Evidence map›Paper›PMID 31376048›Full record

ArticleThe AAPS journal2019

TCPro: an In Silico Risk Assessment Tool for Biotherapeutic Protein Immunogenicity.

Osman N Yogurtcu, Zuben E Sauna, Joseph R McGill, Million A Tegenge, Hong Yang

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 2 institutions in 1 country.

Osman N YogurtcuOffice of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
Zuben E SaunaOffice of Tissues and Advanced Therapy, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
Joseph R McGillOffice of Tissues and Advanced Therapy, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
Million A TegengeOffice of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA.
Hong YangOffice of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, US FDA, 10903 New Hampshire Ave, Silver Spring, 20993, Maryland, USA. Hong.Yang@fda.hhs.gov.
Center for Biologics Evaluation and Research · USUnited States Food and Drug Administration · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most immune responses to biotherapeutic proteins involve the development of anti-drug antibodies (ADAs). New drugs must undergo immunogenicity assessments to identify potential risks at early stages in the drug development process. This immune response is T cell-dependent. Ex vivo assays that monitor T cell proliferation often are used to assess immunogenicity risk. Such assays can be expensive and time-consuming to carry out. Furthermore, T cell proliferation requires presentation of the immunogenic epitope by major histocompatibility complex class II (MHCII) proteins on antigen-presenting cells. The MHC proteins are the most diverse in the human genome. Thus, obtaining cells from subjects that reflect the distribution of the different MHCII proteins in the human population can be challenging. The allelic frequencies of MHCII proteins differ among subpopulations, and understanding the potential immunogenicity risks would thus require generation of datasets for specific subpopulations involving complex subject recruitment. We developed TCPro, a computational tool that predicts the temporal dynamics of T cell counts in common ex vivo assays for drug immunogenicity. Using TCPro, we can test virtual pools of subjects based on MHCII frequencies and estimate immunogenicity risks for different populations. It also provides rapid and inexpensive initial screens for new biotherapeutics and can be used to determine the potential immunogenicity risk of new sequences introduced while bioengineering proteins. We validated TCPro using an experimental immunogenicity dataset, making predictions on the population-based immunogenicity risk of 15 protein-based biotherapeutics. Immunogenicity rankings generated using TCPro are consistent with the reported clinical experience with these therapeutics.

Indexed as

AntibodiesAntigen-Presenting CellsCell ProliferationComputer SimulationDrug DevelopmentHumansProteinsRisk AssessmentT-LymphocytesAntibodiesProteinsanti-drug antibodies (ADA)computational approachesimmunogenicityprotein-based therapeutics

Identifiers

PMID31376048
OpenAlexW2965917512

What OpenQuestion holds

Textmetadata
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.