Key result
Implementing data-sharing models for rare neuromuscular diseases is essential to overcome the siloing of clinical data and accelerate the development of novel therapies.
Siloing of clinical data is a major barrier in rare neuromuscular diseases, and data-sharing models are essential for developing valid biomarkers and accelerating therapy development.
Although the neuromuscular field has seen accelerated approval of a drug for Duchenne muscular dystrophy (DMD) and full approval of one for spinal muscular atrophy, these experiences have shown that objective data and an adequate level of effect are essential for drug approval and reimbursement. The appropriateness and validity of biomarkers and clinically meaningful endpoints and an understanding of disease progression rates all played essential roles in the levels of evidence for these drugs. Such tools are best developed through integration of clinical data. The siloing of clinical data for rare neuromuscular diseases represents a considerable barrier to achieving better care and novel therapies for patients living with neuromuscular diseases. We discuss a data-sharing model implemented for DMD and urge cultural changes in the ways natural history and clinical trial data are collected and shared across all neuromuscular diseases in order to benefit the primary stakeholder, the patient. Muscle Nerve 57: 16-19, 2018.
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Larkindale et al. (2017) conducted an editorial in Neuromuscular disorders. Data-sharing models was evaluated. Implementing data-sharing models for rare neuromuscular diseases is essential to overcome the siloing of clinical data and accelerate the development of novel therapies.
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