The Personalized Pulse

“If we can learn which signal produces which outcome, medicine starts to look less like trial and error and more like engineering.”

— Ken Mayer, Co-founder & Chief Executive Officer

Among the most provocative ideas in modern biology is that bioelectric signals help guide how tissue develops and repairs itself. The biologist Michael Levin has described bioelectric circuits as something like a software layer sitting above the genome — a set of instructions that shapes how cells interpret and execute their genetic code. The genome supplies the parts list; the bioelectric layer helps decide what gets built and where.

As an engineer, that abstraction is the part that grabs me. A software layer implies something programmable. And programmable systems can be read, modeled, and — carefully — reconfigured.

Evidence that the layer is real

This is not pure theory. Laboratory experiments have redirected growth in frog and flatworm models through targeted electrical stimulation — changing developmental outcomes without editing a single gene. The point is not the spectacle of the result but its implication: if you can alter where structure forms by altering an electrical pattern, then electrical patterns carry real instructive information.

A visualization of DNA sequencing data. That insight is being translated toward therapy. Morphoceuticals, for example, is pursuing the use of programmable bioelectric signals delivered with precise dosing protocols. The shared premise across this work is that the right signal, applied at the right place and time, can guide cellular behavior — and that the “right signal” is something we can discover systematically.

“Personalization is the whole promise. The future of care is a therapy that adapts to the patient, not the other way around.”

— Ken Mayer, Co-founder & Chief Executive Officer

Mapping the electrome

Discovering it systematically is exactly an AI problem. The work I care most about involves AI-driven frequency simulators aimed at mapping the human electrome and matching stimulation prescriptions to specific conditions. Picture the eventual workflow: an AI scan characterizes a patient's electrical state, the system proposes a custom signal package, and a wearable device delivers it — then measures the response and updates the plan.

We are early, and I will not dress that up. But the trajectory is clear: decode which signals trigger which cellular outcomes, build digital twins that let us simulate an intervention before we ever apply it, and move toward care that genuinely adapts to the individual. That is the vision of personalized, signal-based medicine that Electrome is building toward.

A wearable health monitor worn on the wrist.