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<\/p>\nIdentifying qualified, high-performing sites for a particular study design and patient population is one of the most challenging aspects of clinical trial feasibility. Getting this right is critical to keeping studies on schedule and within budget.<\/p>\n
\nFor a global pharmaceutical company like Bristol Myers Squibb (BMS), efficient trial initiation depends on a strong partnership with investigator sites. While BMS sought to deepen these relationships, its technology landscape made that difficult. Study start-up and feasibility efforts relied on siloed feasibility data spread across multiple external survey tools. As a result, generating site-level insights was difficult, and historical knowledge was hard to transfer between study teams.<\/p>\n
\nBMS recognized the need to consolidate feasibility data into a single system to enable consistent reporting and dashboards.\n<\/p>\n
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\nMano Das, director IT at BMS, noted that decentralized data and document-heavy processes created several challenges. \u201cPreviously, we had siloed and inefficient data collection methods with no way to validate a site\u2019s estimates. The entire experience of simply signing a confidentiality agreement and completing a survey was incredibly inefficient for the investigator,\u201d Bischoff shares. \u201cWe needed a solution that would respect the site\u2019s time and accelerate the start-up phase.\u201d\n<\/p>\n
\nSites participating in multiple BMS studies also expressed frustration with repeatedly answering the same routine questions across various external platforms.\n<\/p>\n
\nBMS recognized that improving speed and site experience required moving away from manual trackers to a centralized, validated system designed around investigator workflows. By adopting ³Ô¹Ï±¬ÁÏ Clinical Operations, BMS consolidated data and automated key workflows across ³Ô¹Ï±¬ÁÏ CTMS and ³Ô¹Ï±¬ÁÏ Study Startup applications.<\/p>\n
\nThe change delivered measurable results. \u201cBy using ³Ô¹Ï±¬ÁÏ Study Startup, we\u2019ve reduced the overall timeline from site selection to site activation by 33%. And we shaved off six weeks from the time the protocol is approved to when the first subject is dosed,\u201d<\/strong> says Kurt Bischoff, associate director at BMS.\n<\/p>\n \nBMS streamlined feasibility, removing unnecessary steps and logins. \u201cWhen a sponsor sends a new study request, investigators can efficiently review the protocol, electronically sign the confidentiality agreement, and immediately access the feasibility survey \u2014 all through simple email links without ever logging into a separate system,\u201d Bischoff explains. In addition, they can now see centrally stored past feasibility data that’s easily reportable.\n<\/p>\n \nBMS established a single source of truth for feasibility activities, using standard questionnaire templates that can be reused across studies. Routine questions (like a site’s preferred language) are pre-populated from prior responses, reducing duplication. As a result, BMS anticipates a 50% reduction in the time required for site coordinators to complete feasibility surveys.\n<\/p>\n \nTo accelerate site activation, BMS moved away from fragmented country-level trackers to a unified foundation in ³Ô¹Ï±¬ÁÏ Study Startup with standardized global milestones, expected documents, and specific country templates. This shift enabled the team to replace manual reporting with interactive real-time dashboards that use visualization to provide executives and study managers with instant oversight.\n<\/p>\n \nThese visualizations allow for the early identification of activation risks, such as missed deadlines or delayed protocol packages, across various study sites. By leveraging Study Startup cycle-time data and predictive analytics, BMS can now proactively address bottlenecks and capitalize on opportunities for speed and informed, proactive decision-making.\n<\/p>\n \nWith feasibility data consolidated within ³Ô¹Ï±¬ÁÏ, BMS can make informed site selection decisions and improve study oversight. Information collected for one study can be reused for future studies, and teams can track progress against country- and study-level feasibility in near real-time. Across its portfolio, BMS can analyze historical feasibility data by therapeutic specific, region, or site to identify high-performing recruiting sites that have a low risk of study conduct quality concerns.\n<\/p>\n \n\u201cThe retention and consolidation of feasibility data within ³Ô¹Ï±¬ÁÏ allows us to mine the data,\u201d Das explained. \u201cWe can establish correlations between what a site said it could contribute to a study and the actual contributions it ends up making, enabling improved feedback loops to drive site selection decision-making.\u201d\n<\/p>\n \nLooking ahead, BMS plans to further streamline operations, improve the site experience, and do more predictive planning by implementing forecasted site activation dates based on historical cycle-time data.\n<\/p>\n \nBischoff notes: \u201cImagine a future where one or two questions are asked, or perhaps no feasibility questionnaire at all. We are even exploring using large language models to create the first version of the feasibility questionnaire so that we don\u2019t have to spend a lot of time on the first draft.\u201d\n<\/p>\n![\"\"](\"\/wp-content\/uploads\/2026\/01\/On-Page-Graphic_2-Survey@2x.png\")
<\/p>\nAccelerated site activation through analytics and visualization<\/h2>\n
Data-driven site selection and risk-based site activation<\/h2>\n
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<\/p>\nBMS\u2019 vision for study start-up<\/h2>\n
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