Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson’s Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

Plant oils rich in oleate are considered superior products compared to oils rich in polyunsaturated fatty acids. Peanut (Arachis hypogaea L.) is one of the major oilseed crops, and high oleate mutant varieties with as much as 85% oleate have been reported. We examined the possibility that this mutant phenotype resulted from reduction in the activity or the transcript level of microsomal oleoyl-PC desaturase. Two independently generated high oleate mutants, M2-225 and 8-2122, and their partially isogenic lines with a normal oleate phenotype were used in this study. Two cDNA sequences coding for microsomal oleoyl-PC desaturases, ahFAD2A and ahFAD2B, have been isolated from the developing peanut seed with a normal oleate phenotype. Cultivated peanut is an allotetraploid, and sequence comparisons with the genes from the putative diploid progenitor species suggested that ahFAD2A and ahFAD2B are non-allelic, but homeologous genes originating from two different diploid species. Northern analysis showed that the transcripts of oleoyl-PC desaturases are highly abundant in both normal and high oleate peanut seeds in the second stage of development. Differential digestion of the RT-PCR products revealed a restriction site polymorphism between ahFAD2A and ahFAD2B, and allowed us to examine the level of transcript expressed from each gene. The results indicate that ahFAD2A is expressed in both normal and high oleate peanut seeds, but the steady state level of the ahFAD2B transcript is severely reduced in the high oleate peanut varieties. These data suggested that the reduction in ahFAD2B transcript level in the developing seeds is correlated with the high oleate trait.

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