Background: Modern rheumatology research increasingly involves large, complex datasets and requires methods beyond traditional univariate analyses. Objective: To highlight how transdisciplinary collaboration — integrating statisticians and data scientists from the outset — enhances rheumatology research and improves patient care. Methods: The presentation discussed differences between multi‑, inter‑ and transdisciplinary collaboration and emphasised how dedicated statistical and data science expertise enables study designs, analyses and interpretation that align with complex clinical questions. Interactive simulation models were suggested as effective educational tools for clinicians to grasp statistical concepts. Results: Involving statisticians and data scientists early ensures robust study designs, appropriate analytical methods and accurate interpretation of results. Interactive simulations and joint training foster shared understanding among clinicians and analysts, empowering clinicians to plan and interpret data‑driven research. Conclusion: Transdisciplinary collaboration, with statisticians and data scientists as core team members, is essential for rigorous, reproducible rheumatology research and ultimately leads to better patient outcomes【882719239464591†L130-L176】.