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Bayer, United States
Title:Dynamical Modeling as a Precision Tools for Longevity Science
Longevity Science distinguishes itself from general medical research in its depth of ambition, and its scope and scale – as well as its its awareness of the paramount importance of integrative approaches.
Exactly in that spirit, the project Life123.science, about Dynamical Modeling for Systems Biology, takes an extremely integrative approach, with long-range goals and substantial ambition, towards filling what may be a gap in Computational Biology that the current focus on Big Data and AI doesn’t address.
This project made its debut for a general computational-biology audience at the “Bio-IT World” 2025 conference, as summarized in: https://www.youtube.com/watch?v=TBdN8s1-_OI
We now propose to present this effort into a relatively-neglected research area to the Longevity Science community.
This project aims to tackle whole-cell simulations, including membranes, in 1D, 2D and 3D. It’s a Platform for Quantitative Interactomics.
It's intentionally very ambitious, because it intends to be in a ready state for future advances in power computing, and future interactomics data.
Its scope and approach might be too broad, foundational, and open-ended, for typical companies – but may be ideally suited for the long attention span of open-source projects. By contrast, “proprietary” platforms are at the mercy of particular companies... always risking abandonment or neglect if the company shifts it focus.
For something ambitious, extremely integrative and with a long attention span, as needed by Longevity Science, the extended life of open-source has the potential of being a better vehicle, until a later stage of partnering up with industry for application to translational medicine.
Julian West’s academic (Master’s program at UC Berkeley) and professional background includes Math, Computer Science, and Molecular Biology. He alternates working in Big Pharma, currently at Bayer, and in nimble smaller companies that address Personalized (P4) Medicine and Healthspan/Longevity.
His interests and research areas include dynamical modeling for systems biology, chaotic systems, knowledge representation, graph databases, self-evolving network topology in machine learning, genetic algorithms, neurocomputing, and longevity science.
He leads two open-source projects, BrainAnnex.org and Life123.science