Integrating multiple data types facilitates a more holistic approach to risk assessment. By combining experimental data with computational models, toxicologists can identify potential hazards more accurately. This approach also helps in distinguishing between true toxic effects and false positives, thus reducing uncertainty in risk assessment. Furthermore, integrated data can aid in developing alternative testing strategies that minimize reliance on animal testing, aligning with ethical considerations and regulatory guidelines.