Differentiators, Data Coverage and Quality
What makes Investigator SmartSelect unique?
Citeline’s Investigator SmartSelect (ISS) leverages advanced statistics and AI-enabled technology built on industry-leading Sitetrove, Trialtrove data, and Norstella’s RWD, along with proprietary performance insights and from Greenphire data, to deliver a curated and data-driven list of high-performing investigators with the experience, capacity, and patient availability (for the US) to execute your trial on time and on budget.
By mitigating unconscious bias and accounting for patient diversity (for the US), ISS surfaces the absolute best-fit investigators—even those you haven’t worked with before. Often, it uncovers high-performing, up-and-coming investigators who weren’t initially on the team’s radar but prove to be the best match based on experience and execution capability. This reduces the risk of defaulting to familiar choices and expands access to top-tier talent.
Beyond investigator selection, ISS provides data-driven country recommendations by analyzing historical performance data to identify countries most likely to meet enrollment goals. It offers forecasted enrollment rates via a AI-driven model and optimal investigator allocation within those countries, saving feasibility teams time by handling the complex geographic and site landscape analysis.
A key advantage of ISS is its ability to align operational impact with investigator selection. By integrating patient enrollment metrics with investigator recommendations, ISS gives teams a clear view of how selection choices impact trial duration. This data-driven approach empowers teams to optimize speed, recruitment performance, and overall trial success.
What types of data are used to inform the algorithm's recommendations?
Investigator SmartSelect is built on gold-standard and proprietary data that enable you to gain an even more robust recommended list of high-performing investigators who have the experience, capacity, and patient availability (for the US) to deliver their trial. Various datasets are fed into a proprietary algorithm to identify the best-fit investigators for a clinical trial. The algorithm evaluates several factors, including:
Experience conducting multiple trials in the selected indication.
Outcomes of past trials in the selected indication.
Recruitment potential based on historical trial performance.
Industry expertise and specific experience in the selected indication.
Current trial load and capacity to take on new studies.
Patient pool availability for the selected indication.
Regulatory status of the investigator.
Number of patients recruited and enrollment rates.
Timeline of patient enrollment, from first recruitment to completion, including the total number of patients recruited during that period.
What are the key differentiators of Investigator SmartSelect?
Your One Stop Shop for Curated Data
Access curated data meticulously cleaned in-house by our Ontology team and updated daily by our analyst team, ensuring the highest level of accuracy, reliability, and timeliness. Data is presented using our industry-leading, gold-standard methodology, designed to enhance usability and support informed decision-making.
World-Class Data Intelligence
Sitetrove: Features 550,000+ investigators from 194,000+ sites across 185+ countries, accelerating trial planning and execution. It’s the only solution combining rich site and investigator intelligence with U.S. patient and investigator demographics.
Trialtrove: Draws from over 58,000 unique sources, with a ~40% increase in sources per therapeutic area since 2015. More than half of all trials included are not available on ClinicalTrials.gov, offering exclusive insights in a centralized, holistic platform.
Real-World Data (RWD): Encompasses 32 billion+ claims, 200 million+ annual patients, and 200 million+ patient diversity records, including race and ethnicity, providing unparalleled epidemiological data breadth and depth.
Proprietary Performance Data: Draws from the industry's largest and most comprehensive dataset related to investigator performance and financial transactions within clinical trials, including patient enrollment, participant payment data, site payment data, and travel logistics information.
AI-Driven Competitive Advantage
With access to the largest database of clinical trials data and real-world data (RWD), Investigator SmartSelect possesses an extensive knowledge base that no competitor can match. Our competitive edge is further amplified by highly effective advanced statistics- and AI-driven models and cutting-edge capabilities, allowing us to leverage this vast dataset to provide accurate, reliable, and timely recommended investigators to set your trial up for success, by design. This powerful combination of comprehensive data, advanced statistics- and AI-driven technology positions Investigator SmartSelect as the market leader for recommending investigators to accelerate clinical trials, empowering sponsors, researchers, and institutions to make informed, data-driven decisions with confidence.
Effortless Integration Across Industry Trusted Platforms
Investigator SmartSelect is fully interoperable with the industry-leading products sponsors and CROs know and trust – Trialtrove and Sitetrove. Ensure seamless integration with existing workflows, enhancing efficiency and maximizing the value of your data to retrieve and leverage recommended investigators to accelerate trial timelines.
Why choose this solution?
Investigator SmartSelect stands apart from other AI-driven tools by combining Citeline's and Norstella’s world-class data with unparalleled transparency. At its core, the solution leverages Citeline’s Sitetrove, Trialtrove, Norstella’s RWD, and proprietary performance data to provide trusted, data-backed recommendations. Every investigator recommendation comes with a clear data trail, allowing you to view the source information directly in Sitetrove. This level of transparency ensures that you can trust both the data and the recommendations—a critical differentiator in an industry where many AI-driven tools offer only “black-box” outputs without explaining the rationale behind them.
With Investigator SmartSelect, you gain:
Trust in Data-Backed Decisions: Every recommendation is rooted in real-world, meticulously curated data that you can verify. Unlike other solutions, ISS offers the confidence of knowing where the data comes from and why specific investigators are recommended.
Actionable Insights at Your Fingertips: Citeline’s and Norstella’s market-leading datasets power Investigator SmartSelect, enabling you to move beyond guesswork and make informed decisions about investigator and site selection.
Confidence in the Process: The solution not only reduces the time and complexity of identifying the best-fit investigators but also introduces transparency that helps align all stakeholders, from feasibility teams to regulatory authorities, around data you can trust.
Investigator SmartSelect isn’t just about making faster decisions—it’s about making better, more reliable ones, built on data you can stand behind.
Product Questions
How can I trust the results from Investigator SmartSelect?
Investigator SmartSelect combines Citeline’s and Norstella’s world-class data, advanced statistics, machine learning models, and industry insights to recommend investigators with the greatest potential to meet trial enrollment goals. Every recommendation comes with full transparency—you can view the source data directly in Sitetrove and Trialtrove, giving you confidence in the accuracy, reliability, and timeliness of our results.
How is this different from the tiered investigator list in Sitetrove?
Investigator SmartSelect goes beyond the tiered list by incorporating additional factors, such as the investigator's performance, ability and speed to recruit participants, and trial outcomes, which are not included in Sitetrove’s tiered investigator lists. This enables more nuanced, data-driven recommendations to set your trial up for success by design.
Does Investigator SmartSelect only look at investigators from successful trials?
No, Investigator SmartSelect does not limit its analysis to investigators and countries from successful trials. The tool considers a wide range of historical trials, including planned, open, closed, completed, and terminated trials, to holistically evaluate and recommend investigators and countries based on their experience, recruitment performance and potential, trial capacity, and patient availability (for the US) to provide accurate, reliable, and timely recommendations.
Does the algorithm consider the competitive landscape when forecasting enrollment rates?
Yes, the forecasted enrollment rate in "Based on Our Model's Suggested Countries" represents the predicted number of participants per site per month in the recommended countries. When recommending countries for a trial, the model considers factors, such as historical competitiveness. Additionally, we provide user-relevant key analytics metrics per study. However, it does not evaluate the real-time landscape of ongoing trials and cannot determine the country-related competitive intensity of the market at the time the trial is conducted.
How does Greenphire data fit into Investigator SmartSelect?
Greenphire data provide insights into investigator-level performance, including key metrics, such as patient enrollment rates. Along with Greenphire data, the algorithm also factors in investigator capacity, trial experience, and historical recruitment performance to generate recommendations. Additionally, Greenphire data is used to assess whether the recommended countries have the capability to meet the recruitment needs of a study based on their historical performance.
How frequently are Citeline datasets updated in Investigator SmartSelect?
Citeline clinical trials-related data (Sitetrove and Trialtrove) and Norstella real-world data (RWD) are updated regularly, with RWD being updated weekly. Citeline data are updated by analysts who monitor public domain sources and curate or enrich such data based on their expertise and other sources. Updates are reflected in Investigator SmartSelect as soon as they are added to the database, ensuring the most current information is available.
How is “Forecasted Enrollment Duration” defined?
It is the estimated period required for participant enrollment, in months, based on the forecasted enrollment rate via an AI-driven model and the number of investigators allocated per country.