Evaluating protocol lifecycle time intervals in HIV/AIDS clinical trials

Abstract

Background Identifying efficacious interventions for the prevention and treatment of human diseases depends on the efficient development and implementation of controlled clinical trials. Essential to reducing the time and burden of completing the clinical trial lifecycle is determining which aspects take the longest, delay other stages, and may lead to better resource utilization without diminishing scientific quality, safety, or the protection of human subjects. Purpose In this study we modeled time-to-event data to explore relationships between clinical trial protocol development and implementation times, as well as identify potential correlates of prolonged development and implementation. Methods We obtained time interval and participant accrual data from 111 interventional clinical trials initiated between 2006 and 2011 by NIH’s HIV/AIDS Clinical Trials Networks. We determined the time (in days) required to complete defined phases of clinical trial protocol development and implementation. Kaplan-Meier estimates were used to assess the rates at which protocols reached specified terminal events, stratified by study purpose (therapeutic, prevention) and phase group (pilot/phase I, phase II, and phase III/ IV). We also examined several potential correlates to prolonged development and implementation intervals. Results Even though phase grouping did not determine development or implementation times of either therapeutic or prevention studies, overall we observed wide variation in protocol development times. Moreover, we detected a trend toward phase III/IV therapeutic protocols exhibiting longer developmental (median 2 ½ years) and implementation times (>3years). We also found that protocols exceeding the median number of days for completing the development interval had significantly longer implementation. Limitations The use of a relatively small set of protocols may have limited our ability to detect differences across phase groupings. Some timing effects present for a specific study phase may have been masked by combining protocols into phase groupings. Presence of informative censoring, such as withdrawal of some protocols from development if they began showing signs of lost interest among investigators, complicates interpretation of Kaplan-Meier estimates. Because this study constitutes a retrospective examination over an extended period of time, it does not allow for the precise identification of relative factors impacting timing. Conclusions Delays not only increase the time and cost to complete clinical trials, but they also diminish their usefulness by failing to answer research questions in time. We believe that research analyzing the time spent traversing defined intervals across the clinical trial protocol development and implementation continuum can stimulate business process analyses and reengineering efforts that could lead to reductions in the time from clinical trial concept to results, thereby accelerating progress in clinical research.

Activating clinical trials: a process improvement approach

“…We propose a framework based on a totally different approach that maps the administrative process through VSM, identifies barriers for trial opening through timing analysis and SNA, and examines system performance under different scenarios through DES. The use of systematic approaches to analyze the trial activation process, rather than case study alone, has been recognized as a key tool to make trials more efficient [ 21 ].…”

“…This sizable amount is exonerated if we consider that the administrative process associated with trial activation in academic medical settings includes up to 30 different activities, involves up to 11 participants, and lasts on average, from 44 to 172 days [ 6 , 8 , 17 , 18 ]. Such complexity translates into delayed trial activation, which affects patient enrollment goals [ 19 , 20 ] and diminishes the usefulness of trials by failing to attain evidence of investigated interventions on time [ 21 ].…”

Conducting clinical trials—costs, impacts, and the value of clinical trials networks: A scoping review

“…Trials bureaucracy has been estimated at US$50,000 per site, 64 and the trial development process-from study conception to activation-can take upwards of 800 days in the United States 42 and 600 days in the United Kingdom. 43 Delays and associated costs also raised concerns that clinical research will be outpaced by the discoveries they are designed to test, 64,65 and one recent study estimated that 25% of industry trials recruit from lowincome countries to reduce costs. 66 Signs of diminished site capacity were found in Canada as a consequence of activation delays.…”

“…31,[73][74][75] Moreover, because these collectives are inherently integrated, they may be well-positioned to consolidate infrastructure and improve patients' access to trials across communities. 22,75 It is worth noting, however, that networked groups are not de facto efficient entities, 42,65 are underfunded, 70 and have little, if any, control over their share of an institution's operating budget or the complex regulatory environment in which they function.…”

Using a Federated Network of Real-World Data to Optimize Clinical Trials Operations

“…Using a site’s real-world data to analyze the size of the local patient population that satisfies a clinical trial’s eligibility criteria has been shown to accurately predict whether a trial could conceivably attain its accrual goals. 12 Prospectively eliminating studies that lack the required patient cohort size via a data-driven prescreening analysis would reduce the financial loss associated with unsuccessfully accruing trials. Enterprise research repositories, such as those that are built on the Informatics for Integrating Biology and the Bedside (i2b2) 13 platform, have been widely used in cohort identification for prospective studies, and those that have regular refreshes of clinical data can provide a reliable indication of prospective trial accrual.…”