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	<title>symbolic AI &#8211; BIOENGINEER.ORG</title>
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		<title>Symbolic AI digital twins predict breast cancer treatment response in trial simulation</title>
		<link>https://bioengineer.org/symbolic-ai-digital-twins-predict-breast-cancer-treatment-response-in-trial-simulation/</link>
		
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		<pubDate>Mon, 26 Oct 2026 17:03:07 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[Cell Reports Medicine]]></category>
		<category><![CDATA[computational modelling]]></category>
		<category><![CDATA[digital twins]]></category>
		<category><![CDATA[Olaparib]]></category>
		<category><![CDATA[PARP inhibitors]]></category>
		<category><![CDATA[PARTNER trial]]></category>
		<category><![CDATA[precision oncology]]></category>
		<category><![CDATA[symbolic AI]]></category>
		<category><![CDATA[treatment prediction]]></category>
		<category><![CDATA[triple-negative breast cancer]]></category>
		<category><![CDATA[University College London]]></category>
		<category><![CDATA[University of Cambridge]]></category>
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					<description><![CDATA[UCL and Cambridge researchers developed a symbolic AI model that built digital twins of 31 breast cancer patients and correctly predicted treatment response in 74% of simulated cases while suggesting alternative targeted treatments for most non-responders.]]></description>
		
		
		
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