Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization

Age-Dependent Changes of Kidney Injury Biomarkers in Pediatrics

Currently used creatinine-based parameters for monitoring kidney function are not reliable for early detection of kidney injury (KI), particularly tubular damage. Several KI biomarkers allow for early detection of glomerular and tubular damage and may help to prevent drug-related chronic kidney diseases in pediatrics. This literature review describes the state of current research and investigates reference values for these KI biomarkers in neonates, infants, and children to better understand age-related changes. A total of 12 of 237 screened studies fulfilled predefined criteria, including 219 preterm neonates, 70 neonates, 596 infants, and 1726 children. KI biomarkers were analyzed in urine (6 studies), in serum/plasma (5 studies) and in serum and urine (1 study). Four studies (n = 555) measured urinary kidney injury molecule-1, whereas urinary neutrophil gelatinase-associated lipocalin was assessed in 5 studies (n = 888), and 2 studies (n = 203) investigated serum cystatin C. This review of KI biomarkers in different pediatric age groups indicates that (1) the majority of KI biomarkers are measured in urine; (2) the 3 most commonly analyzed KI biomarkers are urinary neutrophil gelatinase-associated lipocalin, urinary kidney injury molecule-1, and serum cystatin C; (3) values of KI biomarkers appear to decrease from prematurity to infancy; and (4) there is an unmet need to further enhance knowledge on age-dependent changes of KI biomarkers in pediatrics. Studies are needed to better characterize reference values for these key KI biomarkers in healthy pediatric populations and to evaluate the value of these markers in the early detection of drug-related KI in neonates, infants, and children.

Accelerated Approval or Risk Reduction? How Response Biomarkers Advance Therapeutics through Clinical Trials in Cystic Fibrosis

Progress in the development of new therapies for cystic fibrosis (CF) has benefited from therapeutically responsive biomarkers to streamline drug development. Paradoxically, these response biomarkers have been proven to be essential even in the presence of data demonstrating a lack of correlation with clinical outcomes across individuals with CF. This finding is unsurprising, particularly in the setting of a rare disease given complex disease processes and an often-limited pool of clinically effective therapies by which to link biomarkers and clinical responsiveness. While many response biomarkers will be unable to progress from their status as markers of biological efficacy to either established correlates of clinical efficacy or surrogate endpoints, they remain critical to the overall success of therapeutic development.

Can the Onset of Atrophic Age-Related Macular Degeneration Be an Acceptable Endpoint for Preventative Trials?

The slowly progressive nature of age-related macular degeneration (AMD) means that establishing the efficacy of novel preventative treatments aiming to slow progression of disease, remains challenging, and where earlier endpoints are needed to improve their feasibility. This review examines whether the onset of atrophic AMD, as seen as anatomical signs on optical coherence tomography termed nascent geographic atrophy, could act as a useful surrogate endpoint for early intervention trials.

Pharmacodynamic Biomarkers for Emerging LRRK2 Therapeutics

Genetic studies have identified variants in the LRRK2 gene as important components of Parkinson's disease (PD) pathobiology. Biochemical and emergent biomarker studies have coalesced around LRRK2 hyperactivation in disease. Therapeutics that diminish LRRK2 activity, either with small molecule kinase inhibitors or anti-sense oligonucleotides, have recently advanced to the clinic. Historically, there have been few successes in the development of therapies that might slow or halt the progression of neurodegenerative diseases. Over the past few decades of biomedical research, retrospective analyses suggest the broad integration of informative biomarkers early in development tends to distinguish successful pipelines from those that fail early. Herein, we discuss the biomarker regulatory process, emerging LRRK2 biomarker candidates, assays, underlying biomarker biology, and clinical integration.

Treatment-related changes in bone mineral density as a surrogate biomarker for fracture risk reduction: meta-regression analyses of individual patient data from multiple randomised controlled trials

BACKGROUND

The validation of bone mineral density (BMD) as a surrogate outcome for fracture would allow the size of future randomised controlled osteoporosis registration trials to be reduced. We aimed to determine the association between treatment-related changes in BMD, assessed by dual-energy x-ray absorptiometry, and fracture outcomes, including the proportion of treatment effect explained by BMD changes.

METHODS

We did a pooled analysis of individual patient data from multiple randomised placebo-controlled clinical trials. We included data from multicentre, randomised, placebo-controlled, double-blind trials of osteoporosis medications that included women and men at increased osteoporotic fracture risk. Using individual patient data for each trial we calculated mean 24-month BMD percent change together with fracture reductions and did a meta-regression of the association between treatment-related differences in BMD changes (percentage difference, active minus placebo) and fracture risk reduction. We also used individual patient data to determine the proportion of anti-fracture treatment effect explained by BMD changes and the BMD change needed in future trials to ensure fracture reduction efficacy.

FINDINGS

Individual patient data from 91 779 participants of 23 randomised, placebo-controlled trials were included. The trials had 1-9 years of follow-up and included 12 trials of bisphosphonate, one of odanacatib, two of hormone therapy (one of conjugated equine oestrogen and one of conjugated equine oestrogen plus medroxyprogesterone acetate), three of PTH receptor agonists, one of denosumab, and four of selective oestrogen receptor modulator trials. The meta-regression revealed significant associations between treatment-related changes in hip, femoral neck, and spine BMD and reductions in vertebral (r2 0·73, p<0·0001; 0·59, p=0·0005; 0·61, p=0·0003), hip (0·41, p=0·014; 0·41, p=0·0074; 0·34, p=0·023) and non-vertebral fractures (0·53, p=0·0021; 0·65, p<0·0001; 0·51, p=0·0019). Minimum 24-month percentage changes in total hip BMD providing almost certain fracture reductions in future trials ranged from 1·42% to 3·18%, depending on fracture site. Hip BMD changes explained substantial proportions (44-67%) of treatment-related fracture risk reduction.

INTERPRETATION

Treatment-related BMD changes are strongly associated with fracture reductions across randomised trials of osteoporosis therapies with differing mechanisms of action. These analyses support BMD as a surrogate outcome for fracture outcomes in future randomised trials of new osteoporosis therapies and provide an important demonstration of the value of public access to individual patient data from multiple trials.

FUNDING

Foundation for National Institutes of Health.

Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers

PURPOSE

The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) consortium intends to prospectively describe in detail, preselected patients with knee osteoarthritis (OA), using conventional and novel clinical, imaging, and biochemical markers, to support OA drug development.

PARTICIPANTS

APPROACH is a prospective cohort study including 297 patients with tibiofemoral OA, according to the American College of Rheumatology classification criteria. Patients were (pre)selected from existing cohorts using machine learning models, developed on data from the CHECK cohort, to display a high likelihood of radiographic joint space width (JSW) loss and/or knee pain progression.

FINDINGS TO DATE

Selection appeared logistically feasible and baseline characteristics of the cohort demonstrated an OA population with more severe disease: age 66.5 (SD 7.1) vs 68.1 (7.7) years, min-JSW 2.5 (1.3) vs 2.1 (1.0) mm and Knee injury and Osteoarthritis Outcome Score pain 31.3 (19.7) vs 17.7 (14.6), except for age, all: p<0.001, for selected versus excluded patients, respectively. Based on the selection model, this cohort has a predicted higher chance of progression.

FUTURE PLANS

Patients will visit the hospital again at 6, 12 and 24 months for physical examination, pain and general health questionnaires, collection of blood and urine, MRI scans, radiographs of knees and hands, CT scan of the knee, low radiation whole-body CT, HandScan, motion analysis and performance-based tests.After two years, data will show whether those patients with the highest probabilities for progression experienced disease progression as compared to those wit lower probabilities (model validation) and whether phenotypes/endotypes can be identified and predicted to facilitate targeted drug therapy.

TRIAL REGISTRATION NUMBER

NCT03883568.

Technical Performance of Two-Dimensional Shear Wave Elastography for Measuring Liver Stiffness: A Systematic Review and Meta-Analysis

Objective

To assess the technical performance of two-dimensional shear wave elastography (2D-SWE) for measuring liver stiffness.

Materials and Methods

The Ovid-MEDLINE and EMBASE databases were searched for studies reporting the technical performance of 2D-SWE, including concerns with technical failures, unreliable measurements, interobserver reliability, and/or intraobserver reliability, published until June 30, 2018. The pooled proportion of technical failure and unreliable measurements was calculated using meta-analytic pooling via the random-effects model and inverse variance method for calculating weights. Subgroup analyses were performed to explore potential causes of heterogeneity. The pooled intraclass correlation coefficients (ICCs) for interobserver and intraobserver reliability were calculated using the Hedges-Olkin method with Fisher's Z transformation of the correlation coefficient.

Results

The search yielded 34 articles. From 20 2D-SWE studies including 6196 patients, the pooled proportion of technical failure was 2.3% (95% confidence interval [CI], 1.3–3.9%). The pooled proportion of unreliable measurements from 20 studies including 6961 patients was 7.5% (95% CI, 4.7–11.7%). In the subgroup analyses, studies conducting more than three measurements showed fewer unreliable measurements than did those with three measurements or less, but no intergroup difference was found in technical failure. The pooled ICCs for interobserver reliability (from 10 studies including 517 patients) and intraobserver reliability (from 7 studies including 679 patients) were 0.87 (95% CI, 0.82–0.90) and 0.93 (95% CI, 0.89–0.95), respectively, suggesting good to excellent reliability.

Conclusion

2D-SWE shows good technical performance for assessing liver stiffness, with high technical success and reliability. Future studies should establish the quality criteria and optimal number of measurements.

Exploiting Circulating MicroRNAs as Biomarkers in Psychiatric Disorders

Non-invasive peripheral biomarkers play a significant role in both disease diagnosis and progression. In the past few years, microRNA (miRNA) expression changes in circulating peripheral tissues have been found to be correlative with changes in neuronal tissues from patients with neuropsychiatric disorders. This is a notable quality of a biomolecule to be considered as a biomarker for both prognosis and diagnosis of disease. miRNAs, members of the small non-coding RNA family, have recently gained significant attention due to their ability to epigenetically influence almost every aspect of brain functioning. Empirical evidence suggests that miRNA-associated changes in the brain are often translated into behavioral changes. Current clinical understanding further implicates their role in the management of major psychiatric conditions, including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). This review aims to critically evaluate the potential advantages and disadvantages of miRNAs as diagnostic/prognostic biomarkers in psychiatric disorders as well as in treatment response.

Urinary Amine and Organic Acid Metabolites Evaluated as Markers for Childhood Aggression: The ACTION Biomarker Study

Biomarkers are of interest as potential diagnostic and predictive instruments in personalized medicine. We present the first urinary metabolomics biomarker study of childhood aggression. We aim to examine the association of urinary metabolites and neurotransmitter ratios involved in key metabolic and neurotransmitter pathways in a large cohort of twins (N = 1,347) and clinic-referred children (N = 183) with an average age of 9.7 years. This study is part of ACTION (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies), in which we developed a standardized protocol for large-scale collection of urine samples in children. Our analytical design consisted of three phases: a discovery phase in twins scoring low or high on aggression (N = 783); a replication phase in twin pairs discordant for aggression (N = 378); and a validation phase in clinical cases and matched twin controls (N = 367). In the discovery phase, 6 biomarkers were significantly associated with childhood aggression, of which the association of O-phosphoserine (β = 0.36; SE = 0.09; p = 0.004), and gamma-L-glutamyl-L-alanine (β = 0.32; SE = 0.09; p = 0.01) remained significant after multiple testing. Although non-significant, the directions of effect were congruent between the discovery and replication analyses for six biomarkers and two neurotransmitter ratios and the concentrations of 6 amines differed between low and high aggressive twins. In the validation analyses, the top biomarkers and neurotransmitter ratios, with congruent directions of effect, showed no significant associations with childhood aggression. We find suggestive evidence for associations of childhood aggression with metabolic dysregulation of neurotransmission, oxidative stress, and energy metabolism. Although replication is required, our findings provide starting points to investigate causal and pleiotropic effects of these dysregulations on childhood aggression.

Determination of Minimal Residual Disease in Multiple Myeloma: Does It Matter?

PURPOSE OF REVIEW

The ability to detect minimal residual disease (MRD) in myeloma has improved due to advances in flow cytometry and sequencing methodologies. Here, we evaluate recent clinical trial data and explore the current and future roles of MRD assessment in the context of clinical trial design and clinical practice.

RECENT FINDINGS

A review of recent phase III studies reveals that achievement of MRD negativity is associated with improved progression-free survival (PFS) and/or overall survival (OS). Treatment arms that are more effective from a PFS or overall response rate perspective are also associated with superior MRD negativity rates. The current standard MRD methodologies are limited by requiring bone marrow samples and refinement of methodologies that can detect disease outside of the bone marrow is needed. Currently, MRD is a prognostic biomarker and further efforts are required to determine whether it can serve as a surrogate endpoint. The use of MRD status to guide treatment decisions is currently not recommended outside the confines of a clinical trial.

A multiparametric organ toxicity predictor for drug discovery

The assessment of major organ toxicities through in silico predictive models plays a crucial role in drug discovery. Computational tools can predict chemical toxicities using the knowledge gained from experimental studies which drastically reduces the attrition rate of compounds during drug discovery and developmental stages. The purpose of in silico predictions for drug leads and anticipating toxicological endpoints of absorption, distribution, metabolism, excretion and toxicity, clinical adverse impacts and metabolism of pharmaceutically active substances has gained widespread acceptance in academia and pharmaceutical industries. With unrestricted accessibility to powerful biomarkers, researchers have an opportunity to contemplate the most accurate predictive scores to evaluate drug's adverse impact on various organs.A multiparametric model involving physico-chemical properties, quantitative structure-activity relationship predictions and docking score was found to be a more reliable predictor for estimating chemical toxicities with potential to reflect atomic-level insights. These in silico models provide informed decisions to carry out in vitro and in vivo studies and subsequently confirms the molecules clues deciphering the cytotoxicity, pharmacokinetics, and pharmacodynamics and organ toxicity properties of compounds. Even though the drugs withdrawn by USFDA at later phases of drug discovery which should have passed all the state-of-the-art experimental approaches and currently acceptable toxicity filters, there is a dire need to interconnect all these molecular key properties to enhance our knowledge and guide in the identification of leads to drug optimization phases. Current computational tools can predict ADMET and organ toxicities based on pharmacophore fingerprint, toxicophores and advanced machine-learning techniques.

Biomarker Acquisition and Quality Control for Multi-Site Studies: The Autism Biomarkers Consortium for Clinical Trials

The objective of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is to evaluate a set of lab-based behavioral video tracking (VT), electroencephalography (EEG), and eye tracking (ET) measures for use in clinical trials with children with autism spectrum disorder (ASD). Within the larger organizational structure of the ABC-CT, the Data Acquisition and Analytic Core (DAAC) oversees the standardization of VT, EEG, and ET data acquisition, data processing, and data analysis. This includes designing and documenting data acquisition and analytic protocols and manuals; facilitating site training in acquisition; data acquisition quality control (QC); derivation and validation of dependent variables (DVs); and analytic deliverables including preparation of data for submission to the National Database for Autism Research (NDAR). To oversee consistent application of scientific standards and methodological rigor for data acquisition, processing, and analytics, we developed standard operating procedures that reflect the logistical needs of multi-site research, and the need for well-articulated, transparent processes that can be implemented in future clinical trials. This report details the methodology of the ABC-CT related to acquisition and QC in our Feasibility and Main Study phases. Based on our acquisition metrics from a preplanned interim analysis, we report high levels of acquisition success utilizing VT, EEG, and ET experiments in a relatively large sample of children with ASD and typical development (TD), with data acquired across multiple sites and use of a manualized training and acquisition protocol.

Translation of Digital Health Technologies to Advance Precision Medicine: Informing Regulatory Science

The proliferation of digital technologies and the application of sophisticated data analysis techniques are increasingly viewed as having the potential to transform translational research and precision medicine. While digital technologies are rapidly applied in innovative ways to develop new diagnostics and therapies, the ultimate approval and adoption of these emerging methods presents several scientific and regulatory challenges. To better understand and address these regulatory science gaps, a working group of the Clinical and Translational Science Awards Program convened the Regulatory Science to Advance Precision Medicine Forum focused on digital health, particularly examining gaps in the use, validation, and interpretation of data from sensors that collect and tools that analyze digital biomarkers. The key findings and recommendations provided here emerged from the Forum and include the need to enhance areas related to data standards, data quality and validity, knowledge management, and building trust between all stakeholders.

Beyond Blood Smears: Qualification of Plasmodium 18S rRNA as a Biomarker for Controlled Human Malaria Infections

18S rRNA is a biomarker that provides an alternative to thick blood smears in controlled human malaria infection (CHMI) trials. We reviewed data from CHMI trials at non-endemic sites that used blood smears and Plasmodium 18S rRNA/rDNA biomarker nucleic acid tests (NATs) for time to positivity. We validated a multiplex quantitative reverse transcription–polymerase chain reaction (qRT-PCR) for Plasmodium 18S rRNA, prospectively compared blood smears and qRT-PCR for three trials, and modeled treatment effects at different biomarker-defined parasite densities to assess the impact on infection detection, symptom reduction, and measured intervention efficacy. Literature review demonstrated accelerated NAT-based infection detection compared with blood smears (mean acceleration: 3.2–3.6 days). For prospectively tested trials, the validated Plasmodium 18S rRNA qRT-PCR positivity was earlier (7.6 days; 95% CI: 7.1–8.1 days) than blood smears (11.0 days; 95% CI: 10.3–11.8 days) and significantly preceded the onset of grade 2 malaria-related symptoms (12.2 days; 95% CI: 10.6–13.3 days). Discrepant analysis showed that the risk of a blood smear–positive, biomarker-negative result was negligible. Data modeling predicted that treatment triggered by specific biomarker-defined thresholds can differentiate complete, partial, and non-protective outcomes and eliminate many grade 2 and most grade 3 malaria-related symptoms post-CHMI. Plasmodium 18S rRNA is a sensitive and specific biomarker that can justifiably replace blood smears for infection detection in CHMI trials in non-endemic settings. This study led to biomarker qualification through the U.S. Food and Drug Administration for use in CHMI studies at non-endemic sites, which will facilitate biomarker use for the qualified context of use in drug and vaccine trials.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

Biological and Clinical Markers to Differentiate the Type of Anxiety Disorders

The present chapter is an overview of possible biomarkers which distinguish anxiety disorders as classified by the DSM-5. Structural or activity changes in the brain regions; changes in N-acetylaspartate/creatine, dopamine, serotonin, and oxytocin; hearth rate variability; hypothalamic-pituitary-adrenal axis activity; error-related negativity; respiratory regulation; and genetic variants are proposed. However, their clinical utility is questionable due to low specificity and sensitivity: the majority does not distinguish subjects with different anxiety disorders, and they might be influenced by stress, comorbidity, physical activity, and psychotropic medications. In this framework, the staging model, a clinimetric tool which allows to define the degree of progression of a disease at a point in time and where the patient is located on the continuum of the course of the disease, is proposed since several DSM anxiety disorders take place at different stages of the same syndrome according to the staging model. Thus, a stage-specific biomarker model for anxiety disorders is hypothesized and illustrated.

Development of a biomarker mortality risk model in acute respiratory distress syndrome

Background

There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.

Methods

This is a secondary analysis using a cohort of 252 mechanically ventilated subjects with the diagnosis of acute respiratory distress syndrome. Survival to day 7 with both day 0 (first day of presentation) and day 7 sample availability was required. Blood was collected for biomarker measurements at first presentation to the intensive care unit and on the seventh day. Biomarkers included cytokine-chemokines, dual-functioning cytozymes, and vascular injury markers. Logistic regression, latent class analysis, and classification and regression tree analysis were used to identify the plasma biomarkers most predictive of 28-day ARDS mortality.

Results

From eight biologically relevant biomarker candidates, six demonstrated an enhanced capacity to predict mortality at day 0. Latent-class analysis identified two biomarker-based phenotypes. Phenotype A exhibited significantly higher plasma levels of angiopoietin-2, macrophage migration inhibitory factor, interleukin-8, interleukin-1 receptor antagonist, interleukin-6, and extracellular nicotinamide phosphoribosyltransferase (eNAMPT) compared to phenotype B. Mortality at 28 days was significantly higher for phenotype A compared to phenotype B (32% vs 19%, p = 0.04).

Conclusions

An adult biomarker-based risk model reliably identifies ARDS subjects at risk of death within 28 days of hospitalization.

Pre-treatment peripheral biomarkers associated with treatment response in panic symptoms in patients with major depressive disorder and panic disorder: A 12-week follow-up study

OBJECTIVE

Peripheral biomarkers have been studied to predict treatment response of panic symptoms. We hypothesized that depressive disorder (MDD) vs. panic disorder (PD) would exhibit different peripheral biomarkers, and their correlation with severity of panic attacks (PA) would also differ.

METHODS

Forty-one MDD patients, 52 PD patients, and 59 healthy controls were followed for 12 weeks. We measured peripheral biomarkers along with the Panic Disorder Severity Scale (PDSS) at each visit-pre-treatment, 2, 4, 8, and 12 weeks on a regular schedule. Peripheral biomarkers including serum cytokines, plasma and serum brain-derived neurotrophic factor (BDNF), leptin, adiponectin, and C-reactive protein (CRP) were quantified using enzyme-linked immunosorbent assay (ELISA).

RESULTS

Patients with MDD and PD demonstrated significantly higher levels of pre-treatment IL-6 compared to controls, but no differences were seen in plasma and serum BDNF, leptin, adiponectin, and CRP. Pre-treatment leptin showed a significant clinical correlation with reduction of panic symptoms in MDD patients at visit 5 (p=0.011), whereas pre-treatment IL-6 showed a negative correlation with panic symptom reduction in PD patients (p=0.022). An improvement in three panic-related items was observed to be positively correlated with pre-treatment leptin in MDD patients: distress during PA, anticipatory anxiety, and occupational interference.

CONCLUSION

Higher pre-treatment leptin was associated with better response to treatment regarding panic symptoms in patients with MDD, while higher IL-6 was associated with worse response regarding panic symptoms in PD patients. Different predictive peripheral biomarkers observed in MDD and PD suggest the need for establishing individualized predictive biomarkers, even in cases of similar symptoms observed in different disorders.

Comparison between protocols and publications for prognostic and predictive cancer biomarker studies

BACKGROUND

Method prespecification in study protocols is important for controlling bias in reports. The primary goal of this study was to assess potential for discordance between study protocols and publications reporting predictive or prognostic cancer biomarker research. Secondary objectives included comparing characteristics of publications with accessible protocols compared to those without.

METHODS

Publications reporting predictive or prognostic cancer biomarker research were identified from 15 major journals, 2012-2015. Protocols were sought online or through repeated queries of corresponding authors. The following four items were extracted: (1) biomarkers, (2) biospecimen/assays, (3) sample size, (4) endpoints. We defined "explicit discordance" as the presence of major inconsistencies on these items.

RESULTS

Of 149 eligible publications, we obtained 19 eligible protocols online (13%). Out of a random sample of 103 publications where protocols were not available online, 12 protocols (12%) were furnished by corresponding authors; 8 (8% of authors) explicitly stated the absence of a protocol. Among 24 retrospective cohort studies, no protocol could be accessed. We found explicit discordance between publications and protocols for 18 studies (58%), in particular choice of biomarkers (36%), biospecimen/assays (6%), or endpoints (29%).

CONCLUSION

Protocols are generally not accessible or not used for cancer biomarker studies. Publications were often explicitly discordant with protocols, particularly regarding biomarkers and endpoints. Our findings point to common unaddressed risk of bias in publications of major journals reporting the relationship between cancer biomarkers and clinical endpoints.

Reliable and robust method for abdominal muscle mass quantification using CT/MRI: An explorative study in healthy subjects

Background

Quantification of abdominal muscle mass by cross-sectional imaging has been increasingly used to diagnose sarcopenia; however, the technical method for quantification has not been standardized yet. We aimed to determine an optimal method to measure the abdominal muscle area.

Methods

Among 50 consecutive subjects who underwent abdominal CT and MRI for possible liver donation, total abdominal muscle area (TAMA) and total psoas muscle area (TPA) at the L3 inferior endplate level were measured by two blinded readers. Inter-scan agreement between CT and MRI and inter-reader agreement between the two readers were evaluated using intraclass correlation coefficient (ICC) and within-subject coefficient of variation (WSCV). To evaluate the effect of measurement level, one reader measured TAMA and TPA at six levels from the L2 to L4 vertebral bodies.

Results

TAMA was a more reliable biomarker than TPA in terms of inter-scan agreement (ICC: 0.928 vs. 0.788 for reader 1 and 0.853 vs. 0.821 for reader 2, respectively; WSCV: 8.3% vs. 23.4% for reader 1 and 10.4% vs. 22.3% for reader 2, respectively) and inter-reader agreement (ICC: 0.986 vs. 0.886 for CT and 0.865 vs. 0.669 for MRI, respectively; WSCV: 8.2% vs. 16.0% for CT and 11.6% vs. 29.7% for MRI, respectively). In terms of the measurement level, TAMA did not differ from the L2_inf to L4_inf levels, whereas TPA increased with a decrease in measurement level.

Conclusions

TAMA is a better biomarker than TPA in terms of inter-scan and inter-reader agreement and robustness to the measurement level. CT was a more reliable imaging modality than MRI. Our results support the use of TAMA measured by CT as a standard biomarker for abdominal muscle area measurement.

Current Status and Future Opportunities in Lung Precision Medicine Research with a Focus on Biomarkers. An American Thoracic Society/National Heart, Lung, and Blood Institute Research Statement

BACKGROUND

Thousands of biomarker tests are either available or under development for lung diseases. In many cases, adoption of these tests into clinical practice is outpacing the generation and evaluation of sufficient data to determine clinical utility and ability to improve health outcomes. There is a need for a systematically organized report that provides guidance on how to understand and evaluate use of biomarker tests for lung diseases.

METHODS

We assembled a diverse group of clinicians and researchers from the American Thoracic Society and leaders from the National Heart, Lung, and Blood Institute with expertise in various aspects of precision medicine to review the current status of biomarker tests in lung diseases. Experts summarized existing biomarker tests that are available for lung cancer, pulmonary arterial hypertension, idiopathic pulmonary fibrosis, asthma, chronic obstructive pulmonary disease, sepsis, acute respiratory distress syndrome, cystic fibrosis, and other rare lung diseases. The group identified knowledge gaps that future research studies can address to efficiently translate biomarker tests into clinical practice, assess their cost-effectiveness, and ensure they apply to diverse, real-life populations.

RESULTS

We found that the status of biomarker tests in lung diseases is highly variable depending on the disease. Nevertheless, biomarker tests in lung diseases show great promise in improving clinical care. To efficiently translate biomarkers into tests used widely in clinical practice, researchers need to address specific clinical unmet needs, secure support for biomarker discovery efforts, conduct analytical and clinical validation studies, ensure tests have clinical utility, and facilitate appropriate adoption into routine clinical practice.

CONCLUSIONS

Although progress has been made toward implementation of precision medicine for lung diseases in clinical practice in certain settings, additional studies focused on addressing specific unmet clinical needs are required to evaluate the clinical utility of biomarkers; ensure their generalizability to diverse, real-life populations; and determine their cost-effectiveness.

Evidence to Support Inclusion of Pharmacogenetic Biomarkers in Randomised Controlled Trials

Pharmacogenetics and biomarkers are becoming normalised as important technologies to improve drug efficacy rates, reduce the incidence of adverse drug reactions, and make informed choices for targeted therapies. However, their wider clinical implementation has been limited by a lack of robust evidence. Suitable evidence is required before a biomarker's clinical use, and also before its use in a clinical trial. We have undertaken a review of five pharmacogenetic biomarker-guided randomised controlled trials (RCTs) and evaluated the evidence used by these trials to justify biomarker inclusion. We assessed and quantified the evidence cited in published rationale papers, or where these were not available, obtained protocols from trial authors. Very different levels of evidence were provided by the trials. We used these observations to write recommendations for future justifications of biomarker use in RCTs and encourage regulatory authorities to write clear guidelines.

Considerations for an In Vitro, Cell-Based Testing Platform for Detection of Drug-Induced Inotropic Effects in Early Drug Development. Part 2: Designing and Fabricating Microsystems for Assaying Cardiac Contractility With Physiological Relevance Using Human iPSC-Cardiomyocytes

Contractility of the myocardium engines the pumping function of the heart and is enabled by the collective contractile activity of its muscle cells: cardiomyocytes. The effects of drugs on the contractility of human cardiomyocytes in vitro can provide mechanistic insight that can support the prediction of clinical cardiac drug effects early in drug development. Cardiomyocytes differentiated from human-induced pluripotent stem cells have high potential for overcoming the current limitations of contractility assays because they attach easily to extracellular materials and last long in culture, while having human- and patient-specific properties. Under these conditions, contractility measurements can be non-destructive and minimally invasive, which allow assaying sub-chronic effects of drugs. For this purpose, the function of cardiomyocytes in vitro must reflect physiological settings, which is not observed in cultured cardiomyocytes derived from induced pluripotent stem cells because of the fetal-like properties of their contractile machinery. Primary cardiomyocytes or tissues of human origin fully represent physiological cellular properties, but are not easily available, do not last long in culture, and do not attach easily to force sensors or mechanical actuators. Microengineered cellular systems with a more mature contractile function have been developed in the last 5 years to overcome this limitation of stem cell-derived cardiomyocytes, while simultaneously measuring contractile endpoints with integrated force sensors/actuators and image-based techniques. Known effects of engineered microenvironments on the maturity of cardiomyocyte contractility have also been discovered in the development of these systems. Based on these discoveries, we review here design criteria of microengineered platforms of cardiomyocytes derived from pluripotent stem cells for measuring contractility with higher physiological relevance. These criteria involve the use of electromechanical, chemical and morphological cues, co-culture of different cell types, and three-dimensional cellular microenvironments. We further discuss the use and the current challenges for developing and improving these novel technologies for predicting clinical effects of drugs based on contractility measurements with cardiomyocytes differentiated from induced pluripotent stem cells. Future research should establish contexts of use in drug development for novel contractility assays with stem cell-derived cardiomyocytes.

Conceptual, Regulatory and Strategic Imperatives in the Early Days of EEG-Based Biomarker Validation for Neurodevelopmental Disabilities

Biological treatment development for syndromal neuropsychiatric conditions such as autism has seen slow progress for decades. Speeding drug discovery may result from the judicious development and application of biomarker measures of brain function to select patients for clinical trials, to confirm target engagement and to optimize drug dose. For neurodevelopmental disorders, electrophysiology (EEG) offers considerable promise because of its ability to monitor brain activity with high temporal resolution and its more ready application for pediatric populations relative to MRI. Here, we discuss conceptual/definitional issues related to biomarker development, discuss practical implementation issues, and suggest preliminary guidelines for validating EEG approaches as biomarkers with a context of use in neurodevelopmental disorder drug development.

Biomarkers as drug development tools: discovery, validation, qualification and use

The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

[Determining the risk of dementia in Parkinson's disease: possibilities and perspectives]

Dementia in Parkinson's disease (D-PD) worsens the course of PD, and it is associated with a decrease in the quality of life of patients and caregivers, as well as with elevated costs for patient care, and, as a consequence, leads to a significant cost increase in the health management. Early detection of the risk of dementia in patients with PD is one of the challenges of modern clinical neurology. Various methods for the detection of morphologic and functional changes associated with D-PD risk (prognostic biomarkers) were suggested. The aim of this article is a brief review of current achievements in the search for and evaluation of the effectiveness of such biomarkers. The review included the following methods: clinical examination, neuroimaging, examination of biological fluids, genetic analysis, neurophysiological methods and combined methods. Biomarkers of D-PD can contribute to optimization of the selection of pharmacological or non-pharmacological methods of preventing cognitive impairment at early stages of PD, and, therefore, to potential improvement of the overall clinical outcomes.

Assay validation and clinical performance of chronic inflammatory and chemokine biomarkers of NASH fibrosis

Nonalcoholic steatohepatitis (NASH) is a chronic liver disease that can lead to cirrhosis, liver transplant, and even hepatocellular carcinoma. While liver biopsy remains the reference standard for disease diagnosis, analytical and clinical development of non-invasive soluble biomarkers of NASH are of great importance to advance the field. To this end, we performed analytical and clinical validation on a series of pro-inflammatory cytokines and chemokines implicated hepatic inflammation; IL-6, CRP, TNFα, MCP-1, MIP-1β, eotaxin, VCAM-1. Biomarker assays were validated for accuracy and precision. Clinical performance was evaluated in a random sample of 52 patients with biopsy-proven NAFLD/NASH. Patients were categorized into three groups according to their fibrosis stage; advanced (F3-F4), mild (F1-2) and no (F0) fibrosis. Serum IL-6 was increased in patients with advanced fibrosis (2.71 pg/mL; 1.26 pg/mL; 1.39 pg/mL p<0.01) compared to patients with mild or no fibrosis respectively. While, there was no significant difference noted in CRP, TNFα, MCP-1, MIP-1β, eotaxin among the three groups, VCAM-1 levels were increased by 55% (p<0.01) and 40% (p<0.05) in the advanced cohort compared to the mild and no fibrosis groups respectively. VCAM-1 also displayed good clinical performance as a biomarker of advanced fibrosis with an area under the receiver operating curve of 0.87. The VCAM-1 assay demonstrated robust accuracy and precision, and VCAM-1 outperformed IL-6, CRP, TNFα, and the chemokines MCP-1, MIP-1β, and eotaxin as a biomarker of advanced fibrosis in NASH. Addition of biomarkers such as IL-6 and VCAM-1 to panels may yield increased sensitivity and specificity for staging of NASH.

Biomarkers of cavernous angioma with symptomatic hemorrhage

BACKGROUNDCerebral cavernous angiomas (CAs) with a symptomatic hemorrhage (CASH) have a high risk of recurrent hemorrhage and serious morbidity.METHODSEighteen plasma molecules with mechanistic roles in CA pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as that minimizing the Akaike information criterion and validated using machine learning, and was compared with the prognostic CASH biomarker predicting bleeding in the subsequent year. Biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the lesional neurovascular unit (NVU) transcriptome and in plasma miRNAs from CASH and non-CASH patients.RESULTSThe diagnostic CASH biomarker included a weighted combination of soluble CD14 (sCD14), VEGF, C-reactive protein (CRP), and IL-10 distinguishing CASH patients with 76% sensitivity and 80% specificity (P = 0.0003). The prognostic CASH biomarker (sCD14, VEGF, IL-1β, and sROBO-4) was confirmed to predict a bleed in the subsequent year with 83% sensitivity and 93% specificity (P = 0.001). Genes associated with diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen plasma miRNAs were differentially expressed between CASH and non-CASH patients.CONCLUSIONShared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA are mechanistically linked to lesional transcriptome and miRNA. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.FUNDINGNIH, William and Judith Davis Fund in Neurovascular Surgery Research, Be Brave for Life Foundation, Safadi Translational Fellowship, Pritzker School of Medicine, and Sigrid Jusélius Foundation.

Pharmacodynamic Drug-Drug Interactions

Pharmacodynamic drug-drug interactions (DDIs) occur when the pharmacological effect of one drug is altered by that of another drug in a combination regimen. DDIs often are classified as synergistic, additive, or antagonistic in nature, albeit these terms are frequently misused. Within a complex pathophysiological system, the mechanism of interaction may occur at the same target or through alternate pathways. Quantitative evaluation of pharmacodynamic DDIs by employing modeling and simulation approaches is needed to identify and optimize safe and effective combination therapy regimens. This review investigates the opportunities and challenges in pharmacodynamic DDI studies and highlights examples of quantitative methods for evaluating pharmacodynamic DDIs, with a particular emphasis on the use of mechanism-based modeling and simulation in DDI studies. Advancements in both experimental and computational techniques will enable the application of better, model-informed assessments of pharmacodynamic DDIs in drug discovery, development, and therapeutics.

Multicentre assessment of motor and sensory evoked potentials in multiple sclerosis: reliability and implications for clinical trials

Background

Motor and sensory evoked potentials (EP) are potential candidate biomarkers for clinical trials in multiple sclerosis.

Objective

To determine test -retest reliability of motor EP (MEP) and sensory EP (SEP) and associated EP-scores in patients with multiple sclerosis.

Methods

In three centres, 16 relapsing and five progressive multiple sclerosis patients had MEPs and SEPs 1-29 days apart. Five neurophysiologists independently marked latencies by central reading. By variance component analysis, we estimated the critical difference (absolute reliability) for cross-sectional group comparison, comparison of longitudinal group changes, within-subject minimal detectable change and defined within-subject improvement.

Results

Cortical SEP responses and cortico-muscular MEP latencies were more reliable than central conduction times. For comparison of 20 subjects per arm, cross-sectional group difference ranged from 0.7 to 3.9 ms and 1.1 to 1.7, group difference in longitudinal changes from 0.4 to 1.8 ms and 0.36 to 0.62, within-subject minimal detectable change from 1.2 to 5.8 ms and 1.2 to 2.0, within-subject improvement from 0.8 to 3.8ms and 0.8 to 1.3, for single EP modalities and EP scores, respectively.

Conclusions

Multicentre EP assessment with central EP reading is feasible and reliable. The critical difference is reasonably low to detect significant group changes and to define responders. The results support the concept of using EP and EP-scores as candidate response biomarkers for quantification of disease progression and for studying remyelination in multiple sclerosis.

Proposed study designs for approval based on a surrogate endpoint and a post-marketing confirmatory study under FDA's accelerated approval regulations for disease modifying osteoarthritis drugs

In 1992, the Food and Drug Administration (FDA) instituted the accelerated approval regulations that allow drugs or biologics for serious conditions that fill an unmet medical need to be approved on the basis of a surrogate endpoint or an intermediate clinical endpoint. The current definition of a serious condition includes chronic disabling conditions, such as osteoarthritis (OA), and thereby provides expanded opportunities for the use of biomarkers for regulatory approval of drugs for OA. The use of surrogates or intermediate clinical endpoints for initial regulatory approval of a drug or biologic requires confirmation in a post-marketing study of a drug effect on a clinically relevant outcome, such as on how a patient feels, functions or survives. Current FDA guidance requires that the post-marketing approval (PMA) study be ongoing during the time of initial drug approval. This white paper arose out of the need to brainstorm trial designs that might be suitable for PMA of drugs initially approved, on the basis of a surrogate or intermediate clinical endpoint, for treatment of OA to alter disease progression, abnormal function or pathological changes in the morphology of the joint. In this white paper we define the concept and regulations regarding accelerated approval and propose two major study design scenarios for PMA trials in OA. The long-term goal is to discuss and refine these designs in consultation with regulatory agencies in order to facilitate development of drugs to fill the large unmet need in OA.

Summary of the Second Annual BMT CTN Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling

The second annual Blood and Marrow Transplant Clinical Trials Network (BMT CTN) Myeloma Intergroup Workshop on Minimal Residual Disease and Immune Profiling was convened on December 7, 2017, at the American Society of Hematology (ASH) meeting. During this workshop, investigators from around the world presented their latest research involving assessment of minimal residual disease (MRD) and immune profiling (IP) in myeloma. This document summarizes the workshop presentations as well as relevant ASH abstracts and focuses on the regulatory issues involved in the integration of MRD and IP assessment in clinical trial design and practice.

Should Overall Survival Remain an Endpoint for Multiple Myeloma Trials?

PURPOSE OF REVIEW

While the traditional gold standard for demonstrating clinical benefit of a therapy has been to show prolongation of overall survival (OS), there are multiple factors which can hinder the use of OS as a primary endpoint in randomized clinical trials (RCTs). Here, we analyze recent myeloma RCTs and evaluate the issues relevant to current and future myeloma RCT design.

RECENT FINDINGS

A review of recent phase III RCTs that led to approval of new agents/combinations reveals that none were designed with OS as the primary endpoint, but instead utilized time to progression (TTP) or progression-free survival (PFS). These studies illuminate the inherent difficulties of designing trials with the primary endpoint of OS/PFS in a disease characterized by increasingly prolonged survival times, availability of effective salvage therapies, and competing events such as co-morbid conditions. Alternative primary endpoints other than OS or PFS need to be developed for future myeloma RCTs. Validated surrogate endpoints with novel clinical trial designs will help improve the feasibility of conducting comparative clinical trials in a timely manner.

The Qualification of an Enrichment Biomarker for Clinical Trials Targeting Early Stages of Parkinson's Disease

As therapeutic trials target early stages of Parkinson's disease (PD), appropriate patient selection based purely on clinical criteria poses significant challenges. Members of the Critical Path for Parkinson's Consortium formally submitted documentation to the European Medicines Agency (EMA) supporting the use of Dopamine Transporter (DAT) neuroimaging in early PD. Regulatory documents included a comprehensive literature review, a proposed analysis plan of both observational and clinical trial data, and an assessment of biomarker reproducibility and reliability. The research plan included longitudinal analysis of the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) and the Parkinson's Progression Markers Initiative (PPMI) study to estimate the degree of enrichment achieved and impact on future trials in subjects with early motor PD. The presence of reduced striatal DAT binding based on visual reads of single photon emission tomography (SPECT) scans in early motor PD subjects was an independent predictor of faster decline in UPDRS Parts II and III as compared to subjects with scans without evidence of dopaminergic deficit (SWEDD) over 24 months. The EMA issued in 2018 a full Qualification Opinion for the use of DAT as an enrichment biomarker in PD trials targeting subjects with early motor symptoms. Exclusion of SWEDD subjects in future clinical trials targeting early motor PD subjects aims to enrich clinical trial populations with idiopathic PD patients, improve statistical power, and exclude subjects who are unlikely to progress clinically from being exposed to novel test therapeutics.

Biological and Clinical Markers in Panic Disorder

OBJECTIVE

Classifying mental disorders on the basis of objective makers might clarify their aetiology, help in making the diagnosis, identify "at risk" individuals, determine the severity of mental illness, and predict the course of the disorder. This study aims to review biological and clinical markers of panic disorder (PD).

METHODS

A computerized search was carried out in PubMed and Science Direct using the key words: "marker/biomarker/clinical marker/neurobiology/staging" combined using Boolean AND operator with "panic." In addition, the reference lists from existing reviews and from the articles retrieved were inspected. Only English language papers published in peer-reviewed journals were included.

RESULTS

Structural changes in the amygdala, hippocampus, cerebral blood level in the left occipital cortex, serotonin 5-TH and noradrenergic systems activation, aberrant respiratory regulation, hearth rate variability, blood cells and peripheral blood stem cells, hypothalamic-pituitary-adrenal axis dysregulation were identified as potential candidate biomarkers of PD. Staging was identified as clinical marker of PD. According to the staging model, PD is described as follows: prodromal phase (stage 1); acute phase (stage 2); panic attacks (stage 3); chronic phase (stage 4).

CONCLUSION

The clinical utility, sensitivity, specificity, and the predictive value of biomarkers for PD is still questionable. The staging model of PD might be a valid susceptibility, diagnostic, prognostic, and predictive marker of PD. A possible longitudinal model of biological and clinical markers of PD is proposed.

The Role of Biomarkers in Alzheimer's Disease Drug Development

Biomarkers have a key role in Alzheimer's disease (AD) drug development. Biomarkers can assist in diagnosis, demonstrate target engagement, support disease modification, and monitor for safety. The amyloid (A), tau (T), neurodegeneration (N) Research Framework emphasizes brain imaging and CSF measures relevant to disease diagnosis and staging and can be applied to drug development and clinical trials. Demonstration of target engagement in Phase 2 is critical before advancing a treatment candidate to Phase 3. Trials with biomarker outcomes are shorter and smaller than those required to show clinical benefit and are important to understanding the biological impact of an agent and inform go/no-go decisions. Companion diagnostics are required for safe and effective use of treatments and may emerge in AD drug development programs. Complementary biomarkers inform the use of therapies but are not mandatory for use. Biomarkers promise to de-risk AD drug development, attract sponsors to AD research, and accelerate getting new drugs to those with or at risk for AD.

Systematic review: predictive biomarkers of therapeutic response in inflammatory bowel disease-personalised medicine in its infancy

BACKGROUND

Inflammatory bowel disease (IBD) is characterised by substantial heterogeneity in treatment response. With an expanding number of therapeutic agents, identifying optimal treatment at the patient level remains a major challenge.

AIM

To systematically review the available literature on predictive biomarkers of therapeutic response in IBD.

METHODS

An electronic literature search was performed on 30 January 2018 using MEDLINE, EMBASE and the Cochrane Library. Retrospective, prospective, uncontrolled and controlled studies reporting on biomarkers predicting therapeutic response in paediatric and adult IBD populations were eligible for inclusion. The methodological quality of the included studies was assessed using the QUIPS tool. Due to anticipated heterogeneity and limited data, a qualitative, rather than quantitative, assessment was planned.

RESULTS

Of the 10 638 citations identified, 92 articles met the inclusion criteria. Several potential DNA, mRNA and protein markers were evaluated as predictive biomarkers. Most studies focused on predicting response to anti-TNF agents. Substantial between-study heterogeneity was identified with respect to both the biomarkers studied and the definition of response. None of the included studies received a low risk of bias rating for all six domains. Currently, none of the biomarkers is sufficiently predictive for clinical use.

CONCLUSIONS

The search for predictive biomarkers is still in its infancy and current evidence is limited. Future research efforts should take into account the high patient heterogeneity within prospective trials with objective response assessment. Predictive models will most likely comprise a combination of several molecular markers from integrated omics-levels and clinical characteristics.

Assessing Response to Therapy for Nontuberculous Mycobacterial Lung Disease: Quo Vadis?

Assessing progression of disease or response to treatment remains a major challenge in the clinical management of nontuberculous mycobacterial (NTM) infections of the lungs. Serial assessments of validated measures of treatment response address whether the current therapeutic approach is on track toward clinical cure, which remains a fundamental question for clinicians and patients during the course of NTM disease treatment. The 2015 NTM Research Consortium Workshop, which included a patient advisory panel, identified treatment response biomarkers as a priority area for investigation. Limited progress in addressing this challenge also hampers drug development efforts. The Biomarker Qualification Program at the FDA supports the use of a validated treatment response biomarker across multiple drug development programs. Current approaches in clinical practice include microbiologic and radiographic monitoring, along with symptomatic and quality-of-life assessments. Blood-based monitoring, including assessments of humoral and cell-mediated NTM-driven immune responses, remain under investigation. Alignment of data collection schemes in prospective multicenter studies, including the support of biosample repositories, will support identification of treatment response biomarkers under standard-of-care and investigational therapeutic strategies. In this review, we outline the role of treatment monitoring biomarkers in both clinical practice and drug development frameworks.

Elevated circulating MMP-9 is linked to increased COPD exacerbation risk in SPIROMICS and COPDGene

BACKGROUND

Matrix metalloprotease 9 (MMP-9) is associated with inflammation and lung remodeling in chronic obstructive pulmonary disease (COPD). We hypothesized that elevated circulating MMP-9 represents a potentially novel biomarker that identifies a subset of individuals with COPD with an inflammatory phenotype who are at increased risk for acute exacerbation (AECOPD).

METHODS

We analyzed Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene) cohorts for which baseline and prospective data were available. Elevated MMP-9 was defined based on >95th percentile plasma values from control (non-COPD) sample in SPIROMICS. COPD subjects were classified as having elevated or nonelevated MMP-9. Logistic, Poisson, and Kaplan-Meier analyses were used to identify associations with prospective AECOPD in both cohorts.

RESULTS

Elevated MMP-9 was present in 95/1,053 (9%) of SPIROMICS and 41/140 (29%) of COPDGene participants with COPD. COPD subjects with elevated MMP-9 had a 13%-16% increased absolute risk for AECOPD and a higher median (interquartile range; IQR) annual AECOPD rate (0.33 [0-0.74] versus 0 [0-0.80] events/year and 0.9 [0.5-2] versus 0.5 [0-1.4] events/year for SPIROMICS and COPDGene, respectively). In adjusted models within each cohort, elevated MMP-9 was associated with increased odds (odds ratio [OR], 1.71; 95%CI, 1.00-2.90; and OR, 3.03; 95%CI, 1.02-9.01), frequency (incidence rate ratio [IRR], 1.45; 95%CI, 1.23-1.7; and IRR, 1.24; 95%CI, 1.03-1.49), and shorter time-to-first AECOPD (21.7 versus 31.7 months and 14 versus 21 months) in SPIROMICS and COPDGene, respectively.

CONCLUSIONS

Elevated MMP-9 was independently associated with AECOPD risk in 2 well-characterized COPD cohorts. These findings provide evidence for MMP-9 as a prognostic biomarker and potential therapeutic target in COPD.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01969344 (SPIROMICS) and NCT00608764 (COPDGene).

FUNDING

This work was funded by K08 HL123940 to JMW; R01HL124233 to PJC; Merit Review I01 CX000911 to JLC; R01 (R01HL102371, R01HL126596) and VA Merit (I01BX001756) to AG. SPIROMICS (Subpopulations and Intermediate Outcomes in COPD Study) is funded by contracts from the NHLBI (HHSN268200900013C, HHSN268200900014C,HHSN268200900015C HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, and HHSN268200900020C) and a grant from the NIH/NHLBI (U01 HL137880), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals Inc.; Chiesi Farmaceutici; Forest Research Institute Inc.; GlaxoSmithKline; Grifols Therapeutics Inc.; Ikaria Inc.; Novartis Pharmaceuticals Corporation; Nycomed GmbH; ProterixBio; Regeneron Pharmaceuticals Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; and Theravance Biopharma and Mylan. COPDGene is funded by the NHLBI (R01 HL089897 and R01 HL089856) and by the COPD Foundation through contributions made to an Industry Advisory Board composed of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion.

What evidence do we need for biomarker qualification?

Biomarkers can facilitate all aspects of the drug development process. However, biomarker qualification-the use of a biomarker that is accepted by the U.S. Food and Drug Administration-needs a clear, predictable process. We describe a multistakeholder effort including government, industry, and academia that proposes a framework for defining the amount of evidence needed for biomarker qualification. This framework is intended for broad applications across multiple biomarker categories and uses.

Precision medicine in asthma: linking phenotypes to targeted treatments

PURPOSE OF REVIEW

Asthma is a heterogeneous disease consisting of different phenotypes that are driven by different mechanistic pathways. The purpose of this review is to emphasize the important role of precision medicine in asthma management.

RECENT FINDINGS

Despite asthma heterogeneity, the approach to management has been on the basis of disease severity, with the most severe patients reserved for the maximum treatments with corticosteroids and bronchodilators. At the severe end, the recent availability of biologic therapies in the form of anti-IgE (omalizumab) and anti-IL5 therapies (mepolizumab and reslizumab) has driven the adaptation of precision medicine. These therapies are reserved for severe asthma with defined either allergic or eosinophilic background, respectively.

SUMMARY

Unbiased definition of phenotypes or endotypes (which are phenotypes defined by mechanisms) is an important step towards the use of precision medicine in asthma. Although T2-high asthma has been defined with targets becoming available for treating allergic or eosinophilic asthma, the definition of non-T2 phenotypes remains a priority. Precision medicine is also dependent on the definition of biomarkers that can help differentiate between these phenotypes and pinpoint patients suitable for specific-targeted therapies. Thus, precision medicine links phenotypes (endotypes) to targeted treatments for better outcomes.

Blood-Based Protein Biomarkers for the Management of Traumatic Brain Injuries in Adults Presenting to Emergency Departments with Mild Brain Injury: A Living Systematic Review and Meta-Analysis

Accurate diagnosis of traumatic brain injury (TBI) is critical to effective management and intervention, but can be challenging in patients with mild TBI. A substantial number of studies have reported the use of circulating biomarkers as signatures for TBI, capable of improving diagnostic accuracy and clinical decision making beyond current practice standards. We performed a systematic review and meta-analysis to comprehensively and critically evaluate the existing body of evidence for the use of blood protein biomarkers (S100 calcium binding protein B [S100B], glial fibrillary acidic protein [GFAP], neuron specific enolase [NSE], ubiquitin C-terminal hydrolase-L1 [UCH-L1]. tau, and neurofilament proteins) for diagnosis of intracranial lesions on CT following mild TBI. Effects of potential confounding factors and differential diagnostic performance of the included markers were explored. Further, appropriateness of study design, analysis, quality, and demonstration of clinical utility were assessed. Studies published up to October 2016 were identified through searches of MEDLINE^®, Embase, EBM Reviews, the Cochrane Library, World Health Organization (WHO), International Clinical Trials Registry Platform (ICTRP), and clinicaltrials.gov. Following screening of the identified articles, 26 were selected as relevant. We found that measurement of S100B can help informed decision making in the emergency department, possibly reducing resource use; however, there is insufficient evidence that any of the other markers is ready for clinical application. Our work pointed out serious problems in the design, analysis, and reporting of many of the studies, and identified substantial heterogeneity and research gaps. These findings emphasize the importance of methodologically rigorous studies focused on a biomarker's intended use, and defining standardized, validated, and reproducible approaches. The living nature of this systematic review, which will summarize key updated information as it becomes available, can inform and guide future implementation of biomarkers in the clinical arena.

Wearable Devices in Clinical Trials: Hype and Hypothesis

The development of innovative wearable technologies has raised great interest in new means of data collection in healthcare and biopharmaceutical research and development. Multiple applications for wearables have been identified in a number of therapeutic areas; however, researchers face many challenges in the clinic, including scientific methodology as well as regulatory, legal, and operational hurdles. To facilitate further evaluation and adoption of these technologies, we highlight methodological and logistical considerations for implementation in clinical trials, including key elements of analytical and clinical validation in the specific context of use (COU). Additionally, we provide an assessment of the maturity of the field and successful examples of recent clinical experiments.

Complement-binding anti-HLA antibodies are independent predictors of response to treatment in kidney recipients with antibody-mediated rejection

A major hurdle to improving clinical care in the field of kidney transplantation is the lack of biomarkers of the response to antibody-mediated rejection (ABMR) treatment. To discover these we investigated the value of complement-binding donor-specific anti-HLA antibodies (DSAs) for evaluating the response to treatment. The study encompassed a prospective cohort of 139 kidney recipients with ABMR receiving the standard of care treatment, including plasma exchange, intravenous immunoglobulin and rituximab. Patients were systematically assessed at the time of diagnosis and three months after treatment initiation for clinical and allograft histological characteristics and anti-HLA DSAs, including their C1q-binding ability. After adjusting for clinical and histological parameters, post-treatment C1q-binding anti-HLA DSA was an independent and significant determinant of allograft loss (adjusted hazard ratio 2.57 (95% confidence interval 1.29-5.12). In 101 patients without post-treatment C1q-binding anti-HLA DSA there was a significantly improved glomerular filtration rate with significantly reduced glomerulitis, peritubular capillaritis, interstitial inflammation, tubulitis, C4d deposition, and endarteritis compared with 38 patients with posttreatment C1q-binding anti-HLA DSA. A conditional inference tree model identified five prognostic groups at the time of post-treatment evaluation based on glomerular filtration rate, presence of cg lesion and C1q-binding anti-HLA DSA (cross-validated accuracy: 0.77). Thus, circulating complement-binding anti-HLA DSAs are strong and independent predictors of allograft outcome after standard of care treatment in kidney recipients with ABMR.

A Clinician's Guide to PTSD Biomarkers and Their Potential Future Use

No clinically validated biomarkers have yet been found to assist in the diagnosis and treatment of posttraumatic stress disorder (PTSD). Innovation in clinical trial design, however, has led to the study of biomarkers as part of testing new medications and psychotherapies. There may soon be viable biomarkers to assist in diagnosis of PTSD and prediction of illness trajectory, severity, and functional outcomes; subtyping; and treatment selection. Processes for the identification and validation of biomarker findings are complex, involving several stages of clinical testing before use. The authors provide an overview of issues regarding the clinical use of PTSD biomarkers and examine a set of genetic, epigenetic, and other blood-based markers along with physiological markers currently proposed as candidate tests for PTSD. Studies that have identified candidate biomarkers with relevance to treatment selection in PTSD are discussed as a promising area of research that may lead to changes in clinical practice.