Safety and feasibility of using acellular sterile filtered amniotic fluid as a treatment for patients with COVID-19: protocol for a randomised, double-blinded, placebo-controlled clinical trial.

INTRODUCTION: Human amniotic fluid (hAF) has been shown to reduce inflammation in multiple experimental models. hAF has previously been approved by the US Food and Drug Administration (FDA) as a human cellular and tissue product for tissue injury for human administration, and used safely in thousands of patients as a therapeutic treatment for diverse conditions. Given the profound inflammatory response observed in patients with COVID-19, and the successful completion of 10-patient pilot study of intravenous hAF, we present a trial design for a larger clinical trial of intravenous hAF for the treatment of COVID-19. METHODS AND ANALYSIS: This paper describes the methodology of a phase I/II randomised, double-blinded, placebo-controlled clinical trial to determine the safety and feasibility of using acellular sterile filtered amniotic fluid as a treatment for patients with COVID-19. Primary outcome will be the change in C-reactive protein. Secondary outcomes include safety, biomarker inflammatory levels and clinically relevant outcomes at 30 days, including mortality, ventilator-free days and hospital and intensive care unit length of stay. Exploratory outcomes of health-related quality-of-life patient-reported outcomes will be collected. Hospitalised patients with laboratory-confirmed COVID-19 will be recruited. ETHICS AND DISSEMINATION: This study was approved by the University of Utah Institutional Review Board (IRB_0013292), approved by the US FDA under Investigational New Drug (No 23369) and is registered on ClinicalTrials.gov. Results will be disseminated via peer-reviewed publications and conference presentations. TRIAL REGISTRATION NUMBER: NCT04497389; Pre-results.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science.

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.