The problem: candidate data scattered across studies
Biopharma formulation screens produce recipes, target checks and stability data for many candidates. Comparing them is hard when each lives in a different file.
Each candidate has a recipe, development targets and months of stability data, often kept in separate study files. Comparing six candidates means assembling them into one view by hand.
What this demo shows
- Compare candidate recipes side by side.
- Check six candidates against the development targets.
- Plot stability curves for the candidates.
Why it matters
Choosing the right formulation candidate early avoids costly late-stage changes. Side-by-side recipes and target checks make the differences clear.
Plotting stability curves for every candidate together shows which ones hold up over time, using data that stays connected to each recipe.
See it with your own data
This video is part of LIMS for R&D. To see how it would work with your own formulations and records, request a demo. Our team replies within 30 minutes during business hours.
Read the transcript
Eight formulation candidates for the mAb-204 drug product. Which one moves forward? Uncountable keeps every candidate in one platform as a structured record with every excipient and every process step. Side by side, each difference stands out such as L-methionine and twice the polysorbate 80 in F20406. Six candidates side by side. Each result checked against the development targets.
Values outside a limit show in red. Three candidates miss a target. Three meet every one. Now, stability. Compare curves plots SEC-HMW species at 25° over 6 months. One curve for each of five candidates. F20406, the same as F20403, but with twice the polysorbate 80, shows the lowest growth. Formulation, results, and stability connected in one platform.
