A class of asynchronous cellular automata (ACA) whose evolution simulates physicochemical kinetics of nano-systems is defined. It is characterized by multicell probabilistic transition rules and stochastic character of their application. To simulate real processes in real time ACAs should have huge cellular arrays and a very long evolution. So, the problem of parallel implementation of ACA algorithms is actual. But as distinct from a synchronous case, it has not any good and simple solution. To overcome this difficulty, a method of ACA approximation by a blocksynchronous cellular automata (BCA) is proposed, analyzed and experimentally studied.