Lilac Biosciences Inc. and Soin Neuroscience have announced the publication of a peer-reviewed clinical review proposing a translational framework for using RNA biomarkers to assess, classify and monitor neuropathic pain. Published in Frontiers in Pain Research on July 16, 2026, the article examines several RNA classes and outlines how they could eventually support a composite biological measure of pain, although the proposed testing system has not been validated in laboratory, animal or clinical studies.
The distinction between a scientific roadmap and a functioning diagnostic product is central to interpreting the publication. The review does not report results from a prospective clinical trial, introduce a commercially available assay or demonstrate that RNA measurements can accurately determine whether an individual patient is experiencing neuropathic pain. Instead, it attempts to organise a fragmented field into a development pathway that researchers, diagnostic companies and clinical trial sponsors could test.
That makes the publication strategically relevant without making it clinically definitive. Neuropathic pain remains difficult to quantify, treatment response varies substantially between patients, and drug developers frequently struggle to separate biological response from subjective reporting, placebo effects and heterogeneous disease mechanisms. RNA biomarkers could potentially add an objective molecular layer, but they would need to complement rather than invalidate the patient’s reported experience.
What exactly have Lilac Biosciences and Soin Neuroscience published?
The article, titled “New insight into RNA biomarkers in neuropathic pain: a clinician-neuroscientist roadmap to translational testing and treatment monitoring,” is a clinical review rather than an original research study. Its authors include clinicians from The Ohio Pain Clinic, researchers affiliated with Lilac Biosciences and a biomedical engineering researcher from Brown University.
The review covers messenger RNA, microRNA, long non-coding RNA, circular RNA, RNA editing and epitranscriptomic modifications such as N6-methyladenosine, commonly known as m6A. It argues that these different molecular layers could be combined to identify biological patterns associated with inflammation, neuronal excitability, central sensitisation, immune activity and other mechanisms relevant to neuropathic pain.
The authors propose a theoretical “pain biology score” that could integrate multiple RNA measurements into a continuous numerical output. Blood, peripheral blood mononuclear cells and potentially saliva are discussed as practical sample sources, while cerebrospinal fluid, skin biopsies and neuronal models could support deeper research applications.
Crucially, the authors state that this pain biology score remains theoretical and has not been validated through in vitro experiments, in vivo studies or clinical trials. They also acknowledge that no RNA based biomarker for pain has been approved by the United States Food and Drug Administration.
Why does neuropathic pain need better biological measurement?
Neuropathic pain can arise when the somatosensory nervous system is damaged or diseased. It is associated with conditions including diabetic neuropathy, postherpetic neuralgia, trigeminal neuralgia, chemotherapy induced peripheral neuropathy and complex regional pain syndrome.
Clinicians currently assess pain through medical history, neurological examination, sensory testing and patient-reported instruments such as numerical rating scales, visual analogue scales and neuropathic pain questionnaires. These tools are indispensable because pain is ultimately experienced by the patient, but they cannot fully reveal which molecular mechanisms are producing or maintaining the symptoms.
Two patients reporting the same pain score may have substantially different biological drivers. One may have prominent inflammatory activity, another may have abnormal ion channel signalling, while a third may have central sensitisation or progressive nerve degeneration. That heterogeneity can weaken clinical trial signals because a therapy directed at one mechanism may be tested across a biologically mixed population.
An objective biomarker would not need to prove that someone is in pain to be useful. Its more realistic early role could be identifying mechanistic subgroups, measuring whether a therapy has engaged its intended biological pathway or tracking whether molecular activity changes alongside reported symptoms.
That narrower purpose is less dramatic than a blood test that “measures pain,” but it is also more scientifically achievable.
Which RNA biomarkers appear most relevant to the proposed testing model?
RNA occupies an interesting position between relatively stable genetic information and rapidly changing cellular activity. RNA expression can change in response to injury, inflammation, medication, immune activation and therapeutic intervention, potentially providing a more dynamic picture than a static DNA sequence.
Messenger RNA reflects which genes are being actively expressed. MicroRNAs and long non-coding RNAs regulate gene activity and may influence inflammatory signalling, neuronal plasticity and ion channel expression. Circular RNAs may also contribute to regulatory networks linked to pain processing.
The review additionally examines RNA editing and m6A modifications. These epitranscriptomic mechanisms can alter the stability, processing or translation of RNA molecules without changing the underlying DNA sequence. Preclinical research has linked m6A related regulatory activity to pathways involved in central sensitisation and neuropathic pain, although translating those observations into a reproducible human blood test is a much larger challenge.
The proposed model therefore avoids relying on a single molecule. It instead suggests combining several molecular modules, potentially covering immune activation, sensory neuron excitability, inflammatory signalling, RNA regulation and post-transcriptional modification.
This multi-marker strategy reflects the complexity of neuropathic pain, but complexity can quickly become a commercial disadvantage. Every additional marker increases the requirements for assay reproducibility, computational interpretation, quality control, sample handling and regulatory validation.
How would a proposed RNA based pain biology score work?
The review describes a tiered biomarker architecture beginning with accessible blood transcriptomics. A first layer could measure immune and inflammatory gene expression in peripheral blood. Additional layers could incorporate neuropathic pain mechanisms and post-transcriptional RNA modifications.
The authors envision computational models assigning different weights to messenger RNA, microRNA and RNA editing signals. The resulting score could theoretically correlate with a reference assessment and produce a standardised value representing biological risk or activity.
This is conceptually similar to multigene tests already used in some areas of oncology and transplant medicine, where no single biomarker provides enough information and an algorithm combines multiple molecular measurements. Pain, however, creates a distinctive validation problem because there is no universally accepted biological gold standard against which the test can be trained.
Quantitative sensory testing could provide one comparator, but it also measures responses influenced by attention, cognition, test methodology and patient participation. Imaging, nerve conduction studies and skin biopsies can add information, but each captures only part of the underlying biology.
A successful validation programme may therefore require composite reference standards combining clinical diagnosis, sensory testing, longitudinal symptoms, functional outcomes and treatment response. The eventual score would need to demonstrate that it adds useful information beyond these existing assessments rather than merely reproducing them at greater cost.
Why should the publication not be treated as clinical validation?
Peer review strengthens the credibility of the scientific discussion, but it does not transform a proposed framework into a validated diagnostic test. The publication synthesises existing research and recommends a development pathway. It does not present sensitivity, specificity, positive predictive value, negative predictive value or prospective patient outcomes for a defined assay.
The review itself is unusually clear about this limitation. It says the proposed pain biology score is theoretical and that substantial work remains around standardisation, external validation, regulatory review and large-scale clinical testing.
The underlying evidence is also uneven. Some candidate RNA mechanisms have been investigated in animal models, neural tissue or small discovery cohorts. Signals identified in one pain condition, tissue type or patient population may not reproduce in another. A biomarker associated with diabetic neuropathy, for example, may behave differently in postherpetic neuralgia or chemotherapy induced peripheral neuropathy.
RNA expression is also sensitive to infection, autoimmune disease, medicines, smoking, body mass index, circadian rhythm, age, sex and sample processing. These variables can produce molecular changes unrelated to pain, creating a risk that an assay detects general inflammation or physiological stress rather than neuropathic pain biology.
Blood accessibility presents another problem. Much of the relevant pathology occurs in peripheral nerves, dorsal root ganglia, the spinal cord and the brain. A peripheral blood signature may offer useful indirect information, but it cannot automatically be assumed to represent molecular events inside nervous tissue.
What would a credible clinical validation programme need to demonstrate?
The first requirement would be analytical validation. Researchers would need to show that the assay consistently measures the intended RNA targets across operators, laboratories, instruments, reagent lots, storage conditions and sample handling procedures.
Pre-analytical controls would be especially important because RNA can degrade and expression patterns can change depending on collection tubes, processing delays, temperature and extraction methods. An impressive computational score has little clinical value if the underlying measurements vary whenever a sample is transported or processed differently.
The second requirement would be clinical validation in well-characterised patient cohorts. Studies would need to include multiple neuropathic pain subtypes, non-neuropathic pain controls, healthy controls and patients with inflammatory or neurological conditions that could confound RNA signals.
Validation should also be geographically diverse and appropriately stratified by age, sex, disease duration, medication exposure and comorbidities. The review specifically notes the importance of sex-related molecular differences and cautions that preliminary candidate markers require confirmation in larger independent cohorts.
The third requirement would be clinical utility. A test can be analytically accurate and statistically associated with disease without improving treatment decisions or outcomes. Developers would need to demonstrate that clinicians can use the result to select patients, predict response, monitor therapy or reduce trial variability in a way that is meaningful and cost-effective.
The review suggests an initial laboratory-developed test pathway followed by broader regulatory development. The ultimate regulatory route would depend on the assay’s intended use. A research tool used for exploratory trial endpoints would face a different evidentiary burden from a diagnostic test used to determine whether a patient has neuropathic pain.
Could RNA biomarkers improve pain drug and neuromodulation trials?
Clinical trials may represent the most credible first commercial use case. Pharmaceutical and medical device developers frequently need pharmacodynamic biomarkers that indicate whether an intervention is affecting its intended biological mechanism.
An RNA panel could potentially show whether an anti-inflammatory therapy reduced a relevant immune signature, whether a neuromodulation intervention altered neuronal signalling pathways or whether a patient’s molecular profile shifted alongside improvements in symptoms and function.
Such biomarkers could also support patient enrichment. Instead of enrolling a broad population under a single neuropathic pain label, a sponsor might identify patients whose biology is more closely aligned with the therapy’s mechanism of action.
That approach could reduce biological noise, but it could also narrow the eligible patient population and create a demanding co-development programme. The biomarker would need to be locked, validated and prospectively incorporated into trial protocols. Retrospective identification of a responding subgroup would be hypothesis-generating rather than confirmatory.
Soin Neuroscience has a direct interest in this question because its research activities have included spinal cord stimulation and neuromodulation. The company and Lilac Biosciences announced a collaboration in February 2026 to study whether RNA expression changes could serve as biological correlates of pain states and neuromodulation response. That programme was initially described as preclinical research involving defined stimulation parameters, waveforms and time courses.
The new review provides a scientific rationale for that collaboration, but it does not disclose experimental results from it.
What does the publication mean commercially for Lilac Biosciences?
Lilac Biosciences is developing low-input RNA measurement technologies originating from work connected to Brown University’s Giuliani RNA Center. The pain field gives the company an opportunity to apply those capabilities to a clinical problem where objective biological tools remain limited.
The commercial opportunity, however, will depend less on publishing a broad framework and more on demonstrating that Lilac’s workflows produce reproducible measurements from clinically practical samples. Speed, sample volume and molecular sensitivity matter, but diagnostic developers, laboratories and pharmaceutical sponsors will also examine failure rates, inter-laboratory consistency, cost and regulatory readiness.
The publication’s conflict-of-interest disclosure states that Shreyas Shah and Sabrina Tolppi are affiliated with Lilac Biosciences, which develops low-input RNA detection technologies discussed in the manuscript. The authors reported receiving no financial support for the work or its publication. That disclosure does not invalidate the review, but readers should recognise that the paper combines scientific analysis with technology areas relevant to Lilac’s commercial strategy.
For Lilac, a logical next step would be moving from a technology-enabled concept to a clearly defined assay-development programme. That would require specifying the intended use, patient population, sample type, marker panel, analytical platform and clinical endpoint.
Without those decisions, “objective pain testing” remains an attractive umbrella concept rather than a product proposition.
What should clinicians and diagnostics developers watch next?
The most meaningful milestone would be publication of prospective human data using a predefined RNA panel. Discovery research identifying dozens or hundreds of differentially expressed transcripts would be insufficient on its own. The field needs locked algorithms tested in independent patients who were not used to build the model.
Longitudinal sampling will also matter. A clinically useful monitoring test should show whether RNA signatures change consistently when a patient improves, deteriorates or receives an effective intervention. Researchers must then determine whether those changes reflect pain mechanisms, medication effects or unrelated biological variation.
For neuromodulation, an important question will be whether molecular changes correlate with stimulation settings, patient-reported relief and functional improvement. Evidence that a waveform changes an RNA signature would not establish clinical benefit unless the molecular signal is connected to meaningful patient outcomes.
The review gives Lilac Biosciences and Soin Neuroscience a credible scientific platform from which to build those studies. It also highlights why progress will probably be incremental. Neuropathic pain is not a single molecular condition, blood is an imperfect window into nervous system biology, and the absence of an established reference standard makes diagnostic development unusually difficult.
RNA biomarkers may eventually help clinicians and researchers describe the biology beneath a patient’s symptoms. The decisive test will be whether a defined assay can produce reproducible, clinically interpretable information that improves patient selection, trial design or treatment monitoring beyond what existing assessments already provide.
