and designs to be performed. In doing so, it helps lead the charge for innovations across disciplines from biotechnology to materials engineering. The ability to optimize these systems is critical for developing new technologies that rely on precise control of cellular and material behaviors.
Aiming for the Holy Grail of Bioengineering
The ultimate goal of this research is ambitious: to engineer the growth of organs, often referred to as the “holy grail of computational bioengineering.” Completing such an accomplishment would be a triumph for medical science, providing opportunities to leverage organ transplantation, regenerative therapies, and more. This framework offers important guidance. Understanding the fundamental biological processes driving this phenomenon will accelerate the development of functional tissues that can replace damaged or diseased organs.
As the research continues to grow and adapt, the SEAS team is determined to use their discoveries to inform and solve practical, down-to-earth challenges. This work contributes to the scientific knowledge base. Furthermore, it has the power to positively set standards for quality of care and health outcomes among patients.