Center for Engineering Biology
Formalise the state of a living system, build computational models, obtain quantitative predictions, test them experimentally and use the experimental error to update the model.
Engineering biology
Biology answers why a system ended up in state X. The engineering question is different. Which intervention moves the system from state X to a required X*, and what happens after it.
We do not create a new science and do not claim superiority of the approach. The project shows that an engineering layer is needed in addition to descriptive biology. A model must produce a quantitative prediction before the experiment, and the disagreement between computation and measurement measures the model's quality. A negative result is kept and refines the model.
Research
Active research is separated from what is only assumed. Work is underway in one direction.
The first task and the first demonstrator of the method. A full cycle from transcriptomic data to a pilot in C. elegans, with the prediction tested by experiment.
Pilot. Replication needed
Latest result
A computational analysis performed without knowledge of the experimental results independently identified the same molecules that were found in the lab. The predicted lifespan extension agrees with what was observed under the studied conditions, and a single dose produced an effect comparable to a repeated one.
Method
Seven steps that repeat until the disagreement between computation and measurement is acceptable for a given task.
Progress is measured by reducing the error between prediction and measurement, not by the number of publications or the persuasiveness of an explanation.
Organisation goals
Engineering biology builds on established fields and does not set itself against them.
People
Co-founder. Engineering models and computation
MSc from MIPT in applied data analysis in medicine. Background in VHDL, reverse engineering, distributed systems and applied machine learning. Responsible for engineering models, mathematical modelling and the computational pipeline.
Head of the systems biology of ageing direction
Omics data, biomarkers and the search for geroprotectors. Responsible for the biological interpretation of models and for linking computational results to data, including measurement limits and experiment validity.
Head of the experimental programme
PhD, senior researcher at Case Western Reserve University, Division of Hematology and Oncology, Cleveland. In preclinical drug development since 1990, from target identification to a therapeutic candidate. He develops assays for anti-ageing and anti-tumour compounds and translates the project's hypotheses into cell experiments.
Top expert at the AI Competence Centre of ANO Digital Platforms.
Deployment of AI agents at big tech companies.
Bioinformatician, organiser of the “Mathematics of Aging” community (computage.org, Telegram).
About
The project develops an engineering approach to living systems and publishes experiment records as they are completed.
Engineering biology here does not replace synthetic or computational biology; it adds a requirement for the full cycle. Project texts are published on Habr.