For the complete documentation index, see /llms.txt. The full corpus is available at /llms-full.txt. Most pages have a raw markdown variant; append .md to the URL or send Accept: text/markdown.
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Made in Invert

See what’s possible with your process data.

Explore live examples of analyses and models built in Invert. Some recreate methods from published research; others demonstrate established approaches developed by our data science team. Each shows the complete path from a question to the code, the charts, and a clear finding.

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Process ModelingAugust 12, 2026

Continuous Lyophilization Line Design — Thermolabile mRNA-LNP Vaccine

A mechanistic freeze-drying model (Srisuma et al., Advanced Science 2025) implemented from scratch and used to design a continuous lyophilization line for a room-temperature-stable mRNA-LNP vaccine — mapping the safe drying window, exposing the collapse risk hidden in the fastest recipe, and sizing the chambers at 500 vials/h.

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Digital TwinJune 4, 2026

Richelle et al. (2022) Digital Twin — Model-Based CHO Intensification

A from-scratch implementation of the mechanistic CHO growth model from Richelle et al. (2022) as an executable digital twin — five kinetic parameters identified from fed-batch data, predicting culture dynamics from fed-batch through intensified perfusion.

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Batch MonitoringJune 3, 2026

Real-Time MVDA Batch Monitoring — Raw Material Lot Variability Detection

Multivariate statistical process control detecting an out-of-spec media lot in a 2000 L CHO fed-batch run — a 25-batch Normal Operating Condition reference flags raw-material lot-to-lot variability that passed CoA release.

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Tech TransferJune 2, 2026

PCA Reference Model — SiteB Tech Transfer Comparability

A PCA reference model trained on 84 primary-site runs, then used to project 15 SiteB tech-transfer runs and assess comparability — reference-only training that mirrors validating a model before new runs arrive.

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Golden BatchJune 1, 2026

Golden Batch Comparison: PD-GB vs Campaign Runs

A 1 L golden-batch reference (PD-GB) compared against a 13-run iPSC scale-up campaign from 1 L to 10 L — tracking differentiation-marker trajectories and each run's deviation from the golden profile.

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