About Pump Science

What is the Vision

The vision of pump.science is to create a protocol for financing, researching, and developing chemicals that increase healthspan, the time a person (or any organism) can live with high physical and cognitive function.

 

The Healthspan Protocol

Among the many known and unknown factors in biology and our environment, there exists an optimal approach to maximize our healthspan. Advocates like Peter Attia, Andrew Huberman, and Bryan Johnson are prominent explorers and educators in this field, emphasizing longevity and biohacking—a movement akin to a modern-day religion of radical self-optimization. As new information emerges, it becomes possible to integrate these insights into actionable protocols, creating a lifestyle designed for health and resilience.

A parallel (discussed here) can be drawn to ancient religious practices that incorporate fasting—a form of nutrient deprivation—into their traditions. Modern science has revealed how fasting aligns with biological mechanisms that promote health, giving deeper, evidence-based meaning to these age-old practices. Similarly, longevity science today seeks to establish new protocols that enhance health by harnessing our understanding of human biology. Some of these protocols are well-understood, while many remain undiscovered.

At pump.science, we envision a framework—a 'game'—for uncovering unknown health-extending protocols, particularly chemical interventions. This game is designed to empower participants to explore and discover pharmacological methods to optimize and extend our healthspan.

From another perspective, the ideal protocol wouldn't just be about extending healthspan but about providing the ultimate training ground for AI to optimize our health on our behalf. Imagine an AI health coach, equipped with the vast expanse of chemical space and the power to tailor interventions that dynamically sustain our health. To create such an agent, we would need to train it with carefully curated data—protocols, trials, and outcomes that reveal how each molecule interacts within our bodies to maintain or restore balance.

We envision a world where each intervention tested and protocol optimized feeds into this open data ecosystem, refining an AI agent’s ability to personalize healthspan strategies for each individual. Our goal is not only to play the ‘game’ of discovery but to build a data-rich landscape that makes this AI health coach a reality. Each step taken toward uncovering new compounds or refining protocols strengthens the foundation for AI to guide us toward a life lived to its healthiest potential.

 

The Game

Our goal is to create a "game" designed to identify chemicals that extend human lifespan in the most time-efficient and cost-effective way possible. The optimal design of this "longevity game" will evolve over time as we incorporate community feedback. At the heart of our approach lies the "longevity trilemma"—balancing cost, speed, and data quality to predict a drug’s potential impact on human lifespan.

To generate meaningful, high-quality data both quickly and affordably, we start by testing on model organisms with short lifespans and low experimental costs. Each level in the game progressively "de-risks" the chemical, building evidence in simpler organisms before moving on to more complex and costly ones.

Initial Game Levels


  1. Worms (Level 1): We start with C. elegans, a small nematode about the size of an eyelash. With a lifespan of only 20-30 days in the lab, worms allow us to quickly observe the effects of potential lifespan-extending chemicals. A high-quality drug screen on worms costs around $300-500.


  2. Flies (Level 2): Next, we test on fruit flies, which live about 3 months in the lab. Flies are relatively inexpensive to culture (~$2-3k per experiment) and offer more complex biological insights than worms. While their lack of a spinal cord limits their direct applicability to human biology, their low cost and rapid life cycle make them an ideal next step.


  3. Mice (Level 3): Promising chemicals then move to testing on mice. Mice live around 2-3 years, and experiments cost $30-60k, depending on the setup. Due to the longer lifespan and higher costs, only the most promising candidates advance to this level, where we can gather more costly and time-consuming, but more human-relevant data.

These levels are subject to change based on scientific understanding, commercially available experiments and costs, and user feedback.