New pipeline graphs integrate preclinical research and competitive insights with single AI platforms to accelerate drug target identification and enhance commercial success
London, June 24, 2025 /prnewswire/ – Causality today released a pipeline graph, giving the Life Sciences research and development team a more effective and efficient way to provide competitive intelligence early in drug discovery. AI-powered applications allow scientists to actively find and access competitive insights while assessing viable drug targets, allowing them to make confident pipeline decisions faster before investing in costly drug development programs.
Pipeline Graph is based on the industry's most advanced AI platform for scientific discovery and other recent innovations. Causal relationships link 500 million facts and 70 million directional relationships across eight relationship types in the knowledge graph, adding over 4 million data points each month. Pipeline graphs now extend drug discovery research beyond biomedical information to include competitive intelligence beyond biomedical information. There is a single platform that fits all scientists' existing workflows.
Nowadays, scientists often rely on external teams for insight, or fragmented, competitive intelligence spreads across cut tools, so extensive manual effort is needed to find relevant information. Existing databases overwhelm users with data, have coverage gaps for new targets, and lack timely updates. Without a central hub, critical insights remain buried in presentations and emails, making effective communication from scientists to leadership time and inefficient.
“The industry is forced to settle for competitive intelligence products that lack AI innovation and require too much manual effort,” says Yiannis Kiachopoulos, co-founder and CEO of Causality. “Pipeline graphs provide scientists with AI-Native applications specifically built for life sciences that bring competitive intelligence to preclinical research. We aim to help teams access unstructured, unstructured data for complete biomedical and competitive information that accelerates market discovery.
Pipeline graphs eliminate outdated tools by embedding competitive intelligence into the same causal AI platforms that scientists already use in their research. Analyses powered by scientific evidence, pipeline data, safety, efficacy insights, and AI are combined into one platform of sources such as scientific literature, clinical trials, news, websites, and more. This allows scientists to quickly connect dots between target identification and commercial viability.
Pipeline graphs are now available July 2025. To learn how scientists can bring competitive intelligence to the early drug discovery process, request a demonstration and sign up for upcoming pipeline graph webinars.
Causal relationship
Causality is the AI leader in life sciences. Leading biopharmaceutical companies use causal AI platforms to discover, visualize, interpret biomedical knowledge and automate critical research workflows. To learn how causality can promote causality through transformative AI technology and make patients more efficient in receiving critical care, visit www.causaly.com.
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