What I mean by this is that the whole nature of chemistry and biology is already rooted on a very secure foundation. So as simulation capabilities increase, you can be sure that these have a very high probability of modeling the "higher-order" phenomena correctly. Even superconductors and superfluids can be modeled correctly. The only things that may not be correct would be the high energy limit of quantum gravity models. But simulation in this area is almost (and may be?) nonexistent.
Now... having stated that we have an almost perfect description of the underlying reality for any practical phenomena we would be interested in, it is true that this model is currently mostly unamenable to calculation. The amount of computation required to reach chemical accuracy is very high and we may not have that capability for quite a while. So we make concessions and approximate things. For example, wavefunctions are modeled as Slater determinants which satisfy the wavefunction's antisymmetry but do not take into effect all the correlative effects (like electron-electron interactions).
It is a scientific and mathematical challenge to characterize exactly how much these models are off from the "true" solution. Most of the time, you have a good idea if the approximation you are using will work for your domain. If I want to fold proteins, I don't need anything more accurate than CHARMM (describes pairwise interactions; it's a non-reactive potential). But if I want to study Cooper Pairs (in superconductors) I'm going to need to make many less approximations, and it will be a much more expensive model computationally.
Want to simulate a cell? Even with hardware 10^100 times faster you can't use QM, it's all models of models. None of which are 100% accurate, but that's no reason you can't Kidd yourself.
Even at the timescales of atomic explosions and the best hardware / software around those models are vary simplified.
PS: That's not to say you can't make useful simulations, but trusting them to be accurate without testing is not science.
What if the current model is wrong?
An experiment in the real/natural world is the only way to find out if a model (or its simulation) is wrong. You have to ask nature.