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Abstract Computer simulation is an indispensable tool for studying complex biological systems. In particular, agent-based modeling is an attractive method to describe biophysical dynamics. However, two barriers limit faster progress. First, simulators do not always take full advantage of parallel and heterogeneous hardware. Second, many agent-based simulators are written with a specific research problem in mind and lack a flexible software design. Consequently, researchers have to spend an unnecessarily long time implementing their simulation and have to compromise either on model resolution or system size. We present a novel simulation platform called BioDynaMo that alleviates both of these problems researchers face in computer simulation of complex biological systems. BioDynaMo features a general-purpose and high-performance simulation engine. The engine simulates cellular elements, their interactions within a 3D physical environment, and their cell-internal genetic dynamics. Cell-internal dynamics can be described in C++ code or using system biology markup language (SBML). We demonstrate BioDynaMo’s wide range of application with three example use cases: soma clustering, neural development, and tumor spheroid growth. We validate our results with experimental data, and evaluate the performance of the simulation engine. We compare BioDynaMo’s performance with a state-of-the-art baseline, and analyze its scalability. We observe a speedup of 20–124× over the state-of-the-art baseline using one CPU core and a parallel speedup between 67× and 76× using 72 physical CPU cores with hyperthreading enabled. Combining these two results, we conclude that, on our test system, BioDynaMo is at least three orders of magnitude faster than the state-of-the-art serial baseline. These improvements make it feasible to simulate neural development with 1.24 billion agents on a single server with 1TB memory, and 12 million agents on a laptop with 16GB memory. BioDynaMo is an open-source project under the Apache 2.0 license and is available at www.biodynamo.org. Author summary Computer simulations of biological systems are crucial to gain insights into complex processes of living organisms. However, the development of increasingly large and complex simulations is a difficult task, partly because a strong background in biology as well as computer science is required. In this paper, we introduce BioDynaMo, an agent-based simulation platform with which life scientists can create simulations that are three orders of magnitude faster than the state-of-the-art baseline. By taking advantage of the latest developments in computing hardware, we build a platform that is highly optimized. This enables the simulation of 1.24 billion agents on a single server and 12 million agents on a laptop. BioDynaMo places a lot of focus on hiding computational complexity and providing an easy-to-use interface, such that the life scientist can concentrate on biological aspects, rather than computational. BioDynaMo helps scientists to translate an idea quickly into a simulation by providing common building blocks, and a modular and extensible software design. We analyze the performance of the platform and demonstrate the capabilities with three example use cases: soma clustering, neural development, and tumor spheroid growth. The results support the view that BioDynaMo will help open up new research opportunities for large-scale biological simulations.