Digital measures of respiratory and upper limb function in spinal muscular atrophy: design, feasibility, reliability, and preliminary validity of a smartphone sensor-based assessment suite.

Spinal muscular atrophy (SMA) is characterized by progressive muscle weakness and paralysis. Motor function is monitored in the clinical setting using assessments including the 32-item Motor Function Measure (MFM-32), but changes in disease severity between clinical visits may be missed. Digital health technologies may assist evaluation of disease severity by bridging gaps between clinical visits. We developed a smartphone sensor-based assessment suite, comprising nine tasks, to assess motor and muscle function in people with SMA. We used data from the risdiplam phase 2 JEWELFISH trial to assess the test-retest reliability and convergent validity of each task. In the first 6 weeks, 116 eligible participants completed assessments on a median of 6.3 days per week. Eight of the nine tasks demonstrated good or excellent test-retest reliability (intraclass correlation coefficients >0.75 and >0.9, respectively). Seven tasks showed a significant association (P < 0.05) with related clinical measures of motor function (individual items from the MFM-32 or Revised Upper Limb Module scales) and seven showed significant association (P < 0.05) with disease severity measured using the MFM-32 total score. This cross-sectional study supports the feasibility, reliability, and validity of using smartphone-based digital assessments to measure function in people living with SMA.

Industrial methodology for process verification in research (IMPROVER): toward systems biology verification.

MOTIVATION: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions. RESULTS: We present here, a review of the current state of systems biology verification and a detailed methodology to address its shortcomings. This methodology named 'Industrial Methodology for Process Verification in Research' or IMPROVER, consists on evaluating a research program by dividing a workflow into smaller building blocks that are individually verified. The verification of each building block can be done internally by members of the research program or externally by 'crowd-sourcing' to an interested community. www.sbvimprover.com IMPLEMENTATION: This methodology could become the preferred choice to verify systems biology research workflows that are becoming increasingly complex and sophisticated in industrial and academic settings.

Information systems for surrogate biomarkers.

Biopharmaceutical industry is incorporating biomarker concepts throughout the R&D processes, including the inclusion of biomarker-related data in the submission of new drug applications. In this paper we discuss the role of IT and information systems that support incorporation of surrogate biomarkers in the clinical development process, with emphasis on new molecular imaging technologies and associated IT requirements. In addition, we discuss how recently introduced FDA standards regarding submission data and FDA guidance documents related to genomic and imaging data can be accommodated in a solution architecture for (surrogate) biomarker-based clinical development.:

Characterization of platelet-derived growth factor-C (PDGF-C): expression in normal and tumor cells, biological activity and chromosomal localization.

The predicted platelet-derived growth factor-C (PDGF-C) polypeptide contains an N-terminal CUB-like domain and a C-terminal domain with homology to members of the PDGF/vascular endothelial growth factor (VEGF) family. PDGF-C mRNA is widely expressed in normal tissues and does not appear to be up-regulated in the tumor cell lines tested. The PDGF-C gene was mapped to human chromosome 4q31-32. PDGF-C protein and the CUB domain of PDGF-C expressed in Escherichia coli, were able to stimulate proliferation of human artery smooth muscle cells, but were inactive on umbilical vein endothelial cells, osteoblasts, fibroblasts, skeletal muscle cells (SkMC), bovine chondrocytes, and rat myocardium cells. Although the mitogenic activity of PDGF-C and the CUB domain was only observed at concentrations ranging from 1 to 10 microg/ml, substitution of Cys(124) by Ser or deletion of Cys(124) significantly reduced the mitogenic activity. Our data suggest a possible role of the CUB domain of PDGF-C in addition to its role in maintaining latency of the PDGF domain.