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9.
Contemp Clin Trials ; 106: 106438, 2021 07.
Article in English | MEDLINE | ID: covidwho-1230388

ABSTRACT

With billions of dollars in research and development (R&D) funding continuing to be invested, the novel coronavirus disease 2019 (COVID-19) has become into a singular focus for the scientific community. However, the collective response from the scientific communities have seen poor return on investment, particularly for therapeutic research for COVID-19, revealing the existing weaknesses and inefficiencies of the clinical trial enterprise. In this article, we argue for the importance of structural changes to existing research programs for clinical trials in light of the lessons learned from COVID-19.


Subject(s)
Biomedical Research/organization & administration , COVID-19/epidemiology , COVID-19/therapy , Clinical Protocols/standards , Clinical Trials as Topic/organization & administration , Biomedical Research/economics , Biomedical Research/standards , Clinical Trials as Topic/economics , Clinical Trials as Topic/standards , Humans , SARS-CoV-2
10.
Clin Trials ; 18(4): 511-513, 2021 08.
Article in English | MEDLINE | ID: covidwho-1195906

ABSTRACT

The proposed triple aim of health care-enhanced patient experience, improved population health, and reduced per capita costs-can be applied to clinical research. A triple aim for clinical research would (1) improve the individual research participant's experience; (2) promote the health of populations; and (3) reduce per capita costs of clinical research. Such an approach is possible by designing trials around the needs of participants rather than sites, embracing digital measures of health, and advancing decentralized studies. Recent studies, including those evaluating therapies for COVID-19, have demonstrated the value of such an approach. Accelerating the adoption of these methods can help fulfill this new triple aim of clinical research.


Subject(s)
Clinical Trials as Topic/methods , Goals , Population Health , Research Subjects , Research Support as Topic , Biomedical Research/economics , Biomedical Research/methods , Biomedical Research/organization & administration , Clinical Trials as Topic/economics , Clinical Trials as Topic/organization & administration , Costs and Cost Analysis , Health Promotion , Humans , Patient Satisfaction , Telemedicine
12.
Contemp Clin Trials ; 104: 106368, 2021 05.
Article in English | MEDLINE | ID: covidwho-1155430

ABSTRACT

OBJECTIVES: COVID-19 pandemic caused several alarming challenges for clinical trials. On-site source data verification (SDV) in the multicenter clinical trial became difficult due to travel ban and social distancing. For multicenter clinical trials, centralized data monitoring is an efficient and cost-effective method of data monitoring. Centralized data monitoring reduces the risk of COVID-19 infections and provides additional capabilities compared to on-site monitoring. The key steps for on-site monitoring include identifying key risk factors and thresholds for the risk factors, developing a monitoring plan, following up the risk factors, and providing a management plan to mitigate the risk. METHODS: For analysis purposes, we simulated data similar to our clinical trial data. We classified the data monitoring process into two groups, such as the Supervised analysis process, to follow each patient remotely by creating a dashboard and an Unsupervised analysis process to identify data discrepancy, data error, or data fraud. We conducted several risk-based statistical analysis techniques to avoid on-site source data verification to reduce time and cost, followed up with each patient remotely to maintain social distancing, and created a centralized data monitoring dashboard to ensure patient safety and maintain the data quality. CONCLUSION: Data monitoring in clinical trials is a mandatory process. A risk-based centralized data review process is cost-effective and helpful to ignore on-site data monitoring at the time of the pandemic. We summarized how different statistical methods could be implemented and explained in SAS to identify various data error or fabrication issues in multicenter clinical trials.


Subject(s)
COVID-19 , Clinical Trials as Topic , Data Accuracy , Multicenter Studies as Topic , Research Design/trends , Risk Management , COVID-19/epidemiology , COVID-19/prevention & control , Change Management , Clinical Trials Data Monitoring Committees/organization & administration , Clinical Trials as Topic/economics , Clinical Trials as Topic/methods , Clinical Trials as Topic/organization & administration , Communicable Disease Control/methods , Cost-Benefit Analysis , Humans , Risk Adjustment/methods , Risk Adjustment/trends , Risk Assessment/methods , Risk Management/methods , Risk Management/trends , SARS-CoV-2 , Travel-Related Illness
20.
Cancer Discov ; 10(9): 1263-1266, 2020 09.
Article in English | MEDLINE | ID: covidwho-646133

ABSTRACT

The COVID-19 pandemic has caused widespread disruption of cancer clinical trials due to the restrictions on nonessential services and the reallocation of resources, and at the same time the urgent global effort toward discovering therapies that treat or prevent COVID-19 infection has led to shortening of traditional regulatory timelines. This experience should stimulate similar urgency in the way future cancer research is conducted.


Subject(s)
Biomedical Research/trends , Clinical Trials as Topic/organization & administration , Coronavirus Infections/therapy , Medical Oncology/trends , Neoplasms/therapy , Pneumonia, Viral/therapy , Betacoronavirus/isolation & purification , Biomedical Research/economics , Biomedical Research/organization & administration , Biomedical Research/standards , COVID-19 , Clinical Trials as Topic/economics , Clinical Trials as Topic/standards , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Forecasting , Health Care Rationing/organization & administration , Health Care Rationing/standards , Health Care Rationing/trends , Humans , Medical Oncology/economics , Medical Oncology/organization & administration , Medical Oncology/standards , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , SARS-CoV-2 , Time Factors
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