Population pharmacokinetic and exposure-efficacy analysis of ixekizumab in paediatric patients with moderate-to-severe plaque psoriasis (IXORA-PEDS)

AIMS: Ixekizumab is a high-affinity monoclonal antibody that selectively targets interleukin-17A used in the treatment of adult and paediatric patients with moderate-to-severe psoriasis. This analysis evaluated the pharmacokinetics (PK) of ixekizumab and the exposure-efficacy relationship in paediatric patients aged 6 to <18 years with psoriasis. METHODS: Population PK and exposure-efficacy models were developed. The models used data from paediatric patients with psoriasis participating in the Phase 3 IXORA-PEDS trial in which patients were dosed according to weight categories. The exposure-efficacy model is a Psoriasis Area and Severity Index (PASI) time course model using data up to Week 12, a co-primary efficacy endpoint. RESULTS: A 2-compartment population PK model describes the PK of ixekizumab in paediatric patients with the effect of body weight incorporated on clearance and volume terms using an allometric relationship. The weight category-based dosing ensured that ixekizumab mean trough serum concentrations in paediatric patients with psoriasis (3.20-3.33 μg/mL) were within the range of concentrations observed in adult patients with psoriasis (mean [standard deviation]: 3.48 [2.16] μg/mL) administered an efficacious dosing regimen. The observed PASI response rates at Week 12 in paediatric patients (91.9/81.8/52.5% for PASI75/90/100) are well predicted by the final exposure-efficacy model and response rates are similar or higher than those achieved in adults (86.2/66.6/35.0% for PASI75/90/100). CONCLUSION: This analysis is the first to describe the PK and exposure-efficacy relationship of ixekizumab in paediatric patients with psoriasis. The analyses support the selection of the weight category-based ixekizumab dosing regimens approved for use in paediatric patients with psoriasis

Resting-brain functional connectivity predicted by analytic measures of network communication.

The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures-search information and path transitivity-which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways

Dynamics and heterogeneity of brain damage in multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune disease driving inflammatory and degenerative processes that damage the central nervous system (CNS). However, it is not well understood how these events interact and evolve to evoke such a highly dynamic and heterogeneous disease. We established a hypothesis whereby the variability in the course of MS is driven by the very same pathogenic mechanisms responsible for the disease, the autoimmune attack on the CNS that leads to chronic inflammation, neuroaxonal degeneration and remyelination. We propose that each of these processes acts more or less severely and at different times in each of the clinical subgroups. To test this hypothesis, we developed a mathematical model that was constrained by experimental data (the expanded disability status scale [EDSS] time series) obtained from a retrospective longitudinal cohort of 66 MS patients with a long-term follow-up (up to 20 years). Moreover, we validated this model in a second prospective cohort of 120 MS patients with a three-year follow-up, for which EDSS data and brain volume time series were available. The clinical heterogeneity in the datasets was reduced by grouping the EDSS time series using an unsupervised clustering analysis. We found that by adjusting certain parameters, albeit within their biological range, the mathematical model reproduced the different disease courses, supporting the dynamic CNS damage hypothesis to explain MS heterogeneity. Our analysis suggests that the irreversible axon degeneration produced in the early stages of progressive MS is mainly due to the higher rate of myelinated axon degeneration, coupled to the lower capacity for remyelination. However, and in agreement with recent pathological studies, degeneration of chronically demyelinated axons is not a key feature that distinguishes this phenotype. Moreover, the model reveals that lower rates of axon degeneration and more rapid remyelination make relapsing MS more resilient than the progressive subtype. Therefore, our results support the hypothesis of a common pathogenesis for the different MS subtypes, even in the presence of genetic and environmental heterogeneity. Hence, MS can be considered as a single disease in which specific dynamics can provoke a variety of clinical outcomes in different patient groups. These results have important implications for the design of therapeutic interventions for MS at different stages of the disease.The European Union Seventh Framework Program (HEALTH-F4-2012-305397): “CombiMS”, grant agreement No 30539; the Horizon 2020 program ERACOSYSMED: Sys4MS grant, and the Spanish Ministry of Economy and Competitiveness and FEDER (project FIS2015-66503-C3-1-P), and the Swedish Research Council (3R)