Sharad Ramanathan, Ph.D.
Sharad Ramanathan leads a research program focused on discovering the rules that govern development and behavior by learning how to control the underlying biology. His lab combines synthetic embryology, quantitative biology, and bioengineering to reconstruct human developmental programs in vitro, with the goal of identifying which signaling, regulatory, and physical mechanisms are sufficient to drive patterning and morphogenesis in both healthy and disease states. Across these systems, his research emphasizes construction and control as stringent tests of biological understanding.
Sharad Ramanathan, Ph.D.
- Llura and Gordon Gund Professor of Neurosciences and of Molecular and Cellular Biology
Harvard University - Professor of Applied Physics and of Stem Cell and Regenerative Biology
Harvard University - Co-Director
Quantitative Biology Initiative
Sharad Ramanathan’s research is directed towards answering two questions. How do cells and organisms process signals from their environment to make decisions? How do the underlying circuits make this possible? His lab currently addresses these questions in the context of human development to understand how pluripotent stem cells undergo morphogenesis to give rise to the complex tissues in the human embryo. The lab develops and uses a combination of techniques from stem cell and molecular biology, genomics, bioengineering and computational biology.
Ramanathan received his Ph.D. in Chemical Physics from Harvard University and his undergraduate degree from the Indian Institute of Technology, Kanpur. He was a member of technical staff in the Theoretical Physics Department at Bell Laboratories before moving back to Harvard. He is currently also a member of the Department of Molecular and Cellular Biology, and of the Applied Physics Division in the John A Paulson School of Engineering.
Lab Overview
Research Mission
We build synthetic biological systems to uncover the rules that drive human development and neural control of behavior. Our work sits at the interface of synthetic embryology, quantitative biology, and bioengineering: we aim to identify which combinations of signals, regulatory interactions, and physical constraints are sufficient to generate robust patterning and morphogenesis from pluripotent stem cells.
Decades of work in model organisms have revealed many genes and pathways required for embryonic development, but necessity does not reveal sufficiency. We therefore reconstruct developmental processes in controlled in vitro systems—where geometry, timing, and signal dynamics can be specified precisely—so we can test causal hypotheses about fate decisions, pattern formation, and tissue-scale organization.
Approach and Platforms
We combine human stem cell biology, bioengineering, quantitative imaging, genomics/single-cell profiling, and computation (including machine-learning–guided experimental design) to make development programmable: we build tissues, perturb them, and measure how patterns and morphogenetic programs emerge.
Ethical Oversight and Impact
Our work with human stem cells is carried out under rigorous ethical oversight and in full compliance with federal, ISSCR, and Harvard guidelines. We aim to responsibly use human-specific cells and tissues we generate to advance biological understanding and improve human health.
Current Focus Areas
• Synthetic human development: patterning and morphogenesis in human stem-cell–based developmental systems (including in vitro models of trunk and brain development), with high throughput controlled morphogen delivery and dynamic high-content readouts.
• Signaling dynamics, mechanics and gene regulatory networks: inferring and testing causal models that govern fate transitions, morphogenesis, and disease.
• Cell, tissue generation and transplantation: to explore the potential for alleviating disease.
• Neural decision-making and control: identifying circuit-level mechanisms that govern behavioral states, and demonstrating understanding through targeted manipulation.
Across these domains, our operating principle is consistent: understanding is demonstrated by construction and control.
