The objective of this study was to evaluate the safety and efficacy of bermekimab, an IL-1a inhibitor, in the treatment of hidradenitis suppurativa (HS). This study was a phase II, multicenter, open-label study of two dose cohorts of bermekimab in patients with moderate-to-severe HS who are naïve to or have failed prior anti-TNF therapy. Patients with HS (n ¼ 42) were divided into groups A and B based on whether or not they had previously failed an anti-TNF therapy. In group A (n ¼ 24), bermekimab was administered subcutaneously at a dose of 400 mg weekly (13 doses) in patients who had previously failed anti-TNF therapy; in group B (n ¼ 18), bermekimab was administered subcutaneously at a dose of 400 mg weekly (13 doses) in patients who were anti-TNF naïve. Bermekimab, previously found to be effective in treating HS, was evaluated using a subcutaneous formulation in patients with HS naïve to or having failed anti-TNF therapy. There were no bermekimab-related adverse events with the exception of injection site reactions. Bermekimab was effective despite treatment history, with 61% and 63% of patients naïve to and having failed anti-TNF therapy, respectively, achieving HS clinical response after 12 weeks of treatment. A significant reduction in abscesses and inflammatory nodules of 60% (P < 0.004) and 46% (P < 0.001) was seen in anti-TNF naïve and anti-TNF failure groups, respectively. Clinically and statistically significant reduction was seen in patients experiencing pain, with the Visual Analogue Scale pain score reducing by 64% (P < 0.001) and 54% (P < 0.001) in the anti-TNF naïve and anti-TNF failure groups, respectively. IL-1a is emerging as an important clinical target for skin disease, and bermekimab may represent a new therapeutic option for treating moderate-to-severe HS.
Abstract. Volunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low-cost access to massive computing resources but also where there is a significant public interest in the research being done.We discuss the way in which cloud services can help BOINC-based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing platform within the cloud, and outline new approaches that could open up new possibilities in this field, using Climateprediction.net (http://www. climateprediction.net/) as a case study.
Abstract. Volunteer or Crowd computing is becoming increasingly popular to solve complex research problems, from an increasing diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low cost access to massive computing resource but also that there is a significant public interest in the research done. We discuss the way in which Cloud services can help BOINC based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing plat- form within the Cloud, and outline new approaches that could open up new possibilities in this field, using http://climateprediction.net as a case study.
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