# David Rimm
**David L. Rimm** is an American pathologist at [Yale School of Medicine](https://www.edgepedia.org/yale-school-of-medicine), where he is the Anthony N. Brady Professor of Pathology and Professor of Medicine (Medical Oncology).[1](https://medicine.yale.edu/profile/david-rimm/) He is known for quantitative pathology, the measurement of biomarkers in tissue as continuous numbers rather than visual scores: his laboratory invented the AQUA method of [quantitative immunofluorescence](https://www.edgepedia.org/quantitative-immunofluorescence), published in *Nature Medicine* in 2002, and he is the scientific founder of HistoRx, the company that commercialized it.[1](https://medicine.yale.edu/profile/david-rimm/) • [2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html) The American Association for Cancer Research credits his invention of the fluorescence-based Automated Quantitative Analysis (AQUA) platform with enabling precise and reproducible protein measurement in tissue specimens.[3](https://www.aacr.org/governance/david-l-rimm-award-recipient-aacr/)
| Key facts | |
|---|---|
| Position | Anthony N. Brady Professor of Pathology and Professor of Medicine (Medical Oncology), Yale School of Medicine[1](https://medicine.yale.edu/profile/david-rimm/) |
| Training | MD-PhD, Johns Hopkins University Medical School, 1981–1989[4](https://orcid.org/0000-0001-5820-4397) |
| Postdoctoral clinical training | Pathology residency at Yale-New Haven Hospital (1993); cytopathology fellowship, Medical College of Virginia (1994)[1](https://medicine.yale.edu/profile/david-rimm/) |
| Career span | Professor of Pathology at Yale since 1 July 1994; Brady professorship since 2021[4](https://orcid.org/0000-0001-5820-4397) • [5](https://news.yale.edu/2021/12/14/rimm-named-anthony-n-brady-professor-pathology) |
| Signature work | "Automated subcellular localization and quantification of protein expression in tissue microarrays", *Nature Medicine*, 2002[6](https://preview-www.nature.com/articles/nm791) |
| Company | Scientific founder of HistoRx, which commercialized AQUA[2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html) |
| Honor | 2026 AACR James S. Ewing-Thelma B. Dunn Award for Outstanding Achievement in Pathology in Cancer Research[7](https://medicine.yale.edu/news-article/david-rimm-md-phd-chosen-for-pathology-cancer-research-award/) |
## Education and career
Rimm completed an MD-PhD at Johns Hopkins University Medical School from 1981 to 1989.[1](https://medicine.yale.edu/profile/david-rimm/) • [4](https://orcid.org/0000-0001-5820-4397) He then took a pathology residency at Yale-New Haven Hospital, finishing in 1993, and a cytopathology fellowship at the Medical College of Virginia, finishing in 1994.[1](https://medicine.yale.edu/profile/david-rimm/) He has been a professor in Yale's Department of Pathology since 1 July 1994 and is board certified in anatomic pathology and cytopathology.[4](https://orcid.org/0000-0001-5820-4397) • [5](https://news.yale.edu/2021/12/14/rimm-named-anthony-n-brady-professor-pathology)
At Yale he directs Yale Pathology Tissue Services, the Yale Cancer Center Tissue Microarray Facility, and the Physician Scientist Training Program in [Pathology](https://www.edgepedia.org/pathology), as well as the Quantitative Diagnostics in Anatomic Pathology (QDAP) laboratory.[1](https://medicine.yale.edu/profile/david-rimm/) • [3](https://www.aacr.org/governance/david-l-rimm-award-recipient-aacr/) He has been principal investigator of the Rimm Laboratory for more than 30 years.[7](https://medicine.yale.edu/news-article/david-rimm-md-phd-chosen-for-pathology-cancer-research-award/) According to Yale News, Yale announced his appointment to the Anthony N. Brady Professorship of Pathology on December 14, 2021.[5](https://news.yale.edu/2021/12/14/rimm-named-anthony-n-brady-professor-pathology)
## Quantitative pathology and the AQUA method
His 2002 *Nature Medicine* paper presented a set of algorithms for the rapid, automated, continuous, and quantitative analysis of tissue microarrays, including the separation of tumor from stromal elements and the sub-cellular localization of signals.[6](https://preview-www.nature.com/articles/nm791) Validation using estrogen receptor in breast carcinoma showed that automated analysis matches or exceeds the results of conventional pathologist-based scoring.[6](https://preview-www.nature.com/articles/nm791) Automated analysis and subcellular localization of beta-catenin in colon cancer identified two novel, prognostically significant tumor subsets that traditional pathologist-based scoring did not detect.[6](https://preview-www.nature.com/articles/nm791)
AQUA defines its compartments from molecules, not from shape. It uses only molecular features to define architectural or subcellular compartments and excludes morphology-based features such as "roundness".[2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html) In one comparison on 640 tissue-microarray cases, the misclassification rate between AQUA estrogen-receptor measurement and pathologist scoring by eye was 16.7 percent.[2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html) A later HER2 study reported a cumulative coefficient of variation under five percent across operators, machines, and stains, comparable to or better than an ELISA.[2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html)
## X-Tile and biomarker analysis tools
X-Tile, published in *Clinical Cancer Research* in 2004, is a bio-informatics tool for biomarker assessment and outcome-based cut-point optimization.[8](https://medicine.yale.edu/lab/rimm/research/software/) The X-tile plot is a graphical method that projects every possible subpopulation division of a patient cohort, showing where a biomarker best separates patients by outcome and how robust that separation is.[8](https://medicine.yale.edu/lab/rimm/research/software/) It was validated against established prognostic markers in breast cancer cohorts, including HER2, estrogen receptor, p53 expression, patient age, tumor size, and node number.[8](https://medicine.yale.edu/lab/rimm/research/software/) The Rimm Lab maintains X-Tile and the AQUAmine database.[9](https://medicine.yale.edu/lab/rimm/research/)
## Representative work
The paper that stands for his approach is "Automated subcellular localization and quantification of protein expression in tissue microarrays", *Nature Medicine*, 2002 ([doi:10.1038/nm791](https://doi.org/10.1038/nm791)).[6](https://preview-www.nature.com/articles/nm791) It introduced AQUA, showed that automated continuous measurement could match or exceed pathologist scoring for estrogen receptor, and used subcellular localization to find prognostic beta-catenin subsets in colon cancer invisible to visual scoring.[6](https://preview-www.nature.com/articles/nm791)
## HistoRx and industry roles
Rimm is a consultant, stockholder, and scientific founder of HistoRx, which commercialized the AQUA technology.[2](http://www.captodayonline.com/Archives/1109/1109e_futurescape.html) His laboratory works on standardizing assays for CLIA laboratories, including standardized assays for antibody-drug conjugate therapies, and uses high-plex methods such as NanoString [digital spatial profiling](https://www.edgepedia.org/digital-spatial-profiling) for biomarker discovery.[1](https://medicine.yale.edu/profile/david-rimm/) He joined the College of American Pathologists Immunohistochemistry committee, and the Breast Cancer Research Foundation lists advisory service for [Genentech](https://www.edgepedia.org/genentech), Novartis, BMS, Perkin Elmer, and Dako, along with membership of correlative science committees for SWOG, ALTTO, and TEACH breast cancer trials.[1](https://medicine.yale.edu/profile/david-rimm/) • [10](https://www.bcrf.org/researchers/david-rimm/)
## Recent developments
AI-based image analysis has moved toward daily practice. In 2025, a study published in *JAMA Network Open* (8: e2518906) assessed pathologist-read versus AI-driven assessment of tumor-infiltrating lymphocytes in melanoma; reporting on it, Rimm noted that machine learning can overcome the subjectivity of traditional pathologist-based assessment and that such technologies are already beginning to appear in daily practice as evidence-based clinical decision support in oncology.[11](https://www.yalemedicine.org/specialists/david-rimm) • [12](https://www.cancernetwork.com/view/refining-artificial-intelligence-tools-in-cancer-pathology-and-research)
His laboratory has also pushed measurement to absolute units. A HER2 assay combining quantitative immunofluorescence on the CyteFinder II HT platform with a mass-spectrometry-standardized cell line array measures HER2 in attomoles per square millimeter; the team determined the HER2-low range as 2 to 20 attomol/mm2, and in initial tests 67 percent of breast cancer patients scored 0 by traditional IHC actually had measurable HER2.[13](https://www.selectscience.net/article/measuring-versus-reading-transforming-the-field-of-quantitative-pathology) With BCRF funding, the lab developed the Troplex assay, which simultaneously measures the HER2 and TROP2 protein targets of the antibody-drug conjugates T-DXd (Enhertu) and sacituzumab govitecan (Trodelvy); two clinical trials to validate it, the QuantifyHER trial and a separate Trop2-levels trial, were launched through the Translational Breast Cancer Research Consortium.[7](https://medicine.yale.edu/news-article/david-rimm-md-phd-chosen-for-pathology-cancer-research-award/) • [10](https://www.bcrf.org/researchers/david-rimm/)
## References
1. David Rimm, MD, PhD | Yale School of Medicine. https://medicine.yale.edu/profile/david-rimm/
2. http://www.captodayonline.com/Archives/1109/1109e_futurescape.html
3. David L. Rimm, MD, PhD | Award Recipient | AACR. https://www.aacr.org/governance/david-l-rimm-award-recipient-aacr/
4. David Rimm (0000-0001-5820-4397) - ORCID. https://orcid.org/0000-0001-5820-4397
5. Rimm named Anthony N. Brady Professor of Pathology. Yale News, December 14, 2021. https://news.yale.edu/2021/12/14/rimm-named-anthony-n-brady-professor-pathology
6. Automated subcellular localization and quantification of protein expression in tissue microarrays. Nat Med 8, 1323–1328 (2002). https://preview-www.nature.com/articles/nm791
7. David Rimm, MD, PhD, Chosen for Pathology Cancer Research Award. Yale School of Medicine. https://medicine.yale.edu/news-article/david-rimm-md-phd-chosen-for-pathology-cancer-research-award/
8. X-Tile Software | Rimm Lab. https://medicine.yale.edu/lab/rimm/research/software/
9. Research Interests | Rimm Lab. https://medicine.yale.edu/lab/rimm/research/
10. David Rimm | Breast Cancer Research Foundation. https://www.bcrf.org/researchers/david-rimm/
11. David Rimm | Specialists | Yale Medicine. https://www.yalemedicine.org/specialists/david-rimm
12. Refining Artificial Intelligence Tools in Cancer Pathology and Research. Cancer Network, October 2, 2025. https://www.cancernetwork.com/view/refining-artificial-intelligence-tools-in-cancer-pathology-and-research
13. Measuring versus reading - transforming the field of quantitative pathology. SelectScience. https://www.selectscience.net/article/measuring-versus-reading-transforming-the-field-of-quantitative-pathology
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*Topic: Encyclopedia › Life and health › Life and health scientists › Medical and health researchers › Researchers in molecular diagnostics, pathology, medical imaging, and precision medicine › Digital pathology and computational pathology*
*Initially written Sep 21, 2026 · Reviewed: Sep 25, 2026; Sep 30, 2026 · Edited: Sep 25, 2026; Sep 30, 2026; Oct 11, 2026; Oct 15, 2026 · Last review: Sep 30, 2026*
*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*
License: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license