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LUPUS RESEARCH ALLIANCE 2024-2028 RESEARCH STRATEGIC PLAN: ACCELERATING PRECISION MEDICINE FOR PEOPLE LIVING WITH LUPUS

2025· article· en· W4410513036 on OpenAlexvenueno aff
Stacie Bell, M. Kahlenberg, Gary Koretzky, Teodora Staeva

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusAllianceLupus erythematosusDermatologyPathologyImmunologyDisease

Abstract

fetched live from OpenAlex

PV140 / #234 Poster Topic: AS17 - Miscellaneous Background/Purpose Lupus is a systemic autoimmune disease characterized by complicated etiopathogenesis, heterogeneous clinical manifestations and a range of immunological abnormalities that affects millions of people worldwide. At present, therapy for lupus is mostly empiric and involves largely nonspecific anti-inflammatory and immunosuppressive agents. The Lupus Research Alliance (LRA), the world’s largest private funder of lupus research, has invested over US$270M in more than 600 individual research programs since 1999. Recently, the LRA successfully completed its previous 5-year research strategic plan, resulting in the establishment of robust research governing bodies, a tripling of the number of grant programs, and the establishment of critical translational and clinical research infrastructure to include a Public-Private Partnership with the FDA, Lupus ABC, a lupus registry, biorepository, and data exchange platform, Lupus Nexus, and has significantly increased the number of clinical studies the organization supports through the clinical affiliate, Lupus Therapeutics. To build upon this success, the LRA set out to create a new 5-year Research Strategic Plan as part of an organization-wide goal to directly impact individuals living with lupus by enabling research that advances safer and accessible treatment options. Methods More than 30 interviews with lupus patients and US and international lupus/related fields researchers were conducted, as well as a survey of the research and clinical landscape and a detailed analysis of the clinical trial landscape using clinicaltrials.gov and other sources. Additionally, an in-depth evaluation of LRA’s research portfolio and broader funding landscape analyses were performed to inform the evolution of LRA’s grant programs and ensure they continue to synergize with external research funding. A planning committee of academic and industry experts, and patients advised the development of the strategy by analyzing the data and engaging in discussions about emerging gaps and opportunities. Results With recent developments in understanding lupus pathogenesis and heterogeneity, impactful technological advancements, and the emergence of engineered cell therapy as a novel treatment paradigm for lupus, the LRA is uniquely positioned to address critical gaps and opportunities to accelerate precision medicine for people living with lupus. The clinical trial landscape analysis highlighted that while the number of lupus clinical trials has increased, there is a high failure rate for primary outcomes, demonstrating the need for better trial design and population characterization, as well as mechanistic understanding of therapies entering trials and for diagnostics/prognostics to stratify patients and quantify outcomes. Importantly, the analysis showed that the LRA clinical affiliate, Lupus Therapeutics, participated in ~25-30% of all lupus trials. The new strategic plan was built on its unique capabilities and the LRA’s robust infrastructure and research programs and includes three 5-year research goals, each with corresponding objectives and intended patient impact: 1) Improve understanding of patient heterogeneity as a basis for individual therapeutic choices; 2) Increase the number of molecular stratification, prognostic/diagnostic tools, and biomarkers; 3) Accelerate development of treatments that reprogram the immune system. The new Plan calls for the LRA to become an effective driver of clinical development, for substantive changes to LRA’s funding portfolio to focus on the new priorities, and the establishment of new partnerships and patient-centric research initiatives. Conclusions By implementing this plan, the LRA envisions a future where patients are promptly diagnosed, clinically and molecularly profiled, and offered safer and more effective personalized treatments and possible cures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.121
Threshold uncertainty score0.406

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0100.007
Open science0.0040.010
Research integrity0.0090.011
Insufficient payload (model declined to judge)0.1210.087

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.137
GPT teacher head0.418
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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