【日本語版】データドリブンなソリューションによる乳がん臨床試験の最適化

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Clinical

NOV 04, 2024

Home / Resources / 【日本語版】データドリブンなソリューションによる乳がん臨床試験の最適化

Last updated: Dec 15, 2025

ある世界的な製薬会社は、乳がんの新しい治療法の臨床試験を実施する準備をしています。同社は、データ主導で効率的なアプローチを確実にするために、Citeline のソリューションスイートを使用して、試験計画と研究の開始を迅速化しています。これらのソリューションは、製薬会社がプロトコルの開発、治験責任医師および施設の選択に長年頼ってきた Trialtrove と Sitetrove の臨床試験データのゴールドスタンダードに基づいて、主要な試験パラメータに関する即時の推奨事項を提供します。

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Step 1: Determining Primary Endpoints & I/E Criteria

The company defines the type of breast cancer trial they need to run in Protocol SmartDesign, which provides recommendations for primary endpoints. These suggestions are tailored to the specific subtype of breast cancer being targeted, such as HER2-positive, triple-negative, or hormone receptor-positive breast cancer.

Protocol SmartDesign also suggests inclusion/exclusion (I/E) criteria, which factor in key patient characteristics such as age, tumor stage, previous treatments, and genetic markers. After reviewing the suggestions, the company modifies the I/E criteria slightly to align with their study’s focus on patients with a specific mutation. The platform updates the projected study duration in real-time, ensuring the company is aware of how these adjustments affect the trial timeline.

Step 2: Forecasting Length of Study

By refining the I/E criteria, the company immediately sees how their changes impact the forecasted enrollment duration. This dynamic feedback enables the team to balance the scientific rigor of the criteria with the practical considerations of recruiting breast cancer patients who meet their specific trial parameters. Protocol SmartDesign ensures that the trial is designed to meet both scientific and operational needs.

Step 3: Selecting Countries and Investigators

The company then moves to select the best countries and investigators to run the trial. Investigator SmartSelect generates a list of recommended investigators account with a strong history of success in breast cancer trials, considering factors such as investigator expertise in treating the specific subtype of breast cancer and their capacity to run a new study. The platform will also recommend countries and investigator allocation.

The company can see forecasted enrollment rates, allowing them to fine-tune the selection of countries and investigators until the trial’s timeline is optimal. Adjusting the mix of countries and investigators ensures they can hit enrollment targets within the desired timeframe.

Step 4: Investigating Patient Populations and Diversity Goals

Once the investigators are selected, the team leverages Sitetrove’s Global Patient Insights to explore patient populations at the selected sites.

This feature allows them to analyze whether there are enough eligible breast cancer patients available in the targeted regions. Importantly, they also confirm that the selected sites can meet all diversity goals, ensuring representation across race, ethnicity, and age groups, which is critical for breast cancer trials where specific populations may have higher risks or respond differently to treatments.

Step 5: Finalizing the Trial Plan

With a breast cancer trial design that has been optimized for both patient recruitment and trial timeline, the pharmaceutical company is ready to move forward confidently. By leveraging real-time data and predictive analytics, they’ve created a trial that not only meets scientific objectives but also ensures a diverse and representative patient population, critical to the study of breast cancer treatment outcomes.

Leveraging the power of Citeline SmartSolutions, Trialtrove, Sitetrove and Global Patient Insights, this company produced a protocol that had limited amendments, investigators who could successful run and recruit for the trial, allowing them to hit enrollment goals and complete the study on time and on budget.

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