Evidence map›Paper›PMID 39688343›Full record

ArticleBiotechnology and bioengineering2025

Kinetic Modeling of the Antibody Disulfide Bond Reduction Reaction With Integrated Prediction of the Drug Load Profile for Cysteine-Conjugated ADCs.

Jan Tobias Weggen, Pedro González, Kimberly Hui, Ryan Bean, Michaela Wendeler, Jürgen Hubbuch

Abstract read
In one paragraph

Article in Biotechnology and bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Methods for Conjugating Antibodies with Quantum Dots.Molecules (Basel, Switzerland) · 2025
    Review
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

6 authors.

Jan Tobias WeggenInstitute of Process Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Baden-Württemberg, Germany.ORCID 0000-0002-9049-6868
Pedro GonzálezInstitute of Process Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Baden-Württemberg, Germany.
Kimberly HuiPurification Process Sciences, Biopharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Ryan BeanPurification Process Sciences, Biopharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA.
Michaela WendelerPurification Process Sciences, Biopharmaceutical Development, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA.ORCID 0000-0001-7503-5257
Jürgen HubbuchInstitute of Process Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Karlsruhe, Baden-Württemberg, Germany.ORCID 0000-0003-0839-561X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibody-drug conjugates (ADC) constitute a groundbreaking advancement in the field of targeted therapy. In the widely utilized cysteine conjugation, the cytotoxic payload is attached to reduced interchain disulfides which involves a reduction of the native monoclonal antibody (mAb). This reaction needs to be thoroughly understood and controlled as it influences the critical quality attributes (CQAs) of the final ADC product, such as the drug-to-antibody ratio (DAR) and the drug load distribution (DLD). However, existing methodologies lack a mechanistic description of the relationship between process parameters and CQAs. In this context, kinetic modeling provides comprehensive reaction understanding, facilitating the model-based optimization of reduction reaction parameters and potentially reduces the experimental effort needed to develop a robust process. With this study, we introduce an integrated modeling framework consisting of a reduction kinetic model for the species formed during the mAb reduction reaction in combination with a regression model to quantify the number of conjugated drugs by DAR and DLD. The species formed during reduction will be measured by analytical capillary gel electrophoresis (CGE), and the DAR and DLD will be derived from reversed-phase (RP) chromatography. First, we present the development of a reduction kinetic model to describe the impact of reducing agent excess and reaction temperature on the kinetic, by careful investigation of different reaction networks and sets of kinetic rates. Second, we introduce a cross-analytical approach based on multiple linear regression (MLR), wherein CGE data is converted into the RP-derived DAR/DLD. By coupling this with the newly developed reduction kinetic model, an integrated model encompassing the two consecutive reaction steps, reduction and conjugation, is created to predict the final DAR/DLD from initial reduction reaction conditions. The integrated model is finally utilized for an in silico screening to analyze the effect of the reduction conditions, TCEP excess, temperature and reaction time, directly on the final ADC product.

Indexed as

Antibodies, MonoclonalCysteineDisulfidesImmunoconjugatesModels, ChemicalKineticsOxidation-ReductionAntibodies, MonoclonalCysteineDisulfidesImmunoconjugatesantibody‐drug conjugate (ADC)capillary gel electrophoresis (CGE)cysteine conjugationinterchain disulfideskinetic modelprocess developmentreduction reaction

Identifiers

PMID39688343
PMCPMC11808428

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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.