From complexity to clarity: How a scientist accelerates target validation with Causaly
From complexity to clarity: How a scientist accelerates target validation with Causaly
Challenges before Causaly
In the high-stakes world of drug discovery, identifying and validating new targets is not just complex, it is a critical step in ensuring promising science translates into real therapies. For a scientist, that task means assessing mechanistic relevance, safety signals, and the strength of supporting evidence, to be able to link targets to diseases, and prioritize with confidence.
Causaly solutions
From a long list to the right list: Unmet needs and opportunities for disruption
This neurological researcher begins with a set of potential targets identified from literature and internal findings. Her challenge now? Validating which ones have the mechanistic and safety profile to pursue.
Using Causaly Discover, she’s able to to uncover the most relevant information around target biology and shift through the most recent publications.
Diving into relationships with Bio Graph
From there, she turns to Causaly Bio Graph to dig deeper. With Bio Graph, she evaluates whether these targets play a credible role in disease biology, linking them to relevant pathways, molecular mechanisms, and known side effects. This visual exploration helps her make smarter, faster decisions about which targets to advance - and which to leave behind.
Understanding the market landscape
She also needs to stay on top of the competitive landscape. In validating a target, understanding its competitive saturation is essential. With Causaly, she benchmarks how well-characterized a target is, what compounds are in development, and where white space remains. With Causaly, she can quickly surface relevant literature, clinical trial data, and emerging research trends to benchmark against competitors and avoid duplication.
Deep analysis without the bottlenecks
The real power of Causaly, she says, lies in its ability to streamline the discovery and validation process. BioGraph reveals deeper layers of biology behind each target, letting her assess relevance, supporting evidence, and risk, all in one place. What used to take hours of cross-checking now takes minutes, with higher confidence. Then she quickly moves on to assess the market opportunity, in light of the competitor landscape. All within a single interface. Instead of stitching together fragmented data from multiple tools, she gets a unified, high-confidence view.
Faster decisions, stronger science
Speed is critical when managing a pipeline, and Causaly delivers. The researcher experiences significant time savings, allowing her to focus on high-value scientific thinking rather than manual literature reviews.
One feature she particularly values is the ability to quickly extract key, supporting sentences within relevant literature citations. This transparency gives her confidence in the findings and makes it easy to back up decisions with evidence.
She also praises Causaly’s data visualization and prioritization capabilities, noting how easy it is to extract insights from robust graphical representations grounded in peer-reviewed literature and other relevant data sources.
De-risking discovery
With Causaly, this researcher is transforming how her team evaluates neurological drug targets; filtering high-risk candidates and focusing resources where biology and evidence align. By using the Causaly product suite to search, review and drill deep into potential new targets, she’s able to confidently prioritize the most promising opportunities, thereby reducing risk and accelerating progress through the pipeline.
Causaly is a much better way of seeing the information as well as the bigger picture - instead of reviewing only a few papers and only seeing connections if you get lucky.
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