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Reply to: Pre-clinical data interpretation requires clinical context

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Why This Matters

This article highlights the critical importance of interpreting pre-clinical data within a clinical context to ensure accurate translation into patient care. It underscores the potential risks of misinterpreting early research findings, which can impact the development of effective cancer therapies. For the tech industry, especially those involved in biomedical data analysis and AI, understanding this nuance is vital for developing tools that support reliable clinical decision-making.

Key Takeaways

Authors and Affiliations

Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA Sean P. Pitroda & Ralph R. Weichselbaum Ludwig Center for Cancer Research, The University of Chicago, Chicago, IL, USA Sean P. Pitroda & Ralph R. Weichselbaum

Contributions

S.P.P. and R.R.W. contributed equally to the conceptualization and writing of the initial paper draft. Both authors reviewed, revised and approved the final version of the paper. S.P.P. and R.R.W. jointly wrote and revised the Matters Arising rebuttal. Although the original paper included additional co-authors, the Matters Arising correspondence specifically concerns the broader clinical implications of our findings rather than the mechanistic aspects that occupied the contributions of the other authors. As S.P.P. and R.R.W. are best positioned to address questions pertaining to clinical translation and interpretation, the author list for this reply is necessarily reduced relative to that of the original article.

Corresponding author

Correspondence to Ralph R. Weichselbaum.