ALife is fundamentally concerned with the research on the kind of control systems that govern how organic life responds to stimuli, how those systems plan in order to maintain long-term homeostasis, how they select goals, how they allocate attention, etc.

One might say that ALife is to an event loop as AI is to a one-time query-response. AI can evaluate, but you need an ALife system in order to "think" in a continuous way.

There's really no sense in which an ALife researcher cares about recreating a full-fidelity model of biology in silico; the point is to specifically study the thinking and decision process of real agents, and figure out how to model those, in a way that the model makes the same series of decisions the real agent does in the same situations (and, therefore, must also be keeping and updating analogous internal state to the kind the real agent keeps.)

Some of those models are attempts to recreate real brains/nervous systems, but these models aren't fundamentally biological. A "low level" connectome simulation doesn't contain any model of cellular inflammatory response, cellular waste and its clearance, etc. It's basically just a brain-as-actor-model with neurons as stateful processes and electrochemical signals as messages.

An ALife researcher cares about as much about biology below the level of intracellular pharmacodynamics (sodium channels et al), as a race-car-chassis engineer cares about physics below the level of fluid dynamics. They don't need to go any lower, because they've found an encapsulating abstraction that makes all the predictions they're interested in making, without needing any lower-level information.