Molecular farming is biology at industrial scale. Constructs, host lines, growth conditions, and harvest yields all matter, and the value of a program lives in the genealogy connecting them. LabRelations builds LIMS for that work: constructs, host lines, growth conditions, harvest batches, extraction lots, and purification trains all linked through one genealogy. Each batch carries its full history forward, including the experiments that informed it.
QMS sits alongside as programs mature toward regulated production: documents, SOPs, deviations, change control, and CAPA. CTMS comes into play when products move into the clinic. Each system is designed for the team using it (process scientists in LIMS, QA in QMS, clinical ops in CTMS), sharing the same genealogy underneath when programs need them to.
LIMS for the science and the scale-up. QMS as programs mature. CTMS when trials start. Used independently. Connected when programs move between.
Constructs, host lines, batches, harvests, extracts, and purified material are each registered as objects with parent-child links. A change at any point in the chain (new construct, new growth condition, new purification step) is captured against the batch it affected. The genealogy is queryable end to end.
Greenhouse and growth-room batches are registered with conditions, dates, lots, and operators. Harvests link back to growth runs. Extraction and purification lots link back to harvests. Every step carries its inputs and outputs forward.
Documents, SOPs, deviations, change control, training, supplier qualification, and CAPA. Light enough to start before full GxP, deep enough to scale into manufacturing prep without re-platforming.
No. Compliance controls turn on when the program needs them. R&D can run without electronic signatures and lock-step approvals. When the program reaches the stage where they're needed, you turn them on and existing data carries over.
CTMS and EDC are available on the same platform when programs move into the clinic. Until then, they're just not part of the picture.
Every change (a new media, a new harvest schedule, a new purification step) is captured against the batch where it was first applied. Historical batches stay intact. Comparing performance across changes is a query, not a spreadsheet exercise.
A mix of people who've actually worked in the industry supported by technical people for configuration needs inside the platform itself.
