The central claim from a new industry analysis is blunt: as cell therapy programs move from clinical to commercial scale, the process knowledge embedded in experienced hands is routinely being lost during technology transfer — and concurrent staff reductions at contract development and manufacturing organizations (CDMOs) are making the problem worse.

The report, published by Drug Discovery Trends, frames the issue as an operational risk rather than a scientific one. The science of autologous and allogeneic cell therapies is advancing; the difficulty lies in reproducing a process across sites, teams and equipment without the tacit know-how that originally made it work.

What is actually at stake

Cell therapy manufacturing is unusually dependent on operator judgment. Unlike small-molecule or antibody production, many cell therapy processes retain manual steps — cell handling, timing decisions, visual checks — where the difference between a passing and failing batch can rest on technique that lives in an individual's muscle memory rather than in a standard operating procedure.

When a sponsor transfers a process to a CDMO, or a CDMO moves a process between its own sites, that tacit dimension is the first casualty. Documents travel; understanding does not. The analysis identifies repeated failure modes: incoming materials that behave differently at the receiving site, equipment qualification gaps, and process drift that only becomes visible in potency or viability metrics weeks after the transfer team has dispersed.

The staffing connection

The second half of the problem is structural. CDMOs across the sector have been trimming headcount as they consolidate capacity after a period of aggressive expansion. The people being cut are frequently the process development scientists and senior operators whose expertise would normally anchor a transfer. The result is a shrinking pool of institutional knowledge at precisely the moment more programs — CAR-T, TIL, stem-cell-derived and iPSC-based therapies among them — are approaching commercial-scale production demands.

For R&D and manufacturing leaders, the practical consequences land in three places. First, transfer timelines slip, because receiving teams must re-learn what departing staff never documented. Second, comparability exercises get harder and more expensive when a process has drifted during the handover. Third, regulatory filings that depend on demonstrated process control across sites face delayed review questions that trace back to undocumented process behavior.

What the analysis suggests sponsors do

The report points to mitigations that are demanding but not novel: capture tacit knowledge deliberately, before a transfer begins, through structured interviews, video documentation of critical manual steps and paired working between outgoing and incoming teams. It also argues for earlier CDMO engagement — involving the receiving site's staff in process development decisions well before the transfer window opens — and for contracts that explicitly budget for knowledge-retention activities rather than treating them as overhead.

These measures carry cost. Sponsors already under margin pressure may resist funding documentation sprints on top of tech transfer fees. The analysis makes the counter-argument without quantifying it: a failed or repeated engineering run at commercial scale costs substantially more than the months of knowledge capture that would have prevented it.

Open questions

The report is an industry perspective rather than a controlled study, and readers should weigh it accordingly. It names no specific sponsors, CDMOs or programs, provides no aggregate figures on transfer failure rates, and does not break down whether the problem is worse for autologous platforms — where batch-to-batch variability is inherent — than for allogeneic processes with more room for automation. Those distinctions matter for portfolio decisions, since the cost of knowledge loss scales differently across modalities.

What is clear is the direction of travel. Cell therapy pipelines are growing, CDMO capacity is being rationalized, and the two trends are converging on the same bottleneck. Companies that treat process know-how as a transferable, documentable asset — rather than an assumed one — will be better positioned as the sector scales.