Multiple Sclerosis Clinical Trials Research Articles

Comparative Effectiveness of Natalizumab, Fingolimod, and Injectable Therapies in Pediatric-Onset Multiple Sclerosis: A Registry-Based Study.

Patients with pediatric-onset multiple sclerosis (POMS) typically experience higher levels of inflammation with more frequent relapses, and though patients with POMS usually recover from relapses better than adults, patients with POMS reach irreversible disability at a younger age than adult-onset patients. There have been few randomized, placebo-controlled clinical trials of multiple sclerosis (MS) disease-modifying therapies (DMTs) in patients with POMS, and most available data are based on observational studies of off-label use of DMTs approved for adults. We assessed the effectiveness of natalizumab compared with fingolimod using injectable platform therapies as a reference in pediatric patients in the global MSBase registry. This retrospective study included patients with POMS who initiated treatment with an injectable DMT, natalizumab, or fingolimod between January 1, 2006, and May 3, 2021. Patients were matched using inverse probability treatment weighting. The primary outcome was time to first relapse from index therapy initiation. Secondary study outcomes included annualized relapse rate; proportions of relapse-free patients at 1, 2, and 5 years; time to treatment discontinuation; and times to 24-week confirmed disability worsening and confirmed disability improvement. A total of 1,218 patients with POMS were included in this analysis. Patients treated with fingolimod had a significantly lower risk of relapse than patients treated with injectable DMTs (hazard ratio [HR], 0.49; 95% confidence interval [CI], 0.29-0.83; p = 0.008). After adjustment for prior DMT experience in the unmatched sample, patients treated with natalizumab had a significantly lower risk of relapse than patients treated either with injectable DMTs (HR, 0.15; 95% CI 0.07-0.31; p < 0.001) or fingolimod (HR, 0.37; 95% CI 0.14-1.00; p = 0.049). The adjusted secondary study outcomes were generally consistent with the primary outcome or with previous observations. The findings in the inverse probability treatment weighting-adjusted patient populations were confirmed in multiple sensitivity analyses. Our analyses of relapse risk suggest that natalizumab is more effective than fingolimod in the control of relapses in this population with high rates of new inflammatory activity, consistent with previous studies of natalizumab and fingolimod in adult-onset patients and POMS. In addition, both fingolimod and natalizumab were more effective than first-line injectable therapies. This study provides Class II evidence that patients with POMS treated with natalizumab had a lower risk of relapse than those with fingolimod.

Investigating the Prevalence of Comorbidity in Multiple Sclerosis Clinical Trial Populations.

Comorbidity is common in multiple sclerosis (MS) with the most prevalent conditions being depression, anxiety, hypertension, and hyperlipidemia. Limited information regarding the representation of comorbidity status is available from phase III clinical trials in MS leading to concern about the potential underrepresentation of individuals with comorbidity in clinical trials. The objective was to estimate the prevalence of comorbidities in MS clinical trial populations. Individual-level data from multiple sponsors were requested for a 2-stage meta-analysis of phase III clinical trials of MS disease-modifying therapies. To ensure consistency of our approach across trials, we followed the Maelstrom retrospective harmonization guidelines. Chronic comorbidities at clinical trial enrollment recommended by the International Advisory Committee on Clinical Trials in MS were considered (depression, anxiety, hypertension, hyperlipidemia, migraine, diabetes, chronic lung disease). Additional comorbidities were also classified. Classification was based on medical history data. Individual comorbidities were summed and categorized as 0, 1, 2, or ≥3. We report the pooled prevalence (95% confidence interval [95% CI]) of comorbidity. The pooled prevalence and prevalence ratios across age, sex, race, disability level, and treatment were also reported. Heterogeneity was assessed using the I2 statistic. Seventeen trials involving 17,926 participants were included. Fourteen trials enrolled participants with relapsing MS (RMS) while 3 enrolled participants with progressive MS (PMS). The distributions of sex, age, and disability level were generally consistent within RMS and PMS trials. When pooled, almost half of trial participants (46.5%) had ≥1 comorbidity (1: 25.0%, 95% CI 23.0-27.0, I2 = 89.9; 2: 11.4% [9.3-14.0], I2 = 96.3; ≥3: 6.0% [4.2-8.4], I2 = 97.7). Depression (16.45% [12.96-20.88], I2 = 98.3) was the most prevalent comorbidity reported, followed by hypertension (10.16% [8.61-11.98], I2 = 93.2). Heterogeneity was high across trials. Older age and female participants were associated with increased number of comorbidities. Older individuals and male participants had a higher prevalence of hyperlipidemia, while older individuals and female participants had a higher prevalence of depression and anxiety. Individuals with comorbidities are included in clinical trials, although they may still be underrepresented compared with the general MS population. Given the comorbidity prevalence in the trial populations and studies suggesting an association of comorbidities with disease activity, comorbidity may influence outcomes in clinical trials.

Clinical characterization of long-term multiple sclerosis (COLuMbus) patients in Argentina: A cross-sectional non-interventional study

BackgroundMost Multiple Sclerosis (MS) clinical trials fail to assess the long-term effects of disease-modifying therapies (DMT) or disability. MethodsCOLuMbus was a single-visit, cross-sectional study in Argentina in adult patients with ≥10 years of MS since first diagnosis. The primary endpoint was to determine patient disability using the Expanded Disability Status Scale (EDSS). The secondary endpoints were to evaluate the distribution of diagnoses between relapsing-remitting MS (RRMS) and secondary progressive MS (SPMS), patient demographics, disease history, and the risk of disability progression. The relationship between baseline characteristics and the current disability state and the risk of disability progression was assessed. ResultsOut of the 210 patients included, 76.7 % had a diagnosis of RRMS and 23.3 % had been diagnosed with SPMS, with a mean disease duration of 17.9 years and 20.5 years, respectively. The mean delay in the initial MS diagnosis was 2.6 years for the RRMS subgroup and 2.8 years for the SPMS subgroups. At the time of cut-off (28May2020), 90.1 % (RRMS) and 75.5 % (SPMS) of patients were receiving a DMT, with a mean of 1.5 and 2.0 prior DMTs, respectively. The median EDSS scores were 2.5 (RRMS) and 6.5 (SPMS). In the RRMS and SPMS subgroups, 23 % and 95.9 % of patients were at high risk of disability, respectively; the time since first diagnosis showed a significant correlation with the degree of disability. ConclusionsThis is the first local real-world study in patients with long-term MS that highlights the importance of recognizing early disease progression to treat the disease on time and delay disability.

Socioeconomic and Regional Disparities in Industry-Sponsored Clinical Trials in Multiple Sclerosis

This cross-sectional study examines the geographical and socioeconomic factors associated with trial distribution and outcome of treatment for multiple sclerosis (MS).

An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training

Large medical imaging data sets are becoming increasingly available. A common challenge in these data sets is to ensure that each sample meets minimum quality requirements devoid of significant artefacts. Despite a wide range of existing automatic methods having been developed to identify imperfections and artefacts in medical imaging, they mostly rely on data-hungry methods. In particular, the scarcity of artefact-containing scans available for training has been a major obstacle in the development and implementation of machine learning in clinical research. To tackle this problem, we propose a novel framework having four main components: (1) a set of artefact generators inspired by magnetic resonance physics to corrupt brain MRI scans and augment a training dataset, (2) a set of abstract and engineered features to represent images compactly, (3) a feature selection process that depends on the class of artefact to improve classification performance, and (4) a set of Support Vector Machine (SVM) classifiers trained to identify artefacts. Our novel contributions are threefold: first, we use the novel physics-based artefact generators to generate synthetic brain MRI scans with controlled artefacts as a data augmentation technique. This will avoid the labour-intensive collection and labelling process of scans with rare artefacts. Second, we propose a large pool of abstract and engineered image features developed to identify 9 different artefacts for structural MRI. Finally, we use an artefact-based feature selection block that, for each class of artefacts, finds the set of features that provide the best classification performance. We performed validation experiments on a large data set of scans with artificially-generated artefacts, and in a multiple sclerosis clinical trial where real artefacts were identified by experts, showing that the proposed pipeline outperforms traditional methods. In particular, our data augmentation increases performance by up to 12.5 percentage points on the accuracy, F1, F2, precision and recall. At the same time, the computation cost of our pipeline remains low –less than a second to process a single scan– with the potential for real-time deployment. Our artefact simulators obtained using adversarial learning enable the training of a quality control system for brain MRI that otherwise would have required a much larger number of scans in both supervised and unsupervised settings. We believe that systems for quality control will enable a wide range of high-throughput clinical applications based on the use of automatic image-processing pipelines.

Can neurofilament lightchain as endpoint in Phase 2 derisk clinical disability worsening in Phase 3 in multiple sclerosis?

BackgroundNeurofilament lightchain has been proposed as a Phase 2 endpoint in clinical trials for multiple sclerosis. We evaluated via simulations the extent to which a positive Phase 2 trial would derisk a Phase 3 trial where the primary endpoint is time to confirmed clinical disability worsening. MethodsUsing a prior distribution of the treatment effect on neurofilament lightchain and a model linking it with clinical disability worsening constructed using the FREEDOMS trial in RRMS patients, the probability of success of two randomized controlled Phase 2 and Phase 3 trials were computed for different scenarios. ResultsThe strength of the correlation between both treatment effects and the success criteria of the Phase 2 trial impact the ability of the Phase 2 to derisk Phase 3. Being more stringent with the success criteria in Phase 2 can increase the Phase 3 PoS by more than 20% after a positive Phase 2 study. Increasing the sample size of the Phase 2 has no substantial impact on the derisking. ConclusionUnder some assumptions a positive Phase 2 trial with neurofilament lightchain as primary endpoint can to a certain extent derisk a Phase 3 trial with clinical disability worsening as primary endpoint.

Is it ethical to use teriflunomide as an active comparator in phase 3 trials?

Ethical concerns have been raised about the practice of using teriflunomide, an oral licensed disease-modifying therapy, as an active comparator in phase 3 multiple sclerosis (MS) trials. The assumption is based on the perceived low efficacy of teriflunomide as judged by its effect on relapses and focal MRI activity. However, when you look beyond focal inflammation, teriflunomide has a robust impact on disability progression and a similar effect to the anti-CD20 monoclonal antibody therapies on slowing down the accelerated brain volume loss associated with MS. Teriflunomide is also more effective when used second or third line. The other classes of disease-modifying therapies have problems with their use as active comparators in clinical trials. Using a non-inferiority or equivalence trial design has its own unique set of regulatory and ethical challenges and is not necessarily a solution. There are also economic, altruistic and pragmatic reasons for continuing to use teriflunomide as an active comparator in MS clinical trials. An online survey indicates that the majority of the MS community feels it is still ethical to randomise subjects to teriflunomide and that procedures can be put in place to protect trial subjects randomised to teriflunomide. Therefore, we still have equipoise, and teriflunomide comparator trials are ethical.

Treatment Effect on Brain Atrophy Correlates with Treatment Effect on Cognition in Multiple Sclerosis.

The purpose of this study was to evaluate the extent to which treatment effect on magnetic resonance imaging (MRI)-derived measures of brain atrophy and focal lesions can mediate, at the trial level, the treatment effect on cognitive outcomes in multiple sclerosis (MS). We collected all published randomized clinical trials in MS lasting at least 2 years and including as end points: active MRI lesions (defined as new/enlarging T2 lesions), brain atrophy (defined as a change in brain volume between month 12 and month 24), and change in cognitive performance (assessed by the Paced Auditory Serial Addition Test [PASAT]). Relative reductions were used to quantify the treatment effect on MRI markers (lesions and atrophy), whereas the standardized mean difference (Hedges g) between baseline and follow-up cognitive assessment was used to quantify the treatment effects on cognition. A linear regression, weighted for trial size, was used to assess the relationship between the treatment effects on MRI markers and cognition. Fourteen trials including more than 8,813 patients with MS were included in the meta-regression. Treatment effect on cognition was strongly associated with the treatment effect on brain atrophy (R2 = 0.79, p < 0.001), but was not correlated with the treatment effect on active MRI lesions (R2 = 0.16, p = 0.14). Results reported here suggest that brain atrophy, a well-established MRI marker in MS clinical trials, can be used as a main outcome for clinical trials with drugs targeting cognitive impairment and neurodegeneration. ANN NEUROL 2023.

Do clinical trials prepare to fail by failing to prepare? An examination of MS trials and recommendations for patient-reported outcome measure selection.

Many clinical trials use patient-reported outcome (PRO) measures, which can influence treatment decision-making, drug approval and label claims. Given that many PRO measure options exist, and there are conceptual and contextual complexities with PRO measurement, we aimed to evaluate how and why specific PRO measures have been selected for pivotal multiple sclerosis (MS) clinical trials. Specifically, we aimed to identify the reasons documented for PRO measure selection in contemporary phase III MS disease-modifying treatment (DMT) clinical trials. We searched for phase III clinical trials of MS DMTs published between 2015 and 2021 and evaluated trial protocols, or primary publications where available, for PRO measure selection information. Specifically, we examined study documents for their clarification of clinical concepts measured, definitions of concepts measured, explanations of which PRO measures were considered, why specific PRO measures were chosen, and trade-offs in PRO measure selection. We identified 1705 abstracts containing 61 unique phase III MS DMT clinical trials. We obtained and examined 27/61 trial protocols. Six protocols were excluded: four contained no mention of PRO measures and two contained redacted sections preventing adequate assessment, leaving 21 protocols for assessment. For the remaining 34 trials (61-27), we retrieved 31 primary publications; 15 primary publications mentioned the use of a PRO measure. None of the 36 clinical trials that mentioned the use of PRO measures (21 protocols and 15 primary publications) documented clear PRO or clinical outcome assessment (COA) measurement strategies, provided clear justifications for PRO selection, or reasons why specific PRO measures were selected when alternatives existed. PRO measure selection for clinical trials is not evidence-based or underpinned by structured systematic approaches. This represents a critical area for study design improvement as PRO measure results directly affect patient care, PRO measurement has conceptual and contextual complexities, and there is a wide range of options when selecting a PRO measure. We recommend trial designers use formal approaches for PRO measure selection to ensure PRO measurement-based decisions are optimised. We provide a simple, logical, five-stage approach for PRO measure selection in clinical trials.

Demographics and baseline disease characteristics of Black and Hispanic patients with multiple sclerosis in the open-label, single-arm, multicenter, phase IV CHIMES trial.

Black/African American patients with multiple sclerosis (BpwMS) and Hispanic/Latino patients with multiple sclerosis (HpwMS), who historically have been underrepresented in multiple sclerosis (MS) clinical trials, exhibit greater disease severity and more rapid disease progression than White patients with MS (WpwMS). The lack of diversity and inclusion in clinical trials, which may be due to barriers at the system, patient and study levels, impacts the ability to effectively assess risks, benefits and treatment responses in a generalized patient population. CHIMES (Characterization of Ocrelizumab in Minorities With Multiple Sclerosis), an open-label, single-arm, multicenter, phase IV study of self-identified BpwMS and HpwMS aged 18-65 years with relapsing MS and an Expanded Disability Status Score (EDSS) of ≤5.5, was developed in collaboration with patients with MS, national advocacy groups and clinical researchers. Patients were enrolled at study centers across the US, including Puerto Rico, and 1 site in Kenya. A total of 182 patients enrolled in CHIMES: 113 (62.1%) were BpwMS, and 69 (37.9%) were HpwMS; the mean (SD) baseline EDSS score was 2.4 (1.4), and 62.6% of patients were treatment naive. Using the pooled non-BpwMS/HpwMS group in the OPERA ocrelizumab trials as a reference population, patients enrolled in CHIMES were younger, had a higher mean body mass and had a greater T2 lesion volume but similar T2 lesion number on MRI. BpwMS and HpwMS have been consistently underrepresented in clinical trials, limiting the understanding of disease biology and response to treatment in this population. Data from the CHIMES study revealed differences in demographics and some baseline disease characteristics and disease burden between BpwMS and HpwMS vs WpwMS. These differences could have an impact when assessing clinical outcomes in BpwMS and HpwMS. NCT04377555.

Treatment of older patients with multiple sclerosis: Results of an International Delphi Survey.

People over age 50-55 have historically been excluded from randomized clinical trials for multiple sclerosis (MS). However, more than half of those living with an MS diagnosis are over 55. Explore the unique considerations of treating older people with MS (PwMS) using an iterative and structured Delphi-based assessment to gather expert opinions. Eight MS neurologists with an interest in older PwMS developed a 2-round survey. Survey respondents were qualified neurologists with ≥3 years' experience, personally responsible for treatment decisions, and treating ≥20 patients per month, of whom ≥10% were ≥50 years old. Consensus was defined as ≥75% agreement on questions with categorical responses or as a mean score ≥4 on questions with numerical responses. In Survey 1, 224 neurologists responded; 180 of these completed Survey 2. Limited consensus was reached with varying levels of agreement on several topics including identification and assessment of older patients; factors relating to treatment decisions including immunosenescence and comorbidities; considerations for high-efficacy treatments; de-escalation or discontinuation of treatment; effects of COVID-19; and unmet needs for treating this population. The results of this Delphi process highlight the need for targeted studies to create guidance for the care of older PwMS.

CancerHERVdb: Human Endogenous Retrovirus (HERV) Expression Database for Human Cancer Accelerates Studies of the Retrovirome and Predictions for HERV-Based Therapies.

In this study, we sought to create a database summarizing the expression of human endogenous retroviruses (HERVs) in various human cancers. HERVs are suitable therapeutic targets due to their abundance in the human genome, overexpression in various malignancies, and involvement in various cancer pathways. We identified articles on HERVs from PubMed and then prescreened and automatically categorized them using the portable document format (PDF) data extractor (PDE) R package. We discovered 196 primary research articles with HERV expression data from cancer tissues or cancer cell lines. HERV RNA and protein expression was reported in brain, breast, cervical, colorectal, endocrine, gastrointestinal, kidney/renal/pelvis, liver, lung, genital, oral cavity, pharynx, ovary, pancreas, prostate, skin, testicular, urinary/bladder, and uterus cancers, leukemias, lymphomas, and myelomas. Additionally, we discovered reports of HERV RNA-only overexpression in soft tissue cancers including heart, thyroid, bone, and joint cancers. The CancerHERVdb database is hosted in the form of interactive visualizations of the expression data and a summary data table at https://erikstricker.shinyapps.io/cancerHERVdb/. The user can filter the findings according to cancer type, HERV family, HERV gene, or a combination thereof and easily export the results with the corresponding reference list. In our report, we provide examples of potential uses of the CancerHERVdb, such as identification of cancers suitable for off-target treatment with the multiple sclerosis-associated retrovirus (MSRV)-Env-targeting antibody GNbAC1 (now named temelimab) currently in phase 2b clinical trials for multiple sclerosis or the discovery of cancers overexpressing HERV-H long terminal repeat-associating 2 (HHLA2), a newly emerging immune checkpoint. In summary, the CancerHERVdb allows cross-study comparisons, encourages data exploration, and informs about potential off-target effects of HERV-targeting treatments. IMPORTANCE Human endogenous retroviruses (HERVs), which in the past have inserted themselves in various regions of the human genome, are to various degrees activated in virtually every cancer type. While a centralized naming system and resources summarizing HERV levels in cancers are lacking, the CancerHERVdb database provides a consolidated resource for cross-study comparisons, data exploration, and targeted searches of HERV activation. The user can access data extracted from hundreds of articles spanning 25 human cancer categories. Therefore, the CancerHERVdb database can aid in the identification of prognostic and risk markers, drivers of cancer, tumor-specific targets, multicancer spanning signals, and targets for immune therapies. Consequently, the CancerHERVdb database is of direct relevance for clinical as well as basic research.

Remyelination in animal models of multiple sclerosis: finding the elusive grail of regeneration.

Remyelination biology and the therapeutic potential of restoring myelin sheaths to prevent neurodegeneration and disability in multiple sclerosis (MS) has made considerable gains over the past decade with many regeneration strategies undergoing tested in MS clinical trials. Animal models used to investigate oligodendroglial responses and regeneration of myelin vary considerably in the mechanism of demyelination, involvement of inflammatory cells, neurodegeneration and capacity for remyelination. The investigation of remyelination in the context of aging and an inflammatory environment are of considerable interest for the potential translation to progressive multiple sclerosis. Here we review how remyelination is assessed in mouse models of demyelination, differences and advantages of these models, therapeutic strategies that have emerged and current pro-remyelination clinical trials.

Real-World Safety and Effectiveness After 5 Years of Dimethyl Fumarate Treatment in Black and Hispanic Patients with Multiple Sclerosis in ESTEEM.

Multiple sclerosis(MS) clinical trials have included low numbers of patients from racial and ethnic minority populations; therefore, it is uncertain whether differences exist in response to disease-modifying therapies. We evaluated the real-world safety and effectiveness of dimethyl fumarate (DMF) treatment over 5years in four patient cohorts: Black, non-Black, Hispanic, and non-Hispanic people with relapsing-remitting MS. ESTEEM is an ongoing, 5-year, multinational, prospective study evaluating the long-term safety and effectiveness of DMF in people with MS. The analysis included patients newly prescribed DMF in routine practice at 393 sites globally. Overall, 5251 patients were analyzed (220 Black, 5031 non-Black; 105 Hispanic, 5146 non-Hispanic). Median (min-max) months of follow-up was 32 (0-72) for Black, 29 (1-77) for Hispanic, and 41 (0-85) for both the non-Black and non-Hispanic populations. In total, 39 (18%) Black and 29 (28%) Hispanic patients reported adverse events leading to treatment discontinuation versus 1126 (22%) non-Black and 1136 (22%) non-Hispanic patients; gastrointestinal disorders were the most common in all subgroups. Median lymphocyte counts decreased by 37% in Black, 40% in non-Black, 10% in Hispanic, and 39% in non-Hispanic patients in the first year, then remained stable and above the lower limit of normal in most patients. Annualized relapse rates (ARRs) (95% confidence intervals) up to 5years were 0.054 (0.038-0.078) for Black, 0.077 (0.072-0.081) for non-Black, 0.069 (0.043-0.112) for Hispanic, and 0.076 (0.072-0.081) for non-Hispanic populations, representing reductions of 91-92% compared with ARR 12months before study entry (all p < 0.0001). The safety profile of DMF in these subgroups was consistent with the overall ESTEEM population. Relapse rates remained low in Black and Hispanic patients, and consistent with non-Black and non-Hispanic patients. These data demonstrate a comparable real-world treatment benefit of DMF in Black and Hispanic patients. ClinicalTrials.gov identifier NCT02047097.

Emerging imaging and liquid biomarkers in multiple sclerosis.

The advent of highly-effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins such as neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies. This article is protected by copyright. All rights reserved.

Real-world annualized relapse rates from contemporary multiple sclerosis clinics in the UK: a retrospective multicentre cohort study.

Annualized relapse rate (ARR) is used as an outcome measure in multiple sclerosis (MS) clinical trials. Previous studies demonstrated that ARR has reduced in placebo groups between 1990 and 2012. This study aimed to estimate real-world ARRs from contemporary MS clinics in the UK, in order to improve the feasibility estimations for clinical trials and facilitate MS service planning. A multicentre observational, retrospective study of patients with MS from 5 tertiary neuroscience centres in the UK. We included all adult patients with a diagnosis of MS that had a relapse between 01/04/2020 and 30/06/2020. One hundred thirteen out of 8783 patients had a relapse during the 3-month study period. Seventy-nine percent of the patients with a relapse were female, the mean age was 39 years, and the median disease duration was 4.5 years; 36% of the patients that had a relapse were on disease-modifying treatment. The ARR from all study sites was estimated at 0.05. The ARR for relapsing remitting MS (RRMS) was estimated at 0.08, while the ARR for secondary progressive MS (SPMS) was 0.01. We report a lower ARR compared to previously reported rates in MS.

Development of a Fast and Sensitive UPLC–MS/MS Analytical Methodology for Fenebrutinib Estimation in Human Liver Microsomes: In Vitro and In Silico Metabolic Stability Evaluation

Fenebrutinib (GDC-0853; FNB) is an oral small molecule that was developed by Roche Pharmaceuticals to slow multiple sclerosis progression. FNB is a reversible bruton tyrosine kinase (BTK) inhibitor, which showed the maximum potency of BTK inhibitors in phase III clinical trials for multiple sclerosis. In the current study, a fast, specific, and sensitive UPLC-MS/MS method for FNB quantification in human liver microsomes (HLMs) was established with application to the evaluation of metabolic stability. The UPLC-MS/MS methodology was verified using the stated USFDA validation guidelines for bioanalytical methodologies that involve selectivity, linearity, accuracy and precision, carryover and extraction recovery, stability, and matrix effect. The FNB calibration curve displayed a linearity in the range from 1 ng/mL to 3000 ng/mL (y = 1.731x + 2.013; R2: 0.9954; RSD &lt; 4.37%) in the HLMs matrix. The limit of quantification was 0.88 ng/mL, which verified the UPLC-MS/MS analytical method sensitivity. The intraday and interday precision and accuracy results of the developed UPLC-MS/MS method were −3.99–14.0% and 0.52–3.83%, respectively. FNB and savolitinib (SVB) (internal standard) were chromatographically separated utilizing an isocratic mobile phase system with a ZORBAX Eclipse plus-C18 (50 mm, 2.1 mm, and 1.8 μm) column. The metabolic stability parameters for FNB, involving high intrinsic clearance (58.21 mL/min/kg) and a short in vitro half-life (13.93 min), revealed the high extraction ratio of FNB. Reviewing the literature revealed that the current UPLC-MS/MS method is the first analytical method for FNB quantification in the HLMs matrix with application to the assessment of FNB metabolic stability.

Evidence of publication bias in multiple sclerosis clinical trials: a comparative analysis of published and unpublished studies registered in ClinicalTrials.gov

BackgroundComplete and timely publication of clinical trials ensures that patients and the medical community are fully informed when making treatment decisions. The aim of this study is to assess the...

Multi-arm U-Net with dense input and skip connectivity for T2 lesion segmentation in clinical trials of multiple sclerosis

T2 lesion quantification plays a crucial role in monitoring disease progression and evaluating treatment response in multiple sclerosis (MS). We developed a 3D, multi-arm U-Net for T2 lesion segmentation, which was trained on a large, multicenter clinical trial dataset of relapsing MS. We investigated its generalization to other relapsing and primary progressive MS clinical trial datasets, and to an external dataset from the MICCAI 2016 MS lesion segmentation challenge. Additionally, we assessed the model’s ability to reproduce the separation of T2 lesion volumes between treatment and control arms; and the association of baseline T2 lesion volumes with clinical disability scores compared with manual lesion annotations. The trained model achieved a mean dice coefficient of ≥ 0.66 and a lesion detection sensitivity of ≥ 0.72 across the internal test datasets. On the external test dataset, the model achieved a mean dice coefficient of 0.62, which is comparable to 0.59 from the best model in the challenge, and a lesion detection sensitivity of 0.68. Lesion detection performance was reduced for smaller lesions (≤ 30 μL, 3–10 voxels). The model successfully maintained the separation of the longitudinal changes in T2 lesion volumes between the treatment and control arms. Such tools could facilitate semi-automated MS lesion quantification; and reduce rater burden in clinical trials.

Outcomes research strategies for clinical trials in multiple sclerosis

Outcomes research strategies for clinical trials in multiple sclerosis