Evidence map›Paper›PMID 36569418›Full record

ReviewOrganic process research & development2022

Digital Design of Filtration and Washing of Active Pharmaceutical Ingredients via Mechanistic Modeling.

Sara Ottoboni, Cameron J Brown, Bhavik Mehta, Guillermo Jimeno, Niall A Mitchell, Jan Sefcik, Chris J Price

Abstract readReview
In one paragraph

Review in Organic process research & development, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Sara OttoboniEPSRC Future Manufacturing Hub in Continuous Manufacturing and Advanced Crystallisation, University of Strathclyde, GlasgowG1 1RD, U.K.ORCID https://orcid.org/0000-0002-2792-3011
Cameron J BrownEPSRC Future Manufacturing Hub in Continuous Manufacturing and Advanced Crystallisation, University of Strathclyde, GlasgowG1 1RD, U.K.ORCID https://orcid.org/0000-0001-7091-1721
Bhavik MehtaSiemens Process Systems Engineering Ltd., LondonW6 7HA, U.K.
Guillermo JimenoSiemens Process Systems Engineering Ltd., LondonW6 7HA, U.K.
Niall A MitchellSiemens Process Systems Engineering Ltd., LondonW6 7HA, U.K.
Jan SefcikEPSRC Future Manufacturing Hub in Continuous Manufacturing and Advanced Crystallisation, University of Strathclyde, GlasgowG1 1RD, U.K.
Chris J PriceEPSRC Future Manufacturing Hub in Continuous Manufacturing and Advanced Crystallisation, University of Strathclyde, GlasgowG1 1RD, U.K.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To facilitate integrated end-to-end pharmaceutical manufacturing using digital design, a model capable of transferring material property information between operations to predict product attributes in integrated purification processes has been developed. The focus of the work reported here combines filtration and washing operations used in active pharmaceutical ingredient (API) purification and isolation to predict isolation performance without the need of extensive experimental work. A fixed Carman-Kozeny filtration model is integrated with several washing mechanisms (displacement, dilution, and axial dispersion). Two limiting cases are considered: case 1 where there is no change in the solid phase during isolation (no particle dissolution and/or growth), and case 2 where the liquid and solid phases are equilibrated over the course of isolation. In reality, all actual manufacturing conditions would be bracketed by these two limiting cases, so consideration of these two scenarios provides rigorous theoretical bounds for assessing isolation performance. This modeling approach aims to facilitate the selection of most appropriate models suitable for different isolation scenarios, without the requirement to use overly complex models for straightforward isolation processes. Mefenamic acid and paracetamol were selected as representative model compounds to assess a range of isolation scenarios. In each case, the objective of the models was to identify the purity of the product reached with a fixed wash ratio and minimize the changes to the crystalline particle attributes that occur during the isolation process. This was undertaken with the aim of identifying suitable criteria for the selection of appropriate filtration and washing models corresponding to relevant processing conditions, and ultimately developing guidelines for the digital design of filtration and washing processes.

Identifiers

PMID36569418
PMCPMC9764418

What OpenQuestion holds

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LicenceCC BY
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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.