Accurately predict your key trial milestones

<!doctype html><html lang="en-us"><head> <meta charset="utf-8"> <title>Accurately predict your key trial milestones | nQuery Predict</title> <link rel="shortcut icon" href="https://www.statsols.com/hubfs/nQuery%20clinical%20trial%20design%20software%20icon.png"> <meta name="description" content="Use nQuery Predict to reduce your risk by accurately forecasting key trial milestones"> <meta name="viewport" content="width=device-width, initial-scale=1"> <script src="/hs/hsstatic/jquery-libs/static-1.4/jquery/jquery-1.11.2.js"></script> <script>hsjQuery = window['jQuery'];</script> <meta property="og:description" content="Use nQuery Predict to reduce your risk by accurately forecasting key trial milestones"> <meta property="og:title" content="Accurately predict your key trial milestones | nQuery Predict"> <meta name="twitter:description" content="Use nQuery Predict to reduce your risk by accurately forecasting key trial milestones"> <meta name="twitter:title" content="Accurately predict your key trial milestones | nQuery Predict"> <style> a.cta_button{-moz-box-sizing:content-box !important;-webkit-box-sizing:content-box !important;box-sizing:content-box !important;vertical-align:middle}.hs-breadcrumb-menu{list-style-type:none;margin:0px 0px 0px 0px;padding:0px 0px 0px 0px}.hs-breadcrumb-menu-item{float:left;padding:10px 0px 10px 10px}.hs-breadcrumb-menu-divider:before{content:'›';padding-left:10px}.hs-featured-image-link{border:0}.hs-featured-image{float:right;margin:0 0 20px 20px;max-width:50%}@media (max-width: 568px){.hs-featured-image{float:none;margin:0;width:100%;max-width:100%}}.hs-screen-reader-text{clip:rect(1px, 1px, 1px, 1px);height:1px;overflow:hidden;position:absolute !important;width:1px} </style> <link rel="stylesheet" href="https://www.statsols.com/hs-fs/hub/488764/hub_generated/template_assets/130521435988/1729287983428/nquery-theme/cli-build/css/styles.min.css"> <link rel="stylesheet" href="https://www.statsols.com/hs-fs/hub/488764/hub_generated/template_assets/130515235912/1723206765330/nquery-theme/css/main.min.css"> <link rel="stylesheet" href="https://www.statsols.com/hs-fs/hub/488764/hub_generated/template_assets/130515336359/1725989622564/nquery-theme/css/theme-overrides.min.css"> <link rel="stylesheet" href="https://www.statsols.com/hs-fs/hub/488764/hub_generated/module_assets/131433263946/1726837309233/module_131433263946_floating-texture.min.css"> <style> #hs_cos_wrapper_module_170500911710710 .button-wrapper { text-align:LEFT; 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data-hsv-src="https://play.hubspotvideo.com/v/488764/id/153559639560?play_button_color=ffffff&autoplay=true&loop=true" referrerpolicy="origin" sandbox="allow-forms allow-scripts allow-same-origin allow-popups" allow="autoplay; fullscreen;" style="position: absolute !important; width: 100% !important; height: 100% !important; left: 0; top: 0; border: 0 none; pointer-events: initial" title="HubSpot Video" loading="lazy" data-hsv-id="153559639560" data-hsv-play-button-color="ffffff" data-hsv-width="1920" data-hsv-height="1009" data-hsv-autoplay="true" data-hsv-loop="true" data-hsv-muted="false" data-hsv-hidden-controls="false" data-hsv-full-width="true"></iframe> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-7 dnd_area-row-1-padding dnd-section"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-8 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050091037537" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17050091037537_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h2 style="text-align: center; font-size: 39px;">Answer important practical trial questions</h2></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-9 dnd_area-row-2-padding dnd-section stack-reverse dnd_area-row-2-max-width-section-centering dnd_area-row-2-vertical-alignment"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_17050091422518-vertical-alignment dnd-column" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-10 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_1705009142252" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_1705009142252_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3>When will my trial finish?</h3></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-11 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050091422522" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17050091422522_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><p>nQuery Predict uses powerful modeling and simulation to accurately forecast your expected study duration for trial milestones such as enrollment targets</p></span></div> </div> </div> </div> </div> <div class="span8 widget-span widget-type-cell cell_17050091422519-vertical-alignment dnd-column" style="" data-widget-type="cell" data-x="4" data-w="8"> <div class="row-fluid-wrapper row-depth-1 row-number-12 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_widget_1705623223101" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image shadow-img" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_widget_1705623223101_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=1504&name=predict-1-new.png" class="hs-image-widget " style="width:1504px;border-width:0px;border:0px;" width="1504" alt="predict-1-new" title="predict-1-new" srcset="https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=752&name=predict-1-new.png 752w, https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=1504&name=predict-1-new.png 1504w, https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=2256&name=predict-1-new.png 2256w, https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=3008&name=predict-1-new.png 3008w, https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=3760&name=predict-1-new.png 3760w, https://www.statsols.com/hs-fs/hubfs/predict-1-new.png?width=4512&name=predict-1-new.png 4512w" sizes="(max-width: 1504px) 100vw, 1504px"></span> </div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-13 dnd_area-row-3-max-width-section-centering dnd-section dnd_area-row-3-padding dnd_area-row-3-vertical-alignment"> <div class="row-fluid "> <div class="span8 widget-span widget-type-cell cell_17050091468404-vertical-alignment cell_17050091468404-margin dnd-column" style="" data-widget-type="cell" data-x="0" data-w="8"> <div class="row-fluid-wrapper row-depth-1 row-number-14 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_widget_1705623260655" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image shadow-img" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_widget_1705623260655_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=1504&name=predict-1-when.png" class="hs-image-widget " style="width:1504px;border-width:0px;border:0px;" width="1504" alt="predict-1-when" title="predict-1-when" srcset="https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=752&name=predict-1-when.png 752w, https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=1504&name=predict-1-when.png 1504w, https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=2256&name=predict-1-when.png 2256w, https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=3008&name=predict-1-when.png 3008w, https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=3760&name=predict-1-when.png 3760w, https://www.statsols.com/hs-fs/hubfs/predict-1-when.png?width=4512&name=predict-1-when.png 4512w" sizes="(max-width: 1504px) 100vw, 1504px"></span> </div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_17050091468405-vertical-alignment dnd-column" style="" data-widget-type="cell" data-x="8" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-15 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500914684011" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500914684011_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3>Project Survival Trends</h3></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-16 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500914684012" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500914684012_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><p>Milestone event targets are key to predicting the length a survival analysis study. nQuery Predict provides tools to project future events trends based on both blinded and unblinded estimates</p></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-17 dnd-section stack-reverse dnd_area-row-4-max-width-section-centering dnd_area-row-4-padding dnd_area-row-4-vertical-alignment"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_17050091528418-vertical-alignment cell_17050091528418-margin dnd-column" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-18 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500915284113" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500915284113_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3>Am I enrolling enough patients?</h3></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-19 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500915284114" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500915284114_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><p>Enrollment delays, slow event rates and high dropout can create additional costs and uncertainty. Use nQuery Predict to model these factors at either a subject or site level using projections based on pre-trial assumptions or interim data</p></span></div> </div> </div> </div> </div> <div class="span8 widget-span widget-type-cell cell_17050091528419-vertical-alignment dnd-column" style="" data-widget-type="cell" data-x="4" data-w="8"> <div class="row-fluid-wrapper row-depth-1 row-number-20 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_widget_1705623273051" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image shadow-img" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_widget_1705623273051_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=1504&name=predict-3.png" class="hs-image-widget " style="width:1504px;border-width:0px;border:0px;" width="1504" alt="predict-3" title="predict-3" srcset="https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=752&name=predict-3.png 752w, https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=1504&name=predict-3.png 1504w, https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=2256&name=predict-3.png 2256w, https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=3008&name=predict-3.png 3008w, https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=3760&name=predict-3.png 3760w, https://www.statsols.com/hs-fs/hubfs/predict-3.png?width=4512&name=predict-3.png 4512w" sizes="(max-width: 1504px) 100vw, 1504px"></span> </div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-21 dnd-section dnd_area-row-5-padding"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-22 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050090326245" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="button-wrapper"> <a class="button" href="https://www.statsols.com/nquery-demo?hsLang=en-us"> Get Started </a> </div></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-23 dnd_area-row-6-padding dnd-section dnd_area-row-6-max-width-section-centering dnd_area-row-6-background-layers dnd_area-row-6-background-color"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-24 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050090102677" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17050090102677_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h2 style="text-align: center; font-size: 39px;">Use nQuery Predict to reduce your risk by accurately forecasting key trial milestones<span style="color: #515c62;"></span></h2></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-25 dnd_area-row-7-background-color dnd_area-row-7-background-layers dnd-section dnd_area-row-7-max-width-section-centering dnd_area-row-7-padding"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_17050089982155-margin dnd-column" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-26 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget module_170500899821510-flexbox-positioning dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821510" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500899821510_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-27 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821511" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500899821511_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Enrollment Prediction</h3> <p><span style="color: #515c62;">Simulate how long it will take to recruit patients</span></p></span></div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_17050089982156-padding dnd-column" style="" data-widget-type="cell" data-x="4" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-28 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module module_170500899821514-flexbox-positioning" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821514" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500899821514_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-29 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821515" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500899821515_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Events Prediction</h3> <p><span style="color: #515c62;">Provide realistic estimates of expected timings and costs</span></p></span></div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="8" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-30 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget module_170500899821518-flexbox-positioning dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821518" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500899821518_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-31 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500899821519" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500899821519_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Global & Site Level</h3> <p><span style="color: #515c62;">Model on a global basis, or individual sites such as hospitals</span></p></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-32 dnd_area-row-8-max-width-section-centering dnd-section dnd_area-row-8-background-layers dnd_area-row-8-padding dnd_area-row-8-background-color"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_170500900326410-margin dnd-column" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-33 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget module_170500900326415-flexbox-positioning dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326415" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500900326415_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-34 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326416" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500900326416_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Powerful Simulation</h3> <p><span style="color: #515c62;">Generate accurate trial projections from your data</span></p></span></div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_170500900326411-padding dnd-column" style="" data-widget-type="cell" data-x="4" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-35 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget module_170500900326419-flexbox-positioning dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326419" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500900326419_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-36 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326420" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500900326420_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Multiple Event Models</h3> <p><span style="color: #515c62;">Projections for both blinded and unblinded data</span></p></span></div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="8" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-37 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module module_170500900326423-flexbox-positioning" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326423" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <span id="hs_cos_wrapper_module_170500900326423_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_linked_image" style="" data-hs-cos-general-type="widget" data-hs-cos-type="linked_image"><img src="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png" class="hs-image-widget " width="48" height="48" style="max-width: 100%; height: auto;" alt="circle-check" title="circle-check" loading="lazy" srcset="https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=24&height=24&name=circle-check.png 24w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=48&height=48&name=circle-check.png 48w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=72&height=72&name=circle-check.png 72w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=96&height=96&name=circle-check.png 96w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=120&height=120&name=circle-check.png 120w, https://www.statsols.com/hs-fs/hubfs/circle-check.png?width=144&height=144&name=circle-check.png 144w" sizes="(max-width: 48px) 100vw, 48px"></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-38 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500900326424" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_170500900326424_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h3 style="font-size: 23px; margin-bottom: 18px;">Visualize Success</h3> <p><span style="color: #515c62;">Easy to use reporting for all trial stakeholders</span></p></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-39 dnd_area-row-9-max-width-section-centering dnd-section dnd_area-row-9-padding"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-40 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050089859267" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17050089859267_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><a id="how-to" data-hs-anchor="true"></a> <h2 style="text-align: center; font-size: 39px;">5 easy steps for better clinical trials</h2> <p style="text-align: center;"><span style="color: #515c62;">nQuery Predict uses simulation to help you make better predictions about when key trial milestones will occur. Identify roadblocks and take action to keep your trial on schedule.</span></p></span></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-41 dnd-section dnd_area-row-10-background-layers dnd_area-row-10-background-color dnd_area-row-10-padding dnd_area-row-10-max-width-section-centering"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_17050089662247-padding dnd-column cell_17050089662247-margin" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-42 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget module_170500896622411-hidden dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500896622411" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_1pj2w2zakp popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Step 1</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Type of Prediction </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_17050089662248-padding dnd-column" style="" data-widget-type="cell" data-x="4" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-43 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500896622413" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_r6x7je9o5x popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Step 2</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Your Data </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_17050089662249-padding dnd-column" style="" data-widget-type="cell" data-x="8" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-44 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500896622415" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_3ah0zyvl5g popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Step 3</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Accrual Options </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-45 dnd_area-row-11-background-layers dnd-section dnd_area-row-11-max-width-section-centering dnd_area-row-11-background-color dnd_area-row-11-padding"> <div class="row-fluid "> <div class="span4 widget-span widget-type-cell cell_1712766906207-padding cell_1712766906207-margin dnd-column" style="" data-widget-type="cell" data-x="0" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-46 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17127669062073" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_1e2a1pmeou popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Step 4</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Event & Dropout </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell cell_1712766917981-padding dnd-column" style="" data-widget-type="cell" data-x="4" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-47 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17127669179813" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_lobbtr6czp popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Step 5</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Simulation Controls </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> <div class="span4 widget-span widget-type-cell dnd-column cell_1712766938489-padding" style="" data-widget-type="cell" data-x="8" data-w="4"> <div class="row-fluid-wrapper row-depth-1 row-number-48 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17127669384893" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="overflow-hidden border border-[#DBDFD4] relative max-w-[380px] mx-auto"> <div> <div class="md:h-[200px]"> <div class="wistia_responsive_padding" style="padding:56.25% 0 0 0;position:relative;"><div class="wistia_responsive_wrapper" style="height:100%;left:0;position:absolute;top:0;width:100%;"> <span class="wistia_embed wistia_async_q0cnct7mvp popover=true popoverContent=thumbnail object-cover playButton=false"> </span></div></div> </div> <div class="p-[24px] bg-white relative"> <div class="mb-3"> <p class="m-0 text-xs text-nq-forest font-semibold bg-[#DBDFD4] px-[8px] py-[4px] inline-block">Video: Your Prediction Results</p> </div> <div class="mb-3"> <p class=" font-semibold text-nq-forest max-lines max-lines-2 leading-normal"> Your Results </p> </div> <div class=""> <p class="text-sm text-nq-primary leading-normal max-lines max-lines-2 "> Watch now </p> </div> </div> </div> </div> <script src="https://fast.wistia.net/assets/external/E-v1.js" async></script> </div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-49 dnd_area-row-12-padding dnd-section"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-50 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050091789234" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="button-wrapper"> <a class="button" href="https://www.statsols.com/nquery-demo?hsLang=en-us"> Get Started </a> </div></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-51 dnd_area-row-13-padding dnd_area-row-13-max-width-section-centering dnd-section"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-52 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17050090708077" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17050090708077_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h2 style="text-align: center; font-size: 33px;">Frequently Asked Questions</h2></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-53 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500905387211" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> What is nQuery Predict? </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p>nQuery Predict is the latest module to be added to the nQuery platform for clinical trial design.</p> <p>nQuery Predict is a suite of tools that uses current data to project the likely trajectory of future enrollment or event milestones.</p> <p>With the nQuery Predict module, you can make more informed decisions based on real trial data as it becomes available.</p> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-54 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17111237682294" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> How do I take a trial? </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><span style="color: #000000;">You can take a</span> <a href="https://www.statsols.com/nquery-demo?hsLang=en-us" rel="noopener">free 14-day trial of nQuery here.</a></p> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-55 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17111237666114" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> How do I purchase? </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><span style="color: #000000;">nQuery Predict is included in our Expert Tier.</span></p> <p><span style="color: #000000;">In addition to the predict module, you also have access to modules for Bayesian, adaptive trial design, and access to over 1000+ sample size scenarios. </span><br><a href="https://www.statsols.com/nquery/request-a-quote?hsLang=en-us" rel="noopener">You can purchase online here.</a></p> <p><strong><span style="color: #000000;">Have A Question?</span><br></strong><a href="https://www.statsols.com/nquery-sales-faq?hsLang=en-us#question" rel="noopener">You can get in contact with us here.</a></p> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-56 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_17111236706094" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module widget-type-rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><span id="hs_cos_wrapper_module_17111236706094_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="widget" data-hs-cos-type="rich_text"><h2 style="text-align: center; font-size: 33px;">More about the Predictive module in nQuery</h2></span></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-57 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500906155215" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> Predictive modeling in clinical trials </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><strong>What is event prediction in clinical trials?</strong></p> <p>Event prediction is a complex problem in trials, such as those in oncology, that plan to use survival analysis.</p> <p>Key decisions such as when to conduct an interim analysis or when to conduct right-censoring to finish the study are most commonly based on a priori unknown time when a given number of subjects will have had an event rather than based on the fixed follow-up more common in other areas. This means that accurate projections of when event milestones will be achieved are vital to provide realistic estimates of expected timings and costs.</p> <p>nQuery Predict provides tools to project events based on both blinded (where treatment group is unknown) and unblinded (where treatment group is known) using multiple event models (exponential, piecewise, Weibull) and design considerations (e.g. fixed follow-up per subject).</p> <p>What is enrollment prediction in clinical trials?<br>Enrollment prediction (i.e. how long will it take will achieve the desired sample size of patients) is an issue common across all trials and has a direct impact on the administration of a clinical trial. Slower than expected enrollment may mean that further resources may be required or that delays should be expected. These are serious economic considerations, particularly in expensive Phase III clinical trials.</p> <p><strong>Using Simulation for Enrollment and Event Predictions</strong></p> <p>Predicting key clinical trial milestones is vital to ensure that trialists can make informed decisions about study trends and ensure their trials remain on schedule. Trials will often have enrollment trends that vary from initial assumptions, requiring a recalibration of expectations and resources.</p> <p>nQuery Predict gives you the ability to identify roadblocks and take action to keep your trial on schedule.</p> <p><strong>Recommended Viewing:</strong><br><a href="https://blog.statsols.com/new-tool-for-clinical-trial-milestone-predictions?hsLang=en-us" rel="noopener">Predicting Key Study Milestones | Using Simulation for Enrollment and Event Predictions</a></p> <p>You will learn about:</p> <ul> <li>Enrollment and Event Milestone Prediction Issues</li> <li>Using Simulation to Model and Project Enrollment</li> <li>Using Simulation to Model and Project Events in Survival Trials</li> </ul> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-58 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500906155216" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> Predict events using blinded & unblinded data </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><strong>How to predict key events for survival analysis trials using blinded & unblinded data</strong></p> <p>Predicting event milestones is needed to ensure that survival trials remain on schedule for both interim and final analyses. Event prediction requires the consideration of a variety of possible influences alongside the events process itself such as accrual, the follow-up length per patient and dropout. Events prediction is further complicated by the high likelihood of only having access to blinded events data during a confirmatory clinical trial.</p> <p><strong>Recommended Viewing:</strong></p> <p><a href="https://blog.statsols.com/how-to-predict-key-events-in-survival-analysis-trials?hsLang=en-us" rel="noopener">Using Simulation to Predict Events using Blinded & Unblinded Data</a></p> <p>In this webinar, we will discuss the challenges of projecting events and how simulation can help provide the best estimate of the key events milestones using either unblinded or blinded interim data.</p> <p><strong>You will learn about:</strong></p> <ul> <li>Event Milestone Prediction Complications</li> <li>Using Simulation to Predict Events using Unblinded Data</li> <li>Using Simulation to Predict Events using Blinded Data</li> </ul> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-59 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500906155217" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> Predict key events for survival analysis </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><strong>Using simulation to model and project key events in survival trials</strong></p> <p>For survival (time-to-event) analysis, where key milestones relate to the number of events and the effect size, these considerations are even more important and also more complex to model.</p> <p>Recommended Viewing:</p> <p><a href="https://blog.statsols.com/predicting-key-study-milestones-with-simulation?hsLang=en-us" rel="noopener">Using Simulation for Enrollment and Event Predictions</a></p> <p>We discuss the challenges of projecting enrollment and event trends and how simulation can be a powerful tool to assess whether your trial is on track to reach trial milestones on schedule and also model the possible changes needed to get a study back on track.</p> <p>You will learn about:</p> <ul> <li>Using Simulation to Model and Project Events in Survival Trials</li> <li>Enrollment and Event Milestone Prediction Issues</li> <li>Using Simulation to Model and Project Enrollment</li> </ul> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-60 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500906155218" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> Pre-trial and interim trial predictions </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p><strong>Using simulation for Pre-trial and interim clinical trial predictions</strong></p> <p>While pre-trial assumptions are used to project when milestones will occur, it is vital to know if enrollment and survival trends are varying from the pre-trial assumptions. With nQuery Predict, re-evaluation of the trial’s trajectory and required resources can be made on real-time interim predictions.</p> <p>Recommended Viewing:</p> <p><a href="/webinar/intro-to-nquery-predict?hsLang=en-us" rel="noopener">Introducing nQuery Predict | A New Tool for Clinical Trial Milestone Predictions</a></p> <p>We explore the challenges of predicting enrollment and event milestones in clinical trials. We show how nQuery Predict is a new tool for making pre-trial and interim predictions for key trial milestones and the variety of modelling options available for this task.</p> <p>You will learn about:</p> <ul> <li>Enrollment and Event Milestone Prediction</li> <li>Using nQuery Predict for Interim Milestone Predictions</li> <li>Using nQuery Predict for Pre-trial Milestone Predictions</li> </ul> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-61 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_170500906155219" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"> <div class="bg-white faq-item px-3 py-3"> <div class="flex items-center justify-between cursor-pointer faq-question "> <div> <p class="text-[16px] font-semibold text-blue-primary"> Enrollment & event prediction plots </p> </div> <div> <svg class="faq-closed" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M9 3.85254V14.3525M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> <svg class="faq-open hidden" width="18" height="19" viewbox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M3.75 9.10254H14.25" stroke="#152430" stroke-width="2" stroke-linecap="square" stroke-linejoin="round" /> </svg> </div> </div> <div class="hidden faq-answer text-nq-primary text-[16px] prose max-w-full prose-a:text-nq-jade mt-6"> <p>nQuery Predict has plotting tools that allow data to be easily be shared from nQuery to all appropriate trial stakeholders. This allows the team to make informed decisions about what steps to take in their trial.</p> <p><strong>Enrollment Prediction Plot</strong></p> <p>The Enrollment Prediction Plot shows the trend in enrollment up until the Current Calendar Time and the projected average accruals in the trial in future.<br>The enrollment predictions include the average expected accruals and a prediction interval for the enrollment process up to the maximum study length, from all the simulations, based on the Target Sample Size being reached. The prediction interval is based on 5% and 95% percentiles across the simulations at each selected time point.</p> <p><strong>Events Prediction Plot</strong></p> <p>The Events Prediction Plot shows the trend in events (e.g. deaths) up until the Current Calendar Time and the projected average events expected in the trial in future.</p> <p>The events predictions include the average expected number of events and a prediction interval for the events process up to the maximum study length, from all the simulations, based on the Target Events being reached. The prediction interval is based on 5% and 95% percentiles across the simulations at each selected time point.</p> <p><strong>Dropout Prediction Plot</strong></p> <p>The Dropout Prediction Plot shows the trend in dropouts up until the Current Calendar Time and the projected average dropouts in the trial in future.</p> <p>The dropout predictions include the average expected dropout and a prediction interval for the dropout process up to the maximum study length, from all the simulations, based on the Target Events being reached. The prediction interval is based on 5% and 95% percentiles across the simulations at each selected time point.</p> <p><strong>Enrollment Prediction Table</strong></p> <p>The Enrollment Prediction Table contains the trend in accruals up until the Current Calendar Time and the projected average number of accruals in the trial in the future. The Enrollment Prediction Table is used to construct the Enrollment Prediction Plot</p> <p>The enrollment predictions include the average expected number of accruals and a prediction interval for the enrollment process up to the maximum study length, from all the simulations, based on the Target Sample Size being reached. Note this plot does not take account of the case where the Target Events is reached before the Target Sample Size leading to the accrual process ending prematurely. The prediction interval is based on 5% and 95% percentiles across the simulations at each selected time point. A total of 100 data points are used with half for each of the pre and post-Current Calendar Time periods.</p> <p><strong>Recommended Viewing:</strong></p> <p><a href="/webinar/intro-to-nquery-predict?hsLang=en-us" rel="noopener">Introducing nQuery Predict | A New Tool for Clinical Trial Milestone Predictions</a></p> </div> </div> <div class="h-[4px] bg-nq-grey w-full"></div></div> </div> </div> </div> </div> </div> </div> <div class="row-fluid-wrapper row-depth-1 row-number-62 dnd_area-row-14-background-layers dnd_area-row-14-background-color dnd-section dnd_area-row-14-padding"> <div class="row-fluid "> <div class="span12 widget-span widget-type-cell dnd-column" style="" data-widget-type="cell" data-x="0" data-w="12"> <div class="row-fluid-wrapper row-depth-1 row-number-63 dnd-row"> <div class="row-fluid "> <div class="span12 widget-span widget-type-custom_widget dnd-module" style="" data-widget-type="custom_widget" data-x="0" data-w="12"> <div id="hs_cos_wrapper_module_1705008944111" 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