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@@ -324,8 +324,7 @@ <h4 class="et_pb_toggle_title">STEP 3: Organising data collection </h4>
 				<h4 class="et_pb_toggle_title">STEP 4: Analysing data </h4>
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 					<p class="paragraph">A template <a href="https://docs.google.com/document/d/177cnfr_AY672qjmbym_1oYXnRJXUjq8Ntrx_4fojrak/edit" target="_blank">Statistical Analysis Plan (SAP)</a> has been developed to align with the ISARIC template protocol and CRF. It can be tailored and used for data analysis.</p>
-					<p class="paragraph">VERTEX employs reproducible analytical pipelines using Python code and currently supports identifying the spectrum of clinical features in a disease and determining risk factors for patient outcomes. New questions will be added by the ISARIC team and the broader scientific community, allowing for the creation and sharing of new pipelines.</p>
-					<p class="paragraph">ISARIC has developed VERTEX, a set of analytic tools designed to perform the analyses outlined in the SAP using ISARIC's data structures. VERTEX generates tables, visualisations, and results using Python code, and displays this information in insight panels, for each relevant research question or study endpoint. See the starting guide on VERTEX insight panels <a href="https://isaricresearch.github.io/Training/insight_panel.html" target="_blank">here</a>.<\p>
+					<p class="paragraph">ISARIC has developed VERTEX, a set of analytic tools designed to perform the analyses outlined in the SAP using ISARIC's data structures. VERTEX generates tables, visualisations, and results using Python code, and displays this information in insight panels, for each relevant research question or study endpoint. See the starting guide on VERTEX insight panels <a href="https://isaricresearch.github.io/Training/insight_panel.html" target="_blank">here</a>.</p>
 					<p class="paragraph">The VERTEX insight panels are built using reproducible analytical pipelines. VERTEX is designed to allow ISARIC members and the broader scientific community to develop, contribute to and share new reproducible analytical pipelines. This will help to broaden the scope of the data analysis tools.</p>
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