A framework for assessing clinical trial site readiness.

Clinical trial processes are unnecessarily inefficient and costly, slowing the translation of medical discoveries into treatments for people living with disease. To reduce redundancies and inefficiencies, a group of clinical trial experts developed a framework for clinical trial site readiness based on existing trial site qualifications from sponsors. The site readiness practices are encompassed within six domains: research team, infrastructure, study management, data collection and management, quality oversight, and ethics and safety. Implementation of this framework for clinical trial sites would reduce inefficiencies in trial conduct and help prepare new sites to enter the clinical trials enterprise, with the potential to improve the reach of clinical trials to underserved communities. Moreover, the framework holds benefits for trial sponsors, contract research organizations, trade associations, trial participants, and the public. For novice sites considering future trials, we provide a framework for site preparation and the engagement of stakeholders. For experienced sites, the framework can be used to assess current practices and inform and engage sponsors, staff, and participants. Details in the supplementary materials provide easy access to key regulatory documents and resources. Invited perspective articles provide greater depth from a systems, DEIA (diversity, equity, inclusion, and accessibility) and decentralized trials perspective.

Role of Plasmapheresis in Hemolysis, Elevated Liver Enzymes and Low Platelets (HELLP) Syndrome.

Hemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome is a rare abnormality comprising a series of symptoms that make up a syndrome. It usually happens during pregnancy or right after delivery. We describe a case of a 31-year-old female G4P2A2 (Gravida 4 Para 2 Abortions 2) who presented to the hospital for normal vaginal delivery but immediately postpartum developed HELLP syndrome. Acute fatty liver of pregnancy was a differential that the patient also met the criteria for. Her condition improved after starting her on plasmapheresis without considering hepatic transplantation. We emphasize distinguishing the overlap of symptoms between HELLP syndrome vs. acute fatty liver of pregnancy and the outcomes of plasmapheresis in managing HELLP syndrome without needing hepatic transplantation.

Advancing translational science education.

In this communication, the authors offer considerations for how the scientific community can capitalize on decades of translational science advances and experiential knowledge to develop new education opportunities for a diverse and highly skilled translational science workforce. Continued advancement of the field of translational science will require new education approaches that distill key concepts in translational science from past and ongoing research initiatives and teach this foundational knowledge to current and future translational scientists. These key concepts include generalizable scientific and operational principles to guide translational science, as well as evidence-informed practices. Inspired by this approach, the National Center for Advancing Translational Sciences (NCATS) has developed an initial set of guiding principles for translational science generated via case studies of multiple highly successful translational science initiatives, and is now teaching them via new education activities that aim to reach a broad scientific audience interested in translational science. Our goal with this review is to prompt continued conversation with the translational science community regarding capitalizing on our collective translational science knowledge to advance core content for translational science education and disseminating this content to a broad range of scientific audiences.

Iodinated Contrast-Induced Thyroid Storm With Concomitant Cardiac Tamponade: A Case Report.

A thyroid storm is a rare but life-threatening condition caused by the exaggeration of the clinical manifestations of thyrotoxicosis. The symptoms of thyroid storms are non-specific in nature, making the Burch Wartofsky Point Scale (BWPS) a valuable resource in the diagnosis of thyroid storms. Though not part of the BWPS scoring criteria, literature reviews have shown an increasing number of reports of pericardial effusion secondary to thyrotoxicosis. Pericardial effusion is a well-known sequela of hypothyroidism that, in severe cases, can cause cardiac tamponade. With increasing reports, clinicians should be aware that pericardial effusions can develop secondary to both underactive and overactive thyroid states. We present a case of iodine contrast-induced Jod-Basedow in a 29-year-old with a prior history of Graves disease with concomitant pericardial effusion requiring thyroidectomy.

Supraventricular Tachycardia: An Atypical Presentation of Thyroid Storm.

Thyroid storm (or thyrotoxic crisis) is commonly defined as a life-threatening condition caused by the exaggeration of the clinical manifestations of thyrotoxicosis. Supraventricular tachycardia (SVT) is an atypical precipitating symptom of thyrotoxicosis that clinicians should be aware of. An empirically derived scoring system known as the Burch-Wartofsky Point Scale (BWPS) has been used by clinicians since the early 1990s. The BWPS considers an array of precipitating factors and the severity of symptoms of multiple organ decompensation. In recent years, there has been an increasing correlation between SARS-CoV-2 and thyroid pathologies. We present a case of an unresponsive elderly male with a recent coronavirus disease 2019 (COVID-19) infection presenting with SVT and a BWPS score of 45, highly indicative of a thyroid storm.

Lemierre's Syndrome: A Comeback Story.

Lemierre's syndrome is a very rare and life-threatening complication of bacterial pharyngitis and tonsillitis. Often referred to as a 'forgotten disease', Lemierre's syndrome has seen a rise in cases over the years secondary to increased antibiotic resistance. With the potential for multiple organ failure secondary to widespread septic emboli, Lemierre's syndrome can no longer be forgotten. Prompt initiation of treatment is needed for better patient outcomes. We describe an unusual case of a young female without any significant past medical history who presented with left-sided pleuritic chest pain several days after experiencing a sore throat.

Teaching principles of translational science to a broad scientific audience using a case study approach: A pilot course from the National Center for Advancing Translational Sciences.

There are numerous examples of translational science innovations addressing challenges in the translational process, accelerating progress along the translational spectrum, and generating solutions relevant to a wide range of human health needs. Examining these successes through an education lens can identify core principles and effective practices that lead to successful translational outcomes. The National Center for Advancing Translational Sciences (NCATS) is identifying and teaching these core principles and practices to a broad audience via online courses in translational science which teach from case studies of NCATS-led or supported research initiatives. In this paper, we share our approach to the design of these courses and offer a detailed description of our initial course, which focused on a preclinical drug discovery and development project spanning academic and government settings. Course participants were from a variety of career stages and institutions. Participants rated the course high in overall value to them and in providing a unique window into the translational science process. We share our model for course development as well as initial findings from the course evaluation with the goal of continuing to stimulate development of novel education activities teaching foundational principles in translational science to a broad audience.

Defining clinical outcome pathways.

Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: molecular initiating event (MIE) â†’ intermediate event(s) â†’ clinical outcome. We illustrate the concept with COP examples both for primary and alternative (i.e., drug repurposing) therapeutic applications. We also describe the elucidation of COPs for several drugs of interest using the publicly accessible Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways (ROBOKOP) biomedical knowledge graph-mining tool. We propose that broader use of COP uncovered with the help of biomedical knowledge graph mining will likely accelerate drug discovery and repurposing efforts.

Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative.

Importance: The National COVID Cohort Collaborative (N3C) is a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy. Objectives: To evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity. Design, Setting, and Participants: In a retrospective cohort study of 1 926 526 US adults with SARS-CoV-2 infection (polymerase chain reaction >99% or antigen <1%) and adult patients without SARS-CoV-2 infection who served as controls from 34 medical centers nationwide between January 1, 2020, and December 7, 2020, patients were stratified using a World Health Organization COVID-19 severity scale and demographic characteristics. Differences between groups over time were evaluated using multivariable logistic regression. Random forest and XGBoost models were used to predict severe clinical course (death, discharge to hospice, invasive ventilatory support, or extracorporeal membrane oxygenation). Main Outcomes and Measures: Patient demographic characteristics and COVID-19 severity using the World Health Organization COVID-19 severity scale and differences between groups over time using multivariable logistic regression. Results: The cohort included 174 568 adults who tested positive for SARS-CoV-2 (mean [SD] age, 44.4 [18.6] years; 53.2% female) and 1 133 848 adult controls who tested negative for SARS-CoV-2 (mean [SD] age, 49.5 [19.2] years; 57.1% female). Of the 174 568 adults with SARS-CoV-2, 32 472 (18.6%) were hospitalized, and 6565 (20.2%) of those had a severe clinical course (invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice). Of the hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March to April 2020 to 8.6% in September to October 2020 (P = .002 for monthly trend). Using 64 inputs available on the first hospital day, this study predicted a severe clinical course using random forest and XGBoost models (area under the receiver operating curve = 0.87 for both) that were stable over time. The factor most strongly associated with clinical severity was pH; this result was consistent across machine learning methods. In a separate multivariable logistic regression model built for inference, age (odds ratio [OR], 1.03 per year; 95% CI, 1.03-1.04), male sex (OR, 1.60; 95% CI, 1.51-1.69), liver disease (OR, 1.20; 95% CI, 1.08-1.34), dementia (OR, 1.26; 95% CI, 1.13-1.41), African American (OR, 1.12; 95% CI, 1.05-1.20) and Asian (OR, 1.33; 95% CI, 1.12-1.57) race, and obesity (OR, 1.36; 95% CI, 1.27-1.46) were independently associated with higher clinical severity. Conclusions and Relevance: This cohort study found that COVID-19 mortality decreased over time during 2020 and that patient demographic characteristics and comorbidities were associated with higher clinical severity. The machine learning models accurately predicted ultimate clinical severity using commonly collected clinical data from the first 24 hours of a hospital admission.

Report of the National Institutes of Health SARS-CoV-2 Antiviral Therapeutics Summit.

The NIH Virtual SARS-CoV-2 Antiviral Summit, held on 6 November 2020, was organized to provide an overview on the status and challenges in developing antiviral therapeutics for coronavirus disease 2019 (COVID-19), including combinations of antivirals. Scientific experts from the public and private sectors convened virtually during a live videocast to discuss severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) targets for drug discovery as well as the preclinical tools needed to develop and evaluate effective small-molecule antivirals. The goals of the Summit were to review the current state of the science, identify unmet research needs, share insights and lessons learned from treating other infectious diseases, identify opportunities for public-private partnerships, and assist the research community in designing and developing antiviral therapeutics. This report includes an overview of therapeutic approaches, individual panel summaries, and a summary of the discussions and perspectives on the challenges ahead for antiviral development.

Opportunities and challenges in translational science.

The mission of translational science is to bring predictivity and efficiency to the development and dissemination of interventions that improve human health. Ten years ago this year, the National Center for Advancing Translational Sciences was founded to embody, conduct, and support this new discipline. The Center's first decade has brought substantial progress across a broad range of translational areas, from diagnostic and drug development to clinical trials to implementation science to education. The origins of the translational science and advances to this point are reviewed here and allow the establishment of an ambitious future research agenda for the field.

A versatile polypharmacology platform promotes cytoprotection and viability of human pluripotent and differentiated cells.

Human pluripotent stem cells (hPSCs) are capable of extensive self-renewal yet remain highly sensitive to environmental perturbations in vitro, posing challenges to their therapeutic use. There is an urgent need to advance strategies that ensure safe and robust long-term growth and functional differentiation of these cells. Here, we deployed high-throughput screening strategies to identify a small-molecule cocktail that improves viability of hPSCs and their differentiated progeny. The combination of chroman 1, emricasan, polyamines, and trans-ISRIB (CEPT) enhanced cell survival of genetically stable hPSCs by simultaneously blocking several stress mechanisms that otherwise compromise cell structure and function. CEPT provided strong improvements for several key applications in stem-cell research, including routine cell passaging, cryopreservation of pluripotent and differentiated cells, embryoid body (EB) and organoid formation, single-cell cloning, and genome editing. Thus, CEPT represents a unique poly-pharmacological strategy for comprehensive cytoprotection, providing a rationale for efficient and safe utilization of hPSCs.

Biological activity-based modeling identifies antiviral leads against SARS-CoV-2.

Computational approaches for drug discovery, such as quantitative structure-activity relationship, rely on structural similarities of small molecules to infer biological activity but are often limited to identifying new drug candidates in the chemical spaces close to known ligands. Here we report a biological activity-based modeling (BABM) approach, in which compound activity profiles established across multiple assays are used as signatures to predict compound activity in other assays or against a new target. This approach was validated by identifying candidate antivirals for Zika and Ebola viruses based on high-throughput screening data. BABM models were then applied to predict 311 compounds with potential activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of the predicted compounds, 32% had antiviral activity in a cell culture live virus assay, the most potent compounds showing a half-maximal inhibitory concentration in the nanomolar range. Most of the confirmed anti-SARS-CoV-2 compounds were found to be viral entry inhibitors and/or autophagy modulators. The confirmed compounds have the potential to be further developed into anti-SARS-CoV-2 therapies.

The National COVID Cohort Collaborative: Clinical Characterization and Early Severity Prediction.

Background: The majority of U.S. reports of COVID-19 clinical characteristics, disease course, and treatments are from single health systems or focused on one domain. Here we report the creation of the National COVID Cohort Collaborative (N3C), a centralized, harmonized, high-granularity electronic health record repository that is the largest, most representative U.S. cohort of COVID-19 cases and controls to date. This multi-center dataset supports robust evidence-based development of predictive and diagnostic tools and informs critical care and policy. Methods and Findings: In a retrospective cohort study of 1,926,526 patients from 34 medical centers nationwide, we stratified patients using a World Health Organization COVID-19 severity scale and demographics; we then evaluated differences between groups over time using multivariable logistic regression. We established vital signs and laboratory values among COVID-19 patients with different severities, providing the foundation for predictive analytics. The cohort included 174,568 adults with severe acute respiratory syndrome associated with SARS-CoV-2 (PCR >99% or antigen <1%) as well as 1,133,848 adult patients that served as lab-negative controls. Among 32,472 hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March/April 2020 to 8.6% in September/October 2020 (p = 0.002 monthly trend). In a multivariable logistic regression model, age, male sex, liver disease, dementia, African-American and Asian race, and obesity were independently associated with higher clinical severity. To demonstrate the utility of the N3C cohort for analytics, we used machine learning (ML) to predict clinical severity and risk factors over time. Using 64 inputs available on the first hospital day, we predicted a severe clinical course (death, discharge to hospice, invasive ventilation, or extracorporeal membrane oxygenation) using random forest and XGBoost models (AUROC 0.86 and 0.87 respectively) that were stable over time. The most powerful predictors in these models are patient age and widely available vital sign and laboratory values. The established expected trajectories for many vital signs and laboratory values among patients with different clinical severities validates observations from smaller studies, and provides comprehensive insight into COVID-19 characterization in U.S. patients. Conclusions: This is the first description of an ongoing longitudinal observational study of patients seen in diverse clinical settings and geographical regions and is the largest COVID-19 cohort in the United States. Such data are the foundation for ML models that can be the basis for generalizable clinical decision support tools. The N3C Data Enclave is unique in providing transparent, reproducible, easily shared, versioned, and fully auditable data and analytic provenance for national-scale patient-level EHR data. The N3C is built for intensive ML analyses by academic, industry, and citizen scientists internationally. Many observational correlations can inform trial designs and care guidelines for this new disease.

Organs-on-chips: into the next decade.

Organs-on-chips (OoCs), also known as microphysiological systems or 'tissue chips' (the terms are synonymous), have attracted substantial interest in recent years owing to their potential to be informative at multiple stages of the drug discovery and development process. These innovative devices could provide insights into normal human organ function and disease pathophysiology, as well as more accurately predict the safety and efficacy of investigational drugs in humans. Therefore, they are likely to become useful additions to traditional preclinical cell culture methods and in vivo animal studies in the near term, and in some cases replacements for them in the longer term. In the past decade, the OoC field has seen dramatic advances in the sophistication of biology and engineering, in the demonstration of physiological relevance and in the range of applications. These advances have also revealed new challenges and opportunities, and expertise from multiple biomedical and engineering fields will be needed to fully realize the promise of OoCs for fundamental and translational applications. This Review provides a snapshot of this fast-evolving technology, discusses current applications and caveats for their implementation, and offers suggestions for directions in the next decade.