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Compare Tables for R&D

Compare Tables turns the papers cited in a LeapSpace response into a customizable comparison table. Each study is a row, and you choose the experiment details to compare such as methods, sample size, or outcomes. Every data point links back to the underlying abstract or full text, making it easy to compare and verify evidence side by side.

Run the cross-domain comparison promptopens in new tab/window

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A table you can fall through 

A spreadsheet cell is usually a dead end. A number, a note, a fragment someone typed, with no way back to where it came from. You take it on faith, or you go hunting. 

A Compare Tables row is the opposite. It begins with a door: the source. Open it and you do not get a citation; you get the record: the peer-reviewed paper, its abstract or full text, publisher-neutral, with the methods and results behind it and the author's work alongside. The table is the calm surface. Beneath every row is the trusted scientific corpus. 

Why that matters in corporate R&D 

Your real output is not a summary. It is a recommendation, and someone will challenge it: at a stage-gate, in a regulatory filing, in a patent dispute. When they do, the question is never how fast you got there. It is: show me. 

A recommendation is only as strong as the evidence you can put your finger on. Compare Tables lets you put your finger on it, cell by cell. It reduces manual extraction and organization, but it does not replace a review protocol, study-quality assessment, regulatory requirements or expert judgment. 

We built Compare Tables so the comparison itself stays scientific: every row anchored to the peer-reviewed reference. The specifics that matter — methods, limitations, the granular numbers — drawn from full text documents, capturing the evidence wherever it lives

Andy Albrecht

LeapSpace Sr Product Manager

From a response to a working table

Start with a goal in LeapSpace, a decision to inform, a risk to check, a direction to explore. The response comes grounded in cited sources, and it is those references that flow into the table. Select Explore as a table, and every referenced paper moves into a structured view: one paper per row, with its abstract, methods, results and conclusions already laid out. 

LeapSpace Deep Research - Compare Tables

One paper per row; abstract, methods, results and conclusions in view. Each row shows its source type, and each source is one click from the full record. 

Traceable, cell by cell

You add the columns your decision turns on, in plain language, name the column, describe what it should find, and LeapSpace runs it across every paper at once, up to 15 columns across as many as 70 papers. Ask for a technical risk, a degradation mechanism, a scale-up constraint, a signal of commercial progress, and each paper is read against the same question. 

Cells trace to peer-reviewed abstracts and full text, publisher-neutral. When a paper says nothing on a column, the cell says so, and a blank is a finding of its own: it shows you where the evidence runs out. You sort by date or citation count, filter to full text, hide what you do not need, add papers by identifier or by describing what you are looking for, and remove the rest. When the set is right, export it to CSV for review. The working table is temporary today; saved tables are on the way. 

How to use it, in five steps

  1. State your goal or question in LeapSpace 

  2. Review the cited response, then select Explore as a table.

  3. Add the columns your decision turns on, named and described in plain language. 

  4. Read across the rows. Where a cell is blank, the evidence is missing, and that is worth knowing. 

  5. Add or remove papers, then export to CSV. 

One job, six R&D decisions

The domains change; the job does not. Define the evidence dimensions that matter, then read every paper against the same frame. 

  • Biopharma and CRO/CDMO.  Does a target, mechanism or asset carry enough coherent evidence to advance? Compare model system, biomarker, efficacy signal, safety, limitations. 

  • Medical devices.  Does the evidence support the endpoint or intended-use claim? Compare population, comparator, endpoint, adverse events, study quality. 

  • Energy.  Commit lab, pilot or capital? Compare operating conditions, measured performance, safety, environmental trade-offs, scale-up constraints. 

  • Chemicals and materials.  Which formulation or route survives scale-up? Compare composition, stability, degradation, safety, manufacturability. 

  • Electronics and semiconductors.  Which process or material holds up? Compare process conditions, stressors, failure modes, reliability, qualification evidence. 

  • Vehicles, automotive and aerospace.  Which pathway clears design review? Compare duty cycle, performance, failure mode, certification evidence, scale-up readiness. 

Built on the scientific record

The reason a cell can be trusted to open onto something real is the base beneath it: more than 20 million full-text versions of record, and the Scopus corpus of over 107 million interconnected records from more than 7,000 publishers, publisher-neutral. Not just papers, but the methods, the measurements and the numbers inside them, and the connected record of who found what, and where. Much of what a comparison needs, the methods, the limitations, the granular numbers, lives only in the full text. That is why the table can filter to it. 

Bring the evidence

The R&D teams with the most at stake are not chasing a faster conclusion. They want the evidence, all of it, in a shape they can interrogate and defend. 

Open the tableopens in new tab/window. Then follow any row to its source, and fall through to the science underneath it.

Next steps:

Frequently asked questions