Evidence map›Paper›PMID 32663581›Full record

ArticleInternational journal of pharmaceutics2020

Design of condition-based maintenance framework for process operations management in pharmaceutical continuous manufacturing.

Sudarshan Ganesh, Qinglin Su, Le Bao Dan Vo, Nolan Pepka, Benjamin Rentz, Lucas Vann, Nima Yazdanpanah, Thomas O'Connor, Zoltan K Nagy, Gintaras V Reklaitis

Abstract read
In one paragraph

Article in International journal of pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

10 authors.

Sudarshan GaneshDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: sudarshan.ganesh@gmail.com.
Qinglin SuDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: ql_su@live.cn.
Le Bao Dan VoDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: baodan.897@gmail.com.
Nolan PepkaDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: npepka13@gmail.com.
Benjamin RentzDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: benrentz@gmail.com.
Lucas VannApplied Global Services, Applied Materials, Inc., Santa Clara, CA, USA. Electronic address: lucas_vann@amat.com.
Nima YazdanpanahOffice of Pharmaceutical Quality, Center for Drug Evaluation Research, Food and Drug Administration, Silver Spring, MD, USA. Electronic address: nima.yazdanpanah@fda.hhs.gov.
Thomas O'ConnorOffice of Pharmaceutical Quality, Center for Drug Evaluation Research, Food and Drug Administration, Silver Spring, MD, USA. Electronic address: thomas.oconnor@fda.hhs.gov.
Zoltan K NagyDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: znagy@purdue.edu.
Gintaras V ReklaitisDavidson School of Chemical Engineering, Purdue University, 480 Stadium Mall Drive, West Lafayette, IN, USA. Electronic address: reklaiti@purdue.edu.

Funding

FDA HHS U01 FD006487
6 · The paper itself

Abstract

Continuous manufacturing, an emerging technology in the pharmaceutical industry, has the potential to increase the efficiency, and agility of pharmaceutical manufacturing processes. To realize these potential benefits of continuous operations, effectively managing materials, equipment, analyzers, and data is vital. Developments for continuous pharmaceutical manufacturing have led to novel technologies and methods for processing material, designing and configuring individual equipment and process analyzers, as well as implementing strategies for active process control. However, limited work has been reported on managing abnormal conditions during operations to prevent unplanned deviations and downtime and sustain system capabilities. Moreover, although the sourcing, analysis, and management of real-time data have received growing attention, limited discussion exists on the continued verification of the infrastructure for ensuring reliable operations. Hence, this work introduces condition-based maintenance (CBM) as a general strategy for continually verifying and sustaining advanced pharmaceutical manufacturing systems, with a focus on the continuous manufacture of oral solid drug products (OSD-CM). Frameworks, such as CBM, benefit unified efforts towards continued verification and operational excellence by leveraging process knowledge and the availability of real-time data. A vital implementation consideration for manufacturing operations management applications, such as CBM, is a systems architecture and an enabling infrastructure. This work outlines the systems architecture design for CBM in OSD-CM and highlights sample fault scenarios involving equipment and process analyzers. For illustrative purposes, this work also describes the infrastructure implemented on an OSD-CM testbed, which uses commercially available automation systems and leverages enterprise architecture standards. With the increasing digitalization of manufacturing operations in the pharmaceutical industry, proactively using process data towards modernizing maintenance practices is relevant to a single unit operation as well as to a series of physically integrated unit operations.

Indexed as

Pharmaceutical PreparationsTechnology, PharmaceuticalAutomationDrug IndustryPharmaceutical PreparationsContinued process verificationContinuous manufacturingMaintenanceManufacturing operations managementOral solid doseProcess monitoringSystems integration

Identifiers

PMID32663581
PMCPMC9912015

What OpenQuestion holds

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Registered trials

None linked

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.