Evidence map›Paper›PMID 35104168›Full record

ReviewmAbs

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics.

Rahul Khetan, Robin Curtis, Charlotte M Deane, Johannes Thorling Hadsund, Uddipan Kar, Konrad Krawczyk, Daisuke Kuroda, Sarah A Robinson, Pietro Sormanni, Kouhei Tsumoto and 2 more

Abstract readReviewVideo-Audio Media
PubMed Full text at PMC Publisher
In one paragraph

Review in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

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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

12 authors.

Rahul KhetanManchester Institute of Biotechnology, University of Manchester, Manchester, UK.ORCID 0000-0003-1890-0886
Robin CurtisManchester Institute of Biotechnology, University of Manchester, Manchester, UK.ORCID 0000-0001-7745-6362
Charlotte M DeaneDepartment of Statistics, University of Oxford, Oxford, UK.ORCID 0000-0003-1388-2252
Johannes Thorling HadsundDepartment of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
Uddipan KarDepartment of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.
Konrad KrawczykNaturalAntibody, Hamburg, Germany.ORCID 0000-0003-0697-5522
Daisuke KurodaDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.ORCID 0000-0003-2390-4785
Sarah A RobinsonDepartment of Statistics, University of Oxford, Oxford, UK.ORCID 0000-0003-2500-0173
Pietro SormanniChemistry of Health, Yusuf Hamied Department of Chemistry, University of Cambridge.ORCID 0000-0002-6228-2221
Kouhei TsumotoDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Jim WarwickerManchester Institute of Biotechnology, University of Manchester, Manchester, UK.ORCID 0000-0002-1302-0815
Andrew C R MartinInstitute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK.ORCID 0000-0002-2835-2572

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on

Indexed as

Antibodies, MonoclonalBiological ProductsComputer SimulationDrug DiscoveryHumansAntibodies, MonoclonalBiological Productsantibody engineeringbiopharmaceutical informaticscomputational predictiondevelopability assessmentdevelopability guidelinestherapeutic antibodies

Identifiers

PMID35104168
PMCPMC8812776

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.