SMA is an inherited disease that leads to loss of motor function and ambulation and a reduced life expectancy. We have been working to develop orally administrated, systemically distributed small molecules to increase levels of functional SMN protein. Compound 2 was the first SMN2 splicing modifier tested in clinical trials in healthy volunteers and SMA patients. It was safe and well tolerated and increased SMN protein levels up to 2-fold in patients. Nevertheless, its development was stopped as a precautionary measure because retinal toxicity was observed in cynomolgus monkeys after chronic daily oral dosing (39 weeks) at exposures in excess of those investigated in patients. Herein, we describe the discovery of 1 (risdiplam, RG7916, RO7034067) that focused on thorough pharmacology, DMPK and safety characterization and optimization. This compound is undergoing pivotal clinical trials and is a promising medicine for the treatment of patients in all ages and stages with SMA.

No positive effect of UV-blocking contact lenses could be proven with the study design used.

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data.

Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization (‘neural recording’). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications.