Remote Monitoring and Data Collection for Decentralized Clinical Trials.

Importance: Less than 5% of patients with cancer enroll in a clinical trial, partly due to financial and logistic burdens, especially among underserved populations. The COVID-19 pandemic marked a substantial shift in the adoption of decentralized trial operations by pharmaceutical companies. Objective: To assess the current global state of adoption of decentralized trial technologies, understand factors that may be driving or preventing adoption, and highlight aspirations and direction for industry to enable more patient-centric trials. Design, Setting, and Participants: The Bloomberg New Economy International Cancer Coalition, composed of patient advocacy, industry, government regulator, and academic medical center representatives, developed a survey directed to global biopharmaceutical companies of the coalition from October 1 through December 31, 2022, with a focus on registrational clinical trials. The data for this survey study were analyzed between January 1 and 31, 2023. Exposure: Adoption of decentralized clinical trial technologies. Main Outcomes and Measures: The survey measured (1) outcomes of different remote monitoring and data collection technologies on patient centricity, (2) adoption of these technologies in oncology and all therapeutic areas, and (3) barriers and facilitators to adoption using descriptive statistics. Results: All 8 invited coalition companies completed the survey, representing 33% of the oncology market by revenues in 2021. Across nearly all technologies, adoption in oncology trials lags that of all trials. In the current state, electronic diaries and electronic clinical outcome assessments are the most used technology, with a mean (SD) of 56% (19%) and 51% (29%) adoption for all trials and oncology trials, respectively, whereas visits within local physician networks is the least adopted at a mean (SD) of 12% (18%) and 7% (9%), respectively. Looking forward, the difference between the current and aspired adoption rate in 5 years for oncology is large, with respondents expecting a 40% or greater absolute adoption increase in 8 of the 11 technologies surveyed. Furthermore, digitally enabled recruitment, local imaging capabilities, and local physician networks were identified as technologies that could be most effective for improving patient centricity in the long term. Conclusions and Relevance: These findings may help to galvanize momentum toward greater adoption of enabling technologies to support a new paradigm of trials that are more accessible, less burdensome, and more inclusive.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson's disease.

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson's disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP(+). Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP(+) model. We hypothesised that analysis of protein-protein interaction networks modelling MPP(+) toxicity could identify proteins critical for mediating MPP(+) toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP(+) toxicity) enabled us to identify four proteins predicted to be key for MPP(+) toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP(+) toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP(+) toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Manganese(III)-mediated radical cyclisations for the (Z)-selective synthesis of exo-alkylidene pyrrolidinones and pyrrolidines.

The cyclisation of alkynyl amido- and amino-malonates in the presence of manganese(III) acetate gives exo-alkylidene pyrrolidinones and pyrrolidines with a preference for the (Z)-alkene product isomer.