All case studies
Case Study
Target evidence mapped from the literature in a day
A discovery scientist maps a target’s published evidence, ligands, mechanisms, and safety signals, into cited tables, compressing early target assessment from weeks to a day.
Pharma & Life SciencesExtract DataResearch AgentAI SearchQuality signals
Instead of a scientist spending two weeks pulling together what the literature says about a target, we get a cited evidence table in an afternoon, and we can see exactly which paper each claim came from.
About
Wei is a principal scientist in discovery biology at a biotech, assessing target rationale and early evidence before programs advance.
The challenge
Early target assessment means synthesizing a large, scattered literature on mechanism, tractability, and safety, fast, and defensibly, so program decisions rest on evidence, not impression. Doing it by hand took weeks per target.
How Paperguide fits
Paperguide extracts and synthesizes what the literature reports about a target into cited, comparable tables, so early assessment is faster without losing traceability. It surfaces published evidence; it does not generate primary data.
In practice
Before a program advances, Wei has to answer a high-stakes question quickly: does the published evidence actually support this target? For something like the reported ligands and inhibitors of HMG-CoA reductase, the relevant evidence, on mechanism, tractability, and safety, is scattered across a large literature, and a scientist pulling it together by hand could spend two weeks per target before the team even has a picture to argue over.
He reframes that as a structured extraction. Pointing Paperguide at the literature, he builds a table where each paper contributes its evidence against the fields that matter, compound or ligand identified, chemical properties, mechanism and selectivity, therapeutic application, with each cell cited to the full text it came from. What the literature reports about the target becomes a comparable, sourced table in an afternoon rather than a fortnight. When he needs to understand a mechanism more deeply or check where studies conflict, the Research Agent investigates across papers and surfaces the disagreements; when a pointed question comes up, like the reported liabilities of a mechanism, a cited answer comes back with sources. Quality signals flag weaker papers before they quietly shape a program decision. Importantly, none of this invents data, Paperguide surfaces and organizes what the published record says, and the traceability means every claim in that assessment can be walked back to its paper.
The benefit is a faster, better-grounded go/no-go: early target evidence assembled in an afternoon instead of weeks, as a cited, comparable table a team can actually interrogate.
Features doing the work here: Extract Data, Research Agent, AI Search, Quality signals.
Results
- Early target evidence assembled in an afternoon rather than weeks
- Cited, comparable evidence tables for program decisions
- Traceability from every claim to its source paper
More case studies
<1 weekfor a 2,000-paper PRISMA review
A 2,000-paper PRISMA review screened and extracted in a fraction of the time, without loosening the criteria.
Read case study6×faster paper analysis
Three separate tools became one workspace, so reading, extracting, and comparing papers happens in a single pass.
Read case study83%faster review across 100 papers
Custom-column extraction across hundreds of nanomedicine papers, every value cited back to its source.
Read case studyStart with a question
Ask something you have been meaning to look into. Paperguide will find the papers, and you can take it as far as the work needs.