Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities.

Importance: Amyloid-related imaging abnormalities (ARIA) are brain magnetic resonance imaging (MRI) findings associated with the use of amyloid-ß-directed monoclonal antibody therapies in Alzheimer disease (AD). ARIA monitoring is important to inform treatment dosing decisions and might be improved through assistive software. Objective: To assess the clinical performance of an artificial intelligence (AI)-based software tool for assisting radiological interpretation of brain MRI scans in patients monitored for ARIA. Design, Setting, and Participants: This diagnostic study used a multiple-reader multiple-case design to evaluate the diagnostic performance of radiologists assisted by the software vs unassisted. The study enrolled 16 US Board of Radiology-certified radiologists to perform radiological reading with (assisted) and without the software (unassisted). The study encompassed 199 retrospective cases, where each case consisted of a predosing baseline and a postdosing follow-up MRI of patients from aducanumab clinical trials PRIME, EMERGE, and ENGAGE. Statistical analysis was performed from April to July 2023. Exposures: Use of icobrain aria, an AI-based assistive software for ARIA detection and quantification. Main Outcomes and Measures: Coprimary end points were the difference in diagnostic accuracy between assisted and unassisted detection of ARIA-E (edema and/or sulcal effusion) and ARIA-H (microhemorrhage and/or superficial siderosis) independently, assessed with the area under the receiver operating characteristic curve (AUC). Results: Among the 199 participants included in this study of radiological reading performance, mean (SD) age was 70.4 (7.2) years; 105 (52.8%) were female; 23 (11.6%) were Asian, 1 (0.5%) was Black, 157 (78.9%) were White, and 18 (9.0%) were other or unreported race and ethnicity. Among the 16 radiological readers included, 2 were specialized neuroradiologists (12.5%), 11 were male individuals (68.8%), 7 were individuals working in academic hospitals (43.8%), and they had a mean (SD) of 9.5 (5.1) years of experience. Radiologists assisted by the software were significantly superior in detecting ARIA than unassisted radiologists, with a mean assisted AUC of 0.87 (95% CI, 0.84-0.91) for ARIA-E detection (AUC improvement of 0.05 [95% CI, 0.02-0.08]; P = .001]) and 0.83 (95% CI, 0.78-0.87) for ARIA-H detection (AUC improvement of 0.04 [95% CI, 0.02-0.07]; P = .001). Sensitivity was significantly higher in assisted reading compared with unassisted reading (87% vs 71% for ARIA-E detection; 79% vs 69% for ARIA-H detection), while specificity remained above 80% for the detection of both ARIA types. Conclusions and Relevance: This diagnostic study found that radiological reading performance for ARIA detection and diagnosis was significantly better when using the AI-based assistive software. Hence, the software has the potential to be a clinically important tool to improve safety monitoring and management of patients with AD treated with amyloid-ß-directed monoclonal antibody therapies.

Precision medicine analysis of heterogeneity in individual-level treatment response to amyloid beta removal in early Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) is a neurological disorder with variability in pathology and clinical progression. AD patients may differ in individual-level benefit from amyloid beta removal therapy. METHODS: Random forest models were applied to the EMERGE trial to create an individual-level treatment response (ITR) score which represents individual-level benefit of high-dose aducanumab relative to the placebo. This ITR score was used to test the existence of heterogeneity in treatment effect (HTE). RESULTS: We found statistical evidence of HTE in the Clinical Dementia Rating-Sum of Boxes (CDR-SB;P =  0.034). The observed CDR-SB benefit was 0.79 points greater in the group with the top 25% of ITR score compared to the remaining 75% (P = 0.020). Of note, the highest treatment responders had lower hippocampal volume, higher plasma phosphorylated tau 181 and a shorter duration of clinical AD at baseline. DISCUSSION: This ITR analysis provides a proof of concept for precision medicine in future AD research and drug development. HIGHLIGHTS: Emerging trials have shown a population-level benefit from amyloid beta (Aß) removal in slowing cognitive decline in early Alzheimer's disease (AD). This work demonstrates significant heterogeneity of individual-level treatment effect of aducanumab in early AD. The greatest clinical responders to Aß removal therapy have a pattern of more severe neurodegenerative process.

Assessing the utility of magnetic resonance imaging-based "SuStaIn" disease subtyping for precision medicine in relapsing-remitting and secondary progressive multiple sclerosis.

BACKGROUND: Patient stratification and individualized treatment decisions based on multiple sclerosis (MS) clinical phenotypes are arbitrary. Subtype and Staging Inference (SuStaIn), a published machine learning algorithm, was developed to identify data-driven disease subtypes with distinct temporal progression patterns using brain magnetic resonance imaging; its clinical utility has not been assessed. The objective of this study was to explore the prognostic capability of SuStaIn subtyping and whether it is a useful personalized predictor of treatment effects of natalizumab and dimethyl fumarate. METHODS: Subtypes were available from the trained SuStaIn model for 3 phase 3 clinical trials in relapsing-remitting and secondary progressive MS. Regression models were used to determine whether baseline SuStaIn subtypes could predict on-study clinical and radiological disease activity and progression. Differences in treatment responses relative to placebo between subtypes were determined using interaction terms between treatment and subtype. RESULTS: Natalizumab and dimethyl fumarate reduced inflammatory disease activity in all SuStaIn subtypes (all p < 0.001). SuStaIn MS subtyping alone did not discriminate responder heterogeneity based on new lesion formation and disease progression (p > 0.05 across subtypes). CONCLUSION: SuStaIn subtypes correlated with disease severity and functional impairment at baseline but were not predictive of disability progression and could not discriminate treatment response heterogeneity.

Glial fibrillary acidic protein and multiple sclerosis progression independent of acute inflammation.

BACKGROUND: The clinical relevance of serum glial fibrillary acidic protein (sGFAP) concentration as a biomarker of MS disability progression independent of acute inflammation has yet to be quantified. OBJECTIVE: To test whether baseline values and longitudinal changes in sGFAP concentration are associated with disability progression without detectable relapse of magnetic resonance imaging (MRI) inflammatory activity in participants with secondary-progressive multiple sclerosis (SPMS). METHODS: We retrospectively analyzed longitudinal sGFAP concentration and clinical outcome data from the Phase 3 ASCEND trial of participants with SPMS, with no detectable relapse or MRI signs of inflammatory activity at baseline nor during the study (n = 264). Serum neurofilament (sNfL), sGFAP, T2 lesion volume, Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), 9-Hole Peg Test (9HPT), and composite confirmed disability progression (CDP) were measured. Linear and logistic regressions and generalized estimating equations were used in the prognostic and dynamic analyses. RESULTS: We found a significant cross-sectional association between baseline sGFAP and sNfL concentrations and T2 lesion volume. No or weak correlations between sGFAP concentration and changes in EDSS, T25FW, and 9HPT, or CDP were observed. CONCLUSION: Without inflammatory activity, changes in sGFAP concentration in participants with SPMS were neither associated with current nor predictive of future disability progression.

Lesion-level correspondence and longitudinal properties of paramagnetic rim and slowly expanding lesions in multiple sclerosis.

BACKGROUND: Paramagnetic rim lesions (PRLs) and slowly expanding lesions (SELs) have been posited as markers of chronic active lesions (CALs). OBJECTIVE: To assess the lesion-level concordance of PRLs and SELs in MS and to characterize changes in brain tissue integrity in CALs over time. METHODS: MRIs were analyzed from a substudy of AFFINITY [NCT03222973], a phase 2 trial of opicinumab in relapsing MS. Assessments included (1) identification of SELs based on longitudinal MRIs over 72 weeks, and identification of PRLs on susceptibility-weighted imaging (SWI) filtered phase images at week 72; (2) evaluation of subject-level correlation of SEL and PRL counts, volumes, and degree of lesion-level overlap between SELs and PRLs; and (3) characterization of tissue integrity over time in overlapping and non-overlapping SELs and PRLs. RESULTS: In 41 subjects, 119 chronic PRLs and 267 SELs were detected. Of 119 (39.5%) chronic PRLs, 47 co-localized with a SEL; 46/267 (17.2%) SELs co-localized with a PRL. PRLs co-localized with SELs showed expansion and worsening microstructural damage over time. SELs with and without co-localization with PRLs showed ongoing tissue damage. CONCLUSIONS: Chronic MS lesions identified as both PRL and SEL were associated with the most severe accumulation of tissue damage. TRIAL REGISTRATION: AFFINITY [NCT03222973].

Evolving regulatory perspectives on digital health technologies for medicinal product development.

Digital health technology tools (DHTTs) present real opportunities for accelerating innovation, improving patient care, reducing clinical trial duration and minimising risk in medicines development. This review is comprised of four case studies of DHTTs used throughout the lifecycle of medicinal products, starting from their development. These cases illustrate how the regulatory requirements of DHTTs used in medicines development are based on two European regulatory frameworks (medical device and the medicinal product regulations) and highlight the need for increased collaboration between various stakeholders, including regulators (medicines regulators and device bodies), pharmaceutical sponsors, manufacturers of devices and software, and academia. As illustrated in the examples, the complexity of the interactions is further increased by unique challenges related to DHTTs. These case studies are the main examples of DHTTs with a regulatory assessment thus far, providing an insight into the applicable current regulatory approach; they were selected by a group of authors, including regulatory specialists from pharmaceutical sponsors, technology experts, academic researchers and employees of the European Medicines Agency. For each case study, the challenges faced by sponsors and proposed potential solutions are discussed, and the benefit of a structured interaction among the different stakeholders is also highlighted.

Single-timepoint low-dimensional characterization and classification of acute versus chronic multiple sclerosis lesions using machine learning.

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease characterized by the appearance of focal lesions across the central nervous system. The discrimination of acute from chronic MS lesions may yield novel biomarkers of inflammatory disease activity which may support patient management in the clinical setting and provide endpoints in clinical trials. On a single timepoint and in the absence of a prior reference scan, existing methods for acute lesion detection rely on the segmentation of hyperintense foci on post-gadolinium T1-weighted magnetic resonance imaging (MRI), which may underestimate recent acute lesion activity. In this paper, we aim to improve the sensitivity of acute MS lesion detection in the single-timepoint setting, by developing a novel machine learning approach for the automatic detection of acute MS lesions, using single-timepoint conventional non-contrast T1- and T2-weighted brain MRI. The MRI input data are supplemented via the use of a convolutional neural network generating "lesion-free" reconstructions from original "lesion-present" scans using image inpainting. A multi-objective statistical ranking module evaluates the relevance of textural radiomic features from the core and periphery of lesion sites, compared within "lesion-free" versus "lesion-present" image pairs. Then, an ensemble classifier is optimized through a recursive loop seeking consensus both in the feature space (via a greedy feature-pruning approach) and in the classifier space (via model selection repeated after each pruning operation). This leads to the identification of a compact textural signature characterizing lesion phenotype. On the patch-level task of acute versus chronic MS lesion classification, our method achieves a balanced accuracy in the range of 74.3-74.6% on fully external validation cohorts.

Preliminary validity of the Draw a Shape Test for upper extremity assessment in multiple sclerosis.

OBJECTIVE: To validate the smartphone sensor-based Draw a Shape Test - a part of the Floodlight Proof-of-Concept app for remotely assessing multiple sclerosis-related upper extremity impairment by tracing six different shapes. METHODS: People with multiple sclerosis, classified functionally normal/abnormal via their Nine-Hole Peg Test time, and healthy controls participated in a 24-week, nonrandomized study. Spatial (trace accuracy), temporal (mean and variability in linear, angular, and radial drawing velocities, and dwell time ratio), and spatiotemporal features (trace celerity) were cross-sectionally analyzed for correlation with standard clinical and brain magnetic resonance imaging (normalized brain volume and total lesion volume) disease burden measures, and for capacity to differentiate people with multiple sclerosis from healthy controls. RESULTS: Data from 69 people with multiple sclerosis and 18 healthy controls were analyzed. Trace accuracy (all shapes), linear velocity variability (circle, figure-of-8, spiral shapes), and radial velocity variability (spiral shape) had a mostly fair/moderate-to-good correlation (|r| = 0.14-0.66) with all disease burden measures. Trace celerity also had mostly fair/moderate-to-good correlation (|r| = 0.18-0.41) with Nine-Hole Peg Test performance, cerebellar functional system score, and brain magnetic resonance imaging. Furthermore, partial correlation analysis related these results to motor impairment. People with multiple sclerosis showed greater drawing velocity variability, though slower mean velocity, than healthy controls. Linear velocity (spiral shape) and angular velocity (circle shape) potentially differentiate functionally normal people with multiple sclerosis from healthy controls. INTERPRETATION: The Draw a Shape Test objectively assesses upper extremity impairment and correlates with all disease burden measures, thus aiding multiple sclerosis-related upper extremity impairment characterization.

Effect of reduction in brain amyloid levels on change in cognitive and functional decline in randomized clinical trials: An instrumental variable meta-analysis.

INTRODUCTION: Whether the reduction in brain amyloid beta (Aß) plaque alone may substantially slow cognitive and functional decline in patients with dementia or mild cognitive impairment due to Alzheimer's disease (AD) remains debated. METHODS: An instrumental variable meta-analysis was performed to infer the effect of change in positron emission tomography (PET)-measured Aß standardized uptake value ratio (SUVR) on cognitive and functional decline. RESULTS: Pooling data from 16 randomized trials demonstrates that each 0.1-unit decrease in PET Aß SUVR is associated with a reduction (95% confidence interval) by 0.09 (0.034-0.15), 0.33 (0.12-0.55), and 0.13 (0.017-0.24) point in the average change of the Clinical Dementia Rating-Sum of Boxes, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, and the Mini-Mental State Examination, respectively. DISCUSSION: This meta-analysis provides statistically significant evidence of a likely causal relationship between a reduction in Aß plaque and a reduction in cognitive and functional decline in patients with AD. HIGHLIGHTS: A widely cited meta-analysis article concluded amyloid beta reduction does not substantially improve cognition. We identified data inconsistencies in the initial publication and found new trial data. We repeated the meta-analysis after correcting data inconsistencies and adding new trial data. Updated results suggested statistically significant clinical benefit of amyloid beta reduction. Amyloid beta is a viable biological target for the treatment and prevention of AD.

Recurrent disability progression endpoints in multiple sclerosis clinical trials.

BACKGROUND: The current standard endpoint to assess disability accumulation in multiple sclerosis (MS) clinical trials is the time to the first confirmed disability progression, which excludes subsequent progression events. Including recurrent progression events may permit a more comprehensive assessment of treatment effects on disability progression. OBJECTIVE: To propose a definition of recurrent disability progression events and to compare time-to-first and recurrent event analysis. METHODS: Recurrent disability progression events were defined by expanding the recommended first event definition. Marginal recurrent event methods (negative binomial model, Lin-Wei-Yang-Ying model) were compared with Cox regression in data from three randomized controlled trials in relapsing multiple sclerosis (RMS) and primary progressive multiple sclerosis (PPMS), and in simulated randomized controlled trial data. RESULTS: The recurrent event analyses included a substantially larger number of progression events compared with the time-to-first-event analyses (+7.5% and +9.9% in the RMS trials and +22.7% in the PPMS trial). The increase in the number of events resulted in more precise treatment effect estimates and a corresponding gain in statistical power. CONCLUSION: Our results support the use of recurrent event data analysis, especially in progressive MS trials, to improve estimates of treatment effects, increase statistical power, and better capture the clinically meaningful long-term disability progression experience.

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.

BACKGROUND: With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes. OBJECTIVE: We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations. METHODS: A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers. RESULTS: A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care-related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care-related device, personal electronic devices, and entertainment consoles). CONCLUSIONS: Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

Overall Disability Response Score: An integrated endpoint to assess disability improvement and worsening over time in patients with multiple sclerosis.

BACKGROUND: Overall Disability Response Score (ODRS) is a composite endpoint including Expanded Disability Status Scale, Timed 25-foot Walk, and 9-Hole Peg Test, designed to quantify both disability improvement and worsening in multiple sclerosis (MS). OBJECTIVE: To assess the sensitivity and clinical meaningfulness of ODRS using natalizumab Phase 3 data sets (AFFIRM in relapsing-remitting MS and ASCEND in secondary progressive MS). METHODS: Differences in ODRS over 96 weeks, ODRS at Week 96, and slope of ODRS change per year between natalizumab and placebo groups were analyzed. Correlation between ODRS and changes in patient-reported outcomes was also analyzed. RESULTS: The difference (95% confidence interval (CI)) in the ODRS over 96 weeks between natalizumab and placebo groups was 0.34 (0.21-0.46) in AFFIRM (p < 0.001), and 0.18 (0.03-0.34) in ASCEND (p = 0.021). Significant differences between treatment arms were also observed in ODRS at Week 96 and in the slope of change per year in both studies. There was a significant linear correlation between ODRS at Week 96 and the change from baseline in both the physical and mental components of the 36-item Short Form Survey (SF-36) in both studies. CONCLUSION: This analysis supports ODRS as a sensitive and potentially clinically meaningful disability outcome measure in MS.

Chronic lesion activity and disability progression in secondary progressive multiple sclerosis.

Objective: Slowly expanding lesions (SELs), a subgroup of chronic white matter lesions that gradually expand over time, have been shown to predict disability accumulation in primary progressive multiple sclerosis (MS) disease. However, the relationships between SELs, acute lesion activity (ALA), overall chronic lesion activity (CLA) and disability progression are not well understood. In this study, we examined the ASCEND phase III clinical trial, which compared natalizumab with placebo in secondary progressive MS (SPMS). Methods: Patients with complete imaging datasets between baseline and week 108 (N=600) were analysed for SEL prevalence (the number and volume of SELs), disability progression, ALA (assessed by gadolinium-enhancing lesions and new T2-hyperintense lesions) and CLA (assessed by T1-hypointense lesion volume increase within baseline T2-non-enhancing lesions identified as SELs and non-SELs). Results: CLA in both SELs and non-SELs was greater in patients with SPMS with confirmed disability progression than in those with no progression. In the complete absence of ALA at baseline and on study, SEL prevalence was significantly lower, while CLA within non-SELs remained associated with disability progression. Natalizumab decreased SEL prevalence and CLA in SELs and non-SELs compared with placebo. Conclusions: This study shows that CLA in patients with SPMS is decreased but persists in the absence of ALA and is associated with disability progression, highlighting the need for therapeutics targeting all mechanisms of CLA, including smouldering inflammation and neurodegeneration. Trial registration number: NCT01416181.

A smartphone sensor-based digital outcome assessment of multiple sclerosis.

BACKGROUND: Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care. OBJECTIVE: The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app. METHODS: In a 24-week study (clinicaltrials.gov: NCT02952911), smartphone-based active tests and passive monitoring assessed cognition (electronic Symbol Digit Modalities Test), upper extremity function (Pinching Test, Draw a Shape Test), and gait and balance (Static Balance Test, U-Turn Test, Walk Test, Passive Monitoring). Intraclass correlation coefficients (ICCs) and age- or sex-adjusted Spearman's rank correlation determined test-retest reliability and correlations with clinical and magnetic resonance imaging (MRI) outcome measures, respectively. RESULTS: Seventy-six people with MS (PwMS) and 25 healthy controls were enrolled. In PwMS, ICCs were moderate-to-good (ICC(2,1) = 0.61-0.85) across tests. Correlations with domain-specific standard clinical disability measures were significant for all tests in the cognitive (r = 0.82, p < 0.001), upper extremity function (|r|= 0.40-0.64, all p < 0.001), and gait and balance domains (r = -0.25 to -0.52, all p < 0.05; except for Static Balance Test: r = -0.20, p > 0.05). Most tests also correlated with Expanded Disability Status Scale, 29-item Multiple Sclerosis Impact Scale items or subscales, and/or normalized brain volume. CONCLUSION: The Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.

Abnormalities in normal-appearing white matter from which multiple sclerosis lesions arise.

Normal-appearing white matter is far from normal in multiple sclerosis; little is known about the precise pathology or spatial pattern of this alteration and its relation to subsequent lesion formation. This study was undertaken to evaluate normal-appearing white matter abnormalities in brain areas where multiple sclerosis lesions subsequently form, and to investigate the spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis. Brain MRIs of pre-lesion normal-appearing white matter were analysed in participants with new T2 lesions, pooled from three clinical trials: SYNERGY (NCT01864148; n = 85 with relapsing multiple sclerosis) was the test data set; ASCEND (NCT01416181; n = 154 with secondary progressive multiple sclerosis) and ADVANCE (NCT00906399; n = 261 with relapsing-remitting multiple sclerosis) were used as validation data sets. Focal normal-appearing white matter tissue state was analysed prior to lesion formation in areas where new T2 lesions later formed (pre-lesion normal-appearing white matter) using normalized magnetization transfer ratio and T2-weighted (nT2) intensities, and compared with overall normal-appearing white matter and spatially matched contralateral normal-appearing white matter. Each outcome was analysed using linear mixed-effects models. Follow-up time (as a categorical variable), patient-level characteristics (including treatment group) and other baseline variables were treated as fixed effects. In SYNERGY, nT2 intensity was significantly higher, and normalized magnetization transfer ratio was lower in pre-lesion normal-appearing white matter versus overall and contralateral normal-appearing white matter at all time points up to 24 weeks before new T2 lesion onset. In ASCEND and ADVANCE (for which normalized magnetization transfer ratio was not available), nT2 intensity in pre-lesion normal-appearing white matter was significantly higher compared to both overall and contralateral normal-appearing white matter at all pre-lesion time points extending up to 2 years prior to lesion formation. In all trials, nT2 intensity in the contralateral normal-appearing white matter was also significantly higher at all pre-lesion time points compared to overall normal-appearing white matter. Brain atlases of normal-appearing white matter abnormalities were generated using measures of voxel-wise differences in normalized magnetization transfer ratio of normal-appearing white matter in persons with multiple sclerosis compared to scanner-matched healthy controls. We observed that overall spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis largely recapitulated the anatomical distribution of probabilities of T2 hyperintense lesions. Overall, these findings suggest that intrinsic spatial properties and/or longstanding precursory abnormalities of normal-appearing white matter tissue may contribute to the risk of autoimmune acute demyelination in multiple sclerosis.

Next-generation Bruton's tyrosine kinase inhibitor BIIB091 selectively and potently inhibits B cell and Fc receptor signaling and downstream functions in B cells and myeloid cells.

OBJECTIVES: Bruton's tyrosine kinase (BTK) plays a non-redundant signaling role downstream of the B-cell receptor (BCR) in B cells and the receptors for the Fc region of immunoglobulins (FcR) in myeloid cells. Here, we characterise BIIB091, a novel, potent, selective and reversible small-molecule inhibitor of BTK. METHODS: BIIB091 was evaluated in vitro and in vivo in preclinical models and in phase 1 clinical trial. RESULTS: In vitro, BIIB091 potently inhibited BTK-dependent proximal signaling and distal functional responses in both B cells and myeloid cells with IC50s ranging from 3 to 106 nm, including antigen presentation to T cells, a key mechanism of action thought to be underlying the efficacy of B cell-targeted therapeutics in multiple sclerosis. BIIB091 effectively sequestered tyrosine 551 in the kinase pocket by forming long-lived complexes with BTK with t 1/2 of more than 40 min, thereby preventing its phosphorylation by upstream kinases. As a key differentiating feature of BIIB091, this property explains the very potent whole blood IC50s of 87 and 106 nm observed with stimulated B cells and myeloid cells, respectively. In vivo, BIIB091 blocked B-cell activation, antibody production and germinal center differentiation. In phase 1 healthy volunteer trial, BIIB091 inhibited naïve and unswitched memory B-cell activation, with an in vivo IC50 of 55 nm and without significant impact on lymphoid or myeloid cell survival after 14 days of dosing. CONCLUSION: Pharmacodynamic results obtained in preclinical and early clinical settings support the advancement of BIIB091 in phase 2 clinical trials.

U-turn speed is a valid and reliable smartphone-based measure of multiple sclerosis-related gait and balance impairment.

BACKGROUND: People living with multiple sclerosis (MS) experience impairments in gait and mobility, that are not fully captured with manually timed walking tests or rating scales administered during periodic clinical visits. We have developed a smartphone-based assessment of ambulation performance, the 5 U-Turn Test (5UTT), a quantitative self-administered test of U-turn ability while walking, for people with MS (PwMS). RESEARCH QUESTION: What is the test-retest reliability and concurrent validity of U-turn speed, an unsupervised self-assessment of gait and balance impairment, measured using a body-worn smartphone during the 5UTT? METHODS: 76 PwMS and 25 healthy controls (HCs) participated in a cross-sectional non-randomised interventional feasibility study. The 5UTT was self-administered daily and the median U-turn speed, measured during a 14-day session, was compared against existing validated in-clinic measures of MS-related disability. RESULTS: U-turn speed, measured during a 14-day session from the 5UTT, demonstrated good-to-excellent test-retest reliability in PwMS alone and combined with HCs (intraclass correlation coefficient [ICC] = 0.87 [95 % CI: 0.80-0.92]) and moderate-to-excellent reliability in HCs alone (ICC = 0.88 [95 % CI: 0.69-0.96]). U-turn speed was significantly correlated with in-clinic measures of walking speed, physical fatigue, ambulation impairment, overall MS-related disability and patients' self-perception of quality of life, at baseline, Week 12 and Week 24. The minimal detectable change of the U-turn speed from the 5UTT was low (19.42 %) in PwMS and indicates a good precision of this measurement tool when compared with conventional in-clinic measures of walking performance. SIGNIFICANCE: The frequent self-assessment of turn speed, as an outcome measure from a smartphone-based U-turn test, may represent an ecologically valid digital solution to remotely and reliably monitor gait and balance impairment in a home environment during MS clinical trials and practice.