An Exploratory Evaluation of the Safety and Efficacy of Vorinostat in Pitt Hopkins Syndrome

Primary Outcomes (3)

• Frequency of treatment-related adverse events

  Treatment-related adverse events coded by MedDRA will be compared qualitatively between low dose treatment, high dose treatment, and placebo groups

  20 weeks

• Drug tolerability as measured by number of treatment discontinuations

  The number of patients discontinuing treatment due to adverse events will be assessed between low dose treatment, high dose treatment, and placebo groups

  20 weeks

• Change in transcriptomic profile from baseline, as measured by RNA-seq (transcriptome biomarker analysis)

  Transcriptome biomarker analysis is widely used to assess dynamic changes in biological systems in response to disease processes and applied stimuli, which cannot be captured with genomic sequencing of DNA mutations and variations. Unravel Biosciences has created a proprietary algorithm for analyzing transcriptome data, identifying underlying signatures of disease progression or recovery. The machine learned gene network approach predicted the use of vorinostat based on restoring a transcriptome signature of Rett syndrome toward a healthy state, which was confirmed preclinically and motivated this clinical trial. The same algorithm will be used to assess time-dependent changes in the transcriptome network signature, to evaluate its ability to capture clinical response data and to measure the extent of restoration of a disease signature back to a healthy state in a human relative to pre-clinical models.

  20 weeks

Conditions