Future missions beyond Low Earth Orbit (LEO) will expose crew to a harsher ionizing radiation environment, particularly as they leave the protection of Earth’s geomagnetic field. The biological impact of space radiation is not well understood and introduces health risks of cancers, degenerative diseases, and other acute and late effects. Simulating the space radiation environment is therefore important for completing risk assessments for crewed missions as well as investigating the response of detectors and the shielding effectiveness of spacecraft materials. The two common simulation methods used include stochastic (Monte Carlo) or deterministic particle transport codes. Monte Carlo simulations are computationally intensive particularly for medium to large spacecraft such as the International Space Station, Tiangong Space Station or Lunar Gateway. Typical simulation run times are large (days-weeks) in order to achieve a low statistical uncertainty in results, therefore, novel techniques are required to reduce simulation time. In the medical field, variance reduction techniques are applied to radiotherapy simulations and clinical Monte Carlo codes to achieve significant time savings. We have developed a custom application utilising the Geant-4 toolkit to study ionizing radiation doses on board the ISS. The method presented was inspired from medical field codes and has been applied to space radiation transport. The technique involves applying a direction source bias to the galactic cosmic rays to remove particles that have a low probability of interacting with a detector. A sensitivity analysis is completed on the incident angle of the particle, investigating the effective dose equivalent contribution by primary and secondary particles (eg. protons, alphas, heavy ions, gammas and neutrons). The input parameter can be applied to any simulations of spacecraft in GCR’s that have similar materials and geometry to the ISS. Our code reduces simulation time by a factor of 130 while maintaining statistical accuracy.