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Record W4289667648 · doi:10.1208/s12249-022-02360-3

Environmental Monitoring for Closed Robotic Workcells Used in Aseptic Processing: Data to Support Advanced Environmental Monitoring Strategies

2022· article· en· W4289667648 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAAPS PharmSciTech · 2022
Typearticle
Languageen
FieldEngineering
TopicIndustrial Vision Systems and Defect Detection
Canadian institutionsEmergent BioSolutions (Canada)
Fundersnot available
KeywordsAseptic processingProcess (computing)Process engineeringComputer scienceEngineeringWaste managementManufacturing engineeringOperations managementMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

The human operator is acknowledged as the greatest potential source of contamination in aseptic processing. To avoid contamination, barrier systems have progressively reduced the amount of human intervention in the critical zone. This study extends the trajectory of enhanced patient safety through the elimination of human intervention in aseptic filling. Eight companies that are users of closed robotic workcells have aggregated their usage data from 2018 to 2021. The study analyzes the critical design elements and performance of the Cytiva SA25 Aseptic Filling Workcell. The SA25 is a standardized, fully closed robotic system for aseptic filling of vials, syringes, and cartridges that eliminates operator intervention in the critical zone. The standardized design means that the system is not modified to suit a particular application and the same environmental monitoring strategy can be used across different installations. The SA25 provides significantly increased sterility assurance when producing sterile injectables. Users have observed non-viable particle levels well within ISO 5/Grade A air requirements, with extremely low probabilities of entering a dosage container. There have been zero cases of microbial growth in more than 250 media fills and good manufacturing practice (GMP) batches. Across all dosage formats and sizes, the aseptic process is repeatable, with more than 99.3% of units meeting acceptance criteria. These data demonstrate that eliminating risk through design is successful in the SA25, with an improved aseptic process in comparison to filling systems using Restricted Access Barrier Systems (RABS) or isolators with glove ports. One of the contributing companies to this article achieved an industry first. The U.S. FDA-approved commercial production of their biologic drugs without the requirement for routine viable environmental monitoring (EM), requiring viable EM only during process simulations. Based on the data presented and planned future research, new regulatory consideration should be made for closed robotic workcells to ensure that regulations meant for previous technologies with different risk profiles are not inappropriately applied.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.301
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it