PURPOSE: Clinical trial monitoring is an essential component of drug development aimed at safeguarding subject safety, data quality, and protocol compliance by focusing sponsor oversight on the most important aspects of study conduct. In recent years, regulatory agencies, industry consortia, and nonprofit collaborations between industry and regulators, such as TransCelerate and International Committee for Harmonization, have been advocating a new, risk-based approach to monitoring clinical trials that places increased emphasis on critical data and processes and encourages greater use of centralized monitoring. However, how best to implement risk-based monitoring (RBM) remains unclear and subject to wide variations in tools and methodologies. The nonprescriptive nature of the regulatory guidelines, coupled with limitations in software technology, challenges in operationalization, and lack of robust evidence of superior outcomes, have hindered its widespread adoption. METHODS: We describe a holistic solution that combines convenient access to data, advanced analytics, and seamless integration with established technology infrastructure to enable comprehensive assessment and mitigation of risk at the study, site, and subject level. FINDINGS: Using data from completed RBM studies carried out in the last 4 years, we demonstrate that our implementation of RBM improves the efficiency and effectiveness of the clinical oversight process as measured on various quality, timeline, and cost dimensions. IMPLICATIONS: These results provide strong evidence that our RBM methodology can significantly improve the clinical oversight process and do so at a lower cost through more intelligent deployment of monitoring resources to the sites that need the most attention.
PURPOSE: Clinical trial monitoring is an essential component of drug development aimed at safeguarding subject safety, data quality, and protocol compliance by focusing sponsor oversight on the most important aspects of study conduct. In recent years, regulatory agencies, industry consortia, and nonprofit collaborations between industry and regulators, such as TransCelerate and International Committee for Harmonization, have been advocating a new, risk-based approach to monitoring clinical trials that places increased emphasis on critical data and processes and encourages greater use of centralized monitoring. However, how best to implement risk-based monitoring (RBM) remains unclear and subject to wide variations in tools and methodologies. The nonprescriptive nature of the regulatory guidelines, coupled with limitations in software technology, challenges in operationalization, and lack of robust evidence of superior outcomes, have hindered its widespread adoption. METHODS: We describe a holistic solution that combines convenient access to data, advanced analytics, and seamless integration with established technology infrastructure to enable comprehensive assessment and mitigation of risk at the study, site, and subject level. FINDINGS: Using data from completed RBM studies carried out in the last 4 years, we demonstrate that our implementation of RBM improves the efficiency and effectiveness of the clinical oversight process as measured on various quality, timeline, and cost dimensions. IMPLICATIONS: These results provide strong evidence that our RBM methodology can significantly improve the clinical oversight process and do so at a lower cost through more intelligent deployment of monitoring resources to the sites that need the most attention.
Authors: Kia E Bryant; Yan Yuan; Melissa Engle; Ekaterina V Kurbatova; Cynthia Allen-Blige; Kumar Batra; Nicole E Brown; Kuo Wei Chiu; Howard Davis; Mascha Elskamp; Melissa Fagley; Pamela Fedrick; Kimberley N C Hedges; Kim Narunsky; Joanita Nassali; Mimi Phan; Ha Phan; Anne E Purfield; Jessica N Ricaldi; Kathleen Robergeau-Hunt; William C Whitworth; Erin E Sizemore Journal: Contemp Clin Trials Date: 2021-03-10 Impact factor: 2.226
Authors: Eric Yang; Jeremy D Scheff; Shih C Shen; Michael A Farnum; James Sefton; Victor S Lobanov; Dimitris K Agrafiotis Journal: Database (Oxford) Date: 2019-01-01 Impact factor: 3.451
Authors: Michael A Farnum; Mathangi Ashok; Daniel Kowalski; Fang Du; Lalit Mohanty; Paul Konstant; Joseph Ciervo; Victor S Lobanov; Dimitris K Agrafiotis Journal: Database (Oxford) Date: 2019-01-01 Impact factor: 3.451
Authors: Joseph Ciervo; Shih Chuan Shen; Kristin Stallcup; Abraham Thomas; Michael A Farnum; Victor S Lobanov; Dimitris K Agrafiotis Journal: JAMIA Open Date: 2019-03-19