ARSA: an autonomous research scientist for target nomination in Alzheimer's disease and related dementias
- 1University of Notre Dame
Abstract
Expanding therapeutic options for Alzheimer's disease and related dementias (ADRD) requires biologically grounded targets, yet nomination demands labor-intensive analysis and multidisciplinary evidence synthesis. To address this challenge, we present ARSA, an autonomous research scientist that transforms natural-language research interests and molecular data into prioritized, evidence-grounded target shortlists. ARSA formulates and audits hypotheses, adapts molecular analyses to observed results, and prioritizes targets using cross-cohort evidence and disease-specific knowledge, preserving the evidence and decisions underlying each nomination. Across three complementary evaluations, we show that ARSA generates hypotheses corresponding to subsequent research and identifies credible candidates within and beyond community nomination records. In structured assessment by 14 experts spanning all four technical cores of the Indiana University School of Medicine-Purdue University TREAT-AD Center, every expert assigned higher mean credibility to ARSA-retained candidates than to rejected comparators. ARSA enables systematic, transparent target exploration, opening opportunities to broaden the therapeutic mechanisms investigated in ADRD.
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BibTeX
@misc{li2026arsa,
title = {{ARSA: an autonomous research scientist for target nomination in Alzheimer's disease and related dementias}},
author = {X. Li and J. Liu and J. Liu and T. I. Richardson and J. L. Dage and R. C. Klein and D. Z. Chen and K. Huang and J. Zhang and T. S. Johnson and Y. Shi},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.19.752836},
url = {https://www.biorxiv.org/content/10.64898/2026.09.19.752836v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - ARSA: an autonomous research scientist for target nomination in Alzheimer's disease and related dementias
AU - X. Li
AU - J. Liu
AU - J. Liu
AU - T. I. Richardson
AU - J. L. Dage
AU - R. C. Klein
AU - D. Z. Chen
AU - K. Huang
AU - J. Zhang
AU - T. S. Johnson
AU - Y. Shi
PY - 2026
DA - 2026/09/19
PB - bioRxiv
DO - 10.64898/2026.09.19.752836
UR - https://www.biorxiv.org/content/10.64898/2026.09.19.752836v1
AB - Expanding therapeutic options for Alzheimer's disease and related dementias (ADRD) requires biologically grounded targets, yet nomination demands labor-intensive analysis and multidisciplinary evidence synthesis. To address this challenge, we present ARSA, an autonomous research scientist that transforms natural-language research interests and molecular data into prioritized, evidence-grounded target shortlists. ARSA formulates and audits hypotheses, adapts molecular analyses to observed results, and prioritizes targets using cross-cohort evidence and disease-specific knowledge, preserving the evidence and decisions underlying each nomination. Across three complementary evaluations, we show that ARSA generates hypotheses corresponding to subsequent research and identifies credible candidates within and beyond community nomination records. In structured assessment by 14 experts spanning all four technical cores of the Indiana University School of Medicine-Purdue University TREAT-AD Center, every expert assigned higher mean credibility to ARSA-retained candidates than to rejected comparators. ARSA enables systematic, transparent target exploration, opening opportunities to broaden the therapeutic mechanisms investigated in ADRD.
ER -