The Association for Diagnostics and Laboratory Medicine To Recognize ARUP Achievements at ADLM 2025

The Association for Diagnostics and Laboratory Medicine (ADLM) and the Academy of Diagnostics and Laboratory Medicine (ADLM Academy) have recognized ARUP Laboratories’ medical directors and scientists for their achievements in the advancement of laboratory medicine.

ARUP’s validation of a plasma-based immunoassay for phosphorylated tau 217 (pTau 217) has been recognized as a 2025 Academy Distinguished Abstracts winner. ADLM also awarded Nicholas Spies, MD, with the Outstanding Scientific Achievements by a Young Investigator Merit Award.

The winners will be honored at the association’s annual meeting, ADLM 2025, which will be held July 27–31 in Chicago. ADLM 2025 provides a forum for laboratory medicine professionals to collaborate with their peers and share the latest research.

The winning abstract, Performance Validation of a Plasma-Based Immunoassay for pTau 217, was submitted by J. Alan Erickson, PhD; Sonia La’ulu, MBA, C(ASCP); Sierra Cunningham, BS; Kelly Doyle, PhD, DABCC, FACC; and Heather Nelson, PhD, DABCC. Of the 821 abstracts that were submitted, only 19 received this recognition.  

Erickson, an ARUP Research and Development scientist with 28 years of experience, and his colleagues spent months working on the study, which evaluated the performance of a chemiluminescent sandwich enzyme-linked immunosorbent assay (ELISA) for the measurement of pTau 217 in human plasma.

“Clinical studies have demonstrated that pTau 217 is the leading plasma biomarker for Alzheimer’s disease (AD) pathology,” said Nelson, ARUP medical director of Clinical Chemistry and Mass Spectrometry. “The advent of disease-modifying therapies has accelerated the need for early diagnosis.”

By detecting pTau 217 in blood, this assay is less invasive than detecting biomarkers in cerebrospinal fluid (CSF), which requires a spinal tap. It is also less expensive than an amyloid positron emission tomography (amyloid-PET) scan.

The study found that “the assay’s performance correlated strongly with results from amyloid-PET and demonstrated 90% sensitivity and specificity,” Erickson said.

The test, which ARUP launched in April 2025, provides a more accessible means for patients with cognitive decline to be assessed for AD and begin treatment earlier.

ADLM attendees will be able to view the abstract poster on Wednesday, July 30. Erickson will be available for questions and discussion from 1:30 to 2:30 p.m.

Outstanding Scientific Achievements by a Young Investigator Merit Award

Spies, medical director of Applied Artificial Intelligence and Clinical Chemistry, recipient of the Outstanding Scientific Achievements by a Young Investigator Merit Award, has been a key contributor to ARUP Laboratories’ Institute for Research and Innovation in Diagnostic and Precision Medicine™.

Spies is using machine learning to minimize laboratory errors and improve the quality of testing, such as by identifying contamination from intravenous fluids in collected specimens, which can skew the results of a laboratory test. While recognizing contamination is a difficult task for a human, machine learning can easily identify patterns that would indicate contamination.

Spies is also currently investigating how to build multimodal approaches for hematopathology that would combine data from different methods, such as flow cytometry and next generation sequencing, to generate new insights about blood-related disorders and malignancies.

“My main research goal is to apply the tools that we have for analytics and data science to make better use of the data we generate from routine clinical care,” Spies said. “We can then integrate these data sources to make better decisions.”

Before becoming a pathologist, Spies completed an obstetrics and gynecology internship at Washington University School of Medicine. There, he began to recognize the role of data in clinical decisions. He then started a company that investigated how artificial intelligence could be used to better inform medical decisions, before turning to pathology.

Spies appreciates that his current role enables him to “build machine-learning tools to improve how we deliver healthcare, which creates a synergy between my research interests and my clinical role,” he said.

Spies said he was “honored and humbled” to receive the award.

“It came as quite a shock, especially seeing some of the names that have received this award in the past,” Spies said. “It’s definitely not in any small part due to the great mentorship and collaborations that I’ve been lucky to experience.”

Kellie Carrigan, kellie.carrigan@aruplab.com