Evidence map›Paper›PMID 38927846›Full record

ArticleBioengineering (Basel, Switzerland)2024

A Cyber-Physical Production System for the Integrated Operation and Monitoring of a Continuous Manufacturing Train for the Production of Monoclonal Antibodies.

Garima Thakur, Saxena Nikita, Vinesh Balakrishnan Yezhuvath, Venkata Sudheendra Buddhiraju, Anurag S Rathore

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. The 10th Anniversary ofBioengineering (Basel, Switzerland) · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Garima ThakurDepartment of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, Delhi 110016, India.
Saxena NikitaDepartment of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, Delhi 110016, India.
Vinesh Balakrishnan YezhuvathTCS Research, Tata Consultancy Services Limited, Pune 411057, India.
Venkata Sudheendra BuddhirajuTCS Research, Tata Consultancy Services Limited, Pune 411057, India.
Anurag S RathoreDepartment of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, Delhi 110016, India.ORCID 0000-0002-5913-4244

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber-physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs.

Indexed as

automationcontinuous bioprocessingcyber–physical production systemmonoclonal antibodyprocess controlprocess monitoring

Identifiers

PMID38927846
PMCPMC11200404

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.