AI and Biomarkers: The Quest to Objectively Diagnose Concussion

RICHMOND, VA – July 22, 2026 – For decades, the diagnosis of a mild traumatic brain injury (mTBI), or concussion, has remained stubbornly lodged in a gray area of subjective assessment. It’s an “invisible injury” where symptoms are inconsistent and standard hospital imaging often reveals nothing, leaving patients and physicians navigating a frustrating path of guesswork. This long-standing challenge may be on the verge of a breakthrough, as a Virginia-based company prepares to showcase an approach that combines blood biomarkers, cognitive testing, and artificial intelligence to bring objective clarity to concussion care.

BRAINBox Solutions announced that two key members of its Scientific Advisory Board, Dr. Alan Wu and Dr. Frank Peacock IV, will be featured on a panel at the prestigious Association for Diagnostics and Laboratory Medicine (ADLM) Annual Scientific Meeting later this month. While a panel discussion might seem routine, its focus on new guidance for TBI biomarkers signals a pivotal moment for the field. It represents a significant step in moving the diagnosis of what the company terms Acute Traumatic Encephalopathy (ATE) from an art into a data-driven science.

The Diagnostic Dilemma of Mild TBI

Every year, millions of people sustain mTBIs from falls, car accidents, or sports injuries. While most recover, a significant minority—estimated between 5% and 40%—develop persistent post-concussion symptoms (PCS) that can last for months or years, including chronic headaches, cognitive fog, and debilitating mood changes. The core problem is the difficulty in predicting who will suffer these long-term effects.

Current diagnostic practice relies heavily on clinical judgment, patient-reported symptom checklists, and neurological exams. These methods are inherently subjective. An athlete may underreport symptoms to get back in the game, while another patient may struggle to articulate their cognitive difficulties. Furthermore, conventional imaging like CT and MRI scans, while critical for identifying life-threatening brain bleeds, typically appear normal in concussion cases, offering no insight into the subtle but damaging neuronal injury.

“The ‘mild’ in mild traumatic brain injury is a dangerous misnomer,” explained one neurologist not affiliated with the company. “It minimizes the potential for severe, life-altering consequences. Without an objective measure of injury severity at the outset, we are limited in our ability to provide personalized treatment plans or give patients a clear prognosis.” This diagnostic gap creates immense uncertainty and can delay appropriate interventions, potentially worsening long-term outcomes.

A Multi-Modal Approach Powered by AI

BRAINBox Solutions is tackling this problem by developing the first AI-enabled, multi-modality diagnostic platform. Instead of relying on a single data point, their test integrates two distinct but complementary sources of information: a panel of proprietary blood biomarkers and a series of neurocognitive tests.

The blood test searches for specific proteins that are released into the bloodstream following a head injury, providing a direct biological signature of trauma. This is combined with data from functional cognitive assessments. The true innovation, however, lies in how this disparate information is synthesized. The company uses an artificial intelligence engine to analyze the complex patterns across both the biological and functional data, generating a single, objective score that quantifies the severity of the injury and predicts the likelihood of persistent symptoms.

“The field is moving for the first time towards an objective measure for ATE risk stratification, including diagnosis and prognosis that integrates biomarkers and neurocognitive assessment through AI,” said Donna Edmonds, CEO of BRAINBox Solutions. The goal is to create a new clinical best-practice standard that provides physicians with actionable information to guide patient care from the moment of injury.

The Path to Market: HeadSmart II and the Competitive Landscape

Bringing such a revolutionary tool to market requires rigorous validation. At the upcoming ADLM meeting, Dr. Peacock is set to provide an update on the HeadSmart II trial, a BRAINBox-sponsored pivotal study involving over 2,000 samples. The term “pivotal” is key; it means the trial is designed to provide the definitive evidence of safety and efficacy needed to support a marketing clearance submission to the U.S. Food and Drug Administration (FDA).

While other companies, such as Abbott and Banyan Biomarkers, have successfully brought FDA-cleared blood tests to market, their primary function is to help clinicians rule out the need for a CT scan in acute head trauma. They identify patients who likely do not have a life-threatening intracranial bleed. BRAINBox’s strategy aims for a much broader and more impactful clinical application: not just ruling out severe injury, but ruling in a concussion diagnosis and providing a detailed prognosis.

This multi-modal, AI-driven prognostic capability is the company’s core differentiator in a growing market. By offering a tool that can be used on point-of-care instruments or standard lab systems, the firm is positioning its technology for widespread adoption, from emergency rooms to sideline clinics. The upcoming panel, which also features Dr. Wu discussing the analytical requirements for TBI biomarker testing, is a strategic move to educate the laboratory medicine community and build the foundation for a paradigm shift in clinical practice.

Reshaping Patient Outcomes and Healthcare Economics

The potential impact of an objective, prognostic tool for concussion is immense. For patients, it could mean an end to the “wait and see” approach. An objective score could validate a patient's experience, guide personalized rehabilitation plans, and inform critical decisions about returning to work, school, or sports. For athletes, it could prevent the catastrophic consequences of a “second impact” injury sustained before the brain has fully healed.

From a healthcare systems perspective, the economic benefits are equally compelling. By improving diagnostic accuracy and enabling early, targeted interventions, such a test could reduce long-term care costs associated with chronic PCS. It could also optimize resource allocation in the emergency department, reducing unnecessary and costly CT scans while ensuring patients who need follow-up care receive it promptly.

This approach aligns perfectly with major initiatives from institutions like the National Institute of Neurological Disorders and Stroke (NINDS), which are advocating for new TBI classification systems that integrate biomarkers and clinical outcomes. The work being done by BRAINBox Solutions is not happening in a vacuum; it is at the forefront of a systemic shift toward more precise, data-driven neurology. The presentation at the ADLM conference is more than a scientific update; it is a glimpse into a future where the invisible injury of concussion is finally made visible.