The prevalence and burden of central nervous system (CNS) diseases worldwide is high and increasing, in part due to the aging of the global population. Despite significant unmet need, discovery and development for CNS disorders has been largely unsuccessful. Even with advances in our understanding of the underlying mechanisms of CNS conditions, the attrition rate of drugs in development remains elevated. This attrition is primarily driven by failure to show efficacy, and, in many cases, researchers are not even able to confirm that the investigational product reached its intended target for action.
As in other therapeutic areas, molecular biomarkers have the potential to revolutionize the development of novel treatments for neurological diseases. However, to date, there are few reliable, measurable biomarkers of mental disorders, even though these conditions account for a larger burden of disease than all cancers combined. Of the biomarkers that have been validated, many require invasive procedures or specialized equipment. Identification and validation of new biomarkers would contribute to new drug development, accelerating targeted discovery and enhancing the likelihood of clinical success.
For most CNS clinical trials, primary endpoints are based on subjective, and often cumbersome, clinician-rated outcome measures that frequently require training or certification prior to administration. The inherent subjectivity of existing efficacy assessments underscores the need for validated biomarkers that can be objectively measured.
Neuroimaging-based biomarkers have played an important role in CNS drug development and have even been used to assist in determining dosing of investigational new drugs (INDs) with novel mechanisms and targets.1 In addition, cerebrospinal fluid (CSF) immunophenotyping—which can be used to assess immune cell phenotypes and evaluate the biological of intrathecal inflammatory processes—has demonstrated potential in guiding immunotherapeutic selection and monitoring treatment efficacy.
The advent of technologies to support genomic, proteomic, and metabolomic interrogation of CNS tissues, CSF, or blood has helped to drive discovery of new CNS biomarkers, but challenges remain. In chronic progressive and relapsing neurodegenerative disease, biomarker identification and validation may be difficult because the underlying degenerative process may be so slow that the biomarker is released only in minute quantities. It may also be hard to differentiate acute, new damage from existing background damage.2 Moreover, pathological processes in the CNS are not always reflected in the systemic compartments, so plasma and serum biomarkers may not be available, limiting clinical feasibility.
To date, the use of CNS biomarkers in clinical trials has been most prevalent in studies of Alzheimer’s disease (AD), multiple sclerosis (MS), and Parkinson’s disease (PD).
Given that there is currently no cure for AD, early prediction is important because neuronal loss is often already present at the time of diagnosis. Available biomarkers for AD include neuroimaging, such as magnetic resonance imaging (MRI) and position emission tomography (PET), and CSF or blood biomarkers including amyloid beta (Aβ), pathologic tau (p-tau), Aβ42/Aβ40 ratio, tau/p-tau ratio, and neurofilament light chain (NfL). Plasma biomarkers are also being evaluated in clinical trials as exploratory endpoints and offer promise as minimally invasive, cost-effective tools for diagnosing AD, predicting cognitive decline, and determining trial or treatment eligibility.3
Several proteins are under investigation as biomarkers of MS, ranging from autoantibodies to biomarkers reflecting immune system alteration, blood-brain barrier disruption, oxidative stress, axonal or neuronal damage, and gliosis.3 One example of an ongoing trial exploring MS biomarkers involves assessment of single nucleotide polymorphism (SNP) haplotype, human leukocyte antigen (HLA) haplotype, and gene and protein expression in relation to clinical and MRI phenotype at baseline, as well as to change in disability, relapse rate, treatment response, and MRI measures of disease over a three-year period. The results of this study are expected to provide insight into disease pathogenesis and heterogeneity and to identify predictive biomarkers correlated with response to different therapies.4
As of January 2023, over 350 studies listed on ClinicalTrials.gov involve evaluation of biomarkers for PD.5 While clinical and imaging biomarkers have been the mainstay of diagnosis, an increasing number of biochemical and genetic biomarkers have emerged as potential tools for identifying at-risk populations, predicting prognosis, and discovering and delivering personalized therapeutic strategies. Still, no fully validated biomarker is currently available.
Other active areas of biomarker investigation include Huntington’s disease, CNS germ cell tumors, traumatic brain injury, epilepsy, stroke, and major depressive disorder.3
Digital biomarkers—collected via devices, wearables, functional assessments, mobile apps, and electronic patient reported outcomes (ePROs)—offer the opportunity for continuous data collection and monitoring outside of the healthcare setting. These biomarkers can support symptoms measures such as gait, balance, tremor, activity, sleep, cognition, and speech, which could be translated into clinical endpoints. For example, in multiple sclerosis, the current gold standard for performance assessment is the Timed 25 Foot Walk Test (T25FW). Collecting real-world data on walking speed via a wearable could be the digital equivalent of the T25FW.
There are several potential applications for biomarkers in CNS studies:
The use of biomarkers may enable earlier go/no go decisions, provide reassurance that compounds are having the intended on-target effect at tolerable doses, assist in dose selection, and serve as inclusion/exclusion criteria. However, the incorporation of biomarkers also increases complexity in terms of protocol design, patient enrollment, study support requirements, and data analysis. It may also require development and validation of sensitive, reliable, and robust assays, which takes time.
Identification and validation of novel biomarkers for CNS disorders holds promise for addressing existing shortcomings in diagnosis and disease monitoring, as well as the discovery and development of new targets and therapeutics. Technological advances have increased the pace of biomarker discovery but while thousands of biomarkers have been identified, most are yet to be validated. Incorporation of biomarkers into clinical trials and, ultimately, clinical practice will help to improve study efficiency success and inform advancements in personalized neurology.
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1. Suhara T, et al. Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP Working Group report. Int J Neuropsychopharmacol. 2017;20(4):285-294.
2. Jain KK. Biomarkers in neurology, updated May 30, 2021. Available at https://www.medlink.com/articles/biomarkers-in-neurology.
3. Cullen NC, et al. Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations. Nature Communications. 2021;12:3555.
4. National Institute of Neurological Disorders and Stroke. Biomarkers in multiple sclerosis. Available at https://www.ninds.nih.gov/health-information/clinical-trials/biomarkers-multiple-sclerosis.
5. ClinicalTrials.gov, searched January 24, 2023.
Tracey Owens is a Director of Project and Clinical Trial Management at Precision, having 28 years of experience in managing Phase I-IV clinical trials. Tracey is highly experienced in providing directional oversight on rare disease, CNS, psychiatric and oncology clinical trials. Her experience notably includes: ALS, bipolar disorder, epilepsy, major depressive disorder, schizophrenia, idiopathic hypersomnia, CIDP, traumatic brain injury, multiple myeloma and dementia (including Alzheimer’s and Parkinson’s Disease.)
Vincent Shortino is a Principal Clinical Trial Manager, bringing more than 20 years of experience to Precision. His experience spans all major therapeutic areas with a heavy emphasis on Cardiovascular and Rare Indications, across Phases I–IV. He brings solid perspectives inclusive of sites, pharma and CROs from his previous roles of Study Coordinator, Site Director, CRA, and Clinical Trial Manager.
Precision for Medicine is part of the Precision Medicine Group, an integrated team of experts that extends Precision for Medicine’s therapeutic development capabilities beyond approval and into launch strategies, marketing communication, and payer insights. As one company, the Precision Medicine Group helps pharmaceutical and life-sciences clients conquer product development and commercialization challenges in a rapidly evolving environment.
