Modern antibody development demands analytical workflows that can keep pace with evolving formats and accelerating timelines. Though as modalities grow more complex, traditional platform methods can struggle to deliver the specificity, reproducibility, and speed that teams need for confident decision making.
This article explores how affinity chromatography is becoming a strategic tool for optimizing bioprocess performance and strengthening data integrity across development stages.
Download this article to discover:
- Why affinity chromatography is shifting from a capture step to a driver of process insight
- How engineered ligands support novel modalities like bispecifics, ADCs, and Fab fragments
- Ways to integrate affinity methods into high-throughput workflows for faster, more reliable analytics
Pharma analytics
Article | Protein Analytics
Optimizing Antibody Development:
The Strategic Integration of Affinity
Chromatography
Introduction
Biopharmaceutical manufacturing requires a strong and reliable bridge between a
promising early-stage molecule and a market-ready drug product. The strength of
this bridge depends on the quality and reproducibility of analytical data. In modern
purification, affinity chromatography is no longer merely a capture step; it is a primary
driver of bioprocess performance.1
Effective antibody development benefits from early-stage consideration of analytical
needs. Implementing robust and highly specific affinity methods during the earliest
stages of development streamlines the journey through clinical trials and complex
regulatory filings.
As antibody formats evolve from standard structures to include complex novel modalities
like bispecifics and antibody–drug conjugates (ADCs), traditional platform methods like
Protein A are being supplemented or replaced by more versatile and engineered ligand
technologies. By integrating these specific methods into a unified analytical paradigm,
development teams can achieve the high level of reproducibility, speed, and long-term
confidence required to navigate the inherent complexities of modern bioproduction. This
approach helps ensure that data collected in small-scale laboratories remains relevant
and valid as projects scale to massive production volumes.
This article explores how these advanced analytical strategies, including engineered
ligands and high-throughput workflows, can support more efficient and robust antibody
development from early-stage research to late-stage production.
Watch the complete Teach Me in 10 episode with Dr. Kelly Flook here.
Kelly Flook, PhD,
Senior Product Manager,
BioProduction Group
Kelly Flook, PhD, is a Senior Manager
within the bioproduction product
management team at Thermo Fisher
Scientific, where she leads strategy and
development for advanced analytical
technologies supporting bioprocessing
workflows. With more than 20 years
of experience in chromatography and
bioseparation, Kelly specializes in scalable
solutions for complex biologics, including
monoclonal antibody-based therapeutics
and next-generation vaccines.The basics of affinity chromatography
The process behind affinity chromatography is elegant and
simple, yet capable of achieving high purity in a single step by
following a framework of loading, flushing, and eluting (Figure 1).
The core mechanism relies on the high biological specificity
of a target molecule for an immobilized ligand on a stationary
phase within a column. Unlike other forms of chromatography
that rely on physical properties like size or net charge, affinity
chromatography mimics natural biological interactions, such as
the relationship between an antigen and a target molecule.
Crude samples are often incredibly dirty mixtures containing
thousands of different host cell proteins, lipids, and cellular
debris. However, when a sample is loaded onto the column, only
the target molecule binds to the ligands and is held firmly by
the stationary phase; all other impurities simply flow through the
system and are discarded. Then, by switching the mobile phase
or eluent to a different pH, for example, the target analyte is
selectively released.
As only the target is captured and subsequently released,
the resulting data provides a highly accurate reflection of the
actual titer and bioreactor yield. This helps provide a clean and
reliable baseline for every subsequent analytical step in the
process and reduces the noise that often affects other forms of
protein analysis.
Integrating affinity-based methods for data confidence
While affinity chromatography is a powerful standalone tool,
integrating it into a unified analytical suite allows a holistic
approach toward molecular characterization. High-resolution
techniques, such as size exclusion chromatography (SEC) and
ion exchange chromatography (IEX), are used to characterize
proteins. SEC can measure aggregation and fragmentation, while
IEX profiles charge variants that may impact pharmacodynamics.
These methods can be combined with affinity-based quantitation
to build a comprehensive picture of target biomolecules.2,3
Integration also extends to impurity analysis, such as measuring
residual DNA via quantitative polymerase chain reaction (qPCR)
methods. When these diverse data streams are unified, they
allow reproducible analysis, early-stage decision making, and
cross-site reproducibility, saving time and money in process
development and bioprocessing.
Addressing challenges of novel modalities
The biopharmaceutical industry is rapidly moving beyond
traditional monoclonal antibodies toward much more complex
molecular formats, including ADCs, bispecifics, Fc-fusion proteins,
and Fab fragments. ADCs link a cytotoxic drug to an antibody,
while bispecific antibodies can bind to two different targets
simultaneously.4 Fc-fusion proteins combine a therapeutic protein
with the Fc region of an antibody to improve stability and extend
half-life, whereas Fab fragments consist only of the antigen-binding
region, offering smaller size and improved tissue penetration.5,6
Figure 1. The load, flush, elute workflow of affinity chromatography.
Load Flush Elute
Sample injected onto column
containing target molecule
and impurities
Target binds to the affinity resin in
the column and impurities
flow through
Target is then eluted using
a buffer change, typically,
pH or salt
Immobilized
ligand
Complex Impurities Purified
target
Feedstock
containing impurities
2One of the most widely adopted affinity approaches is Protein A
chromatography, which offers highly selective binding to specific
parts of the Fc region of an antibody.1 While most traditional
antibody-based products contain this region, as researchers
re-engineer molecules to enhance therapeutic design, it is often
altered or entirely removed (Figure 2).
When the primary binding site is lost, Protein A is no longer a
universal platform for all molecules. This shift forces development
teams to look toward alternative domains, such as the light
chain, to find new binding sites that remain intact. Consequently,
a diverse suite of specialized ligands has been developed to
preserve the platform benefits of speed and simplicity, even as
molecular structures become increasingly complex.
The CaptureSelect Ligands from Thermo Fisher Scientific
exemplify this approach, offering selective binding to regions
beyond the Fc domain, that include light chains and Fab
fragments. These ligands help support both purification and
analytical applications, and are available in multiple formats.
Formats include purification bioprocessing resins, packed column
formats suitable for HPLC, and conjugated ligands to support
analytical techniques such as ELISA, SPR, and BLI. Such diverse
formats allow researchers to tailor their approach based on both
the structure of the molecule and the specific analytical objectives.
Supporting high-throughput workflows
and process development
In addition to targeting different antibody regions for analysis,
today’s processes also rely on high-capacity, fast, and robust
columns to keep pace with high-throughput workflows, real-time
decision making, and cross-site reproducibility.
Labs today can generate hundreds of samples every week.
Without reliable solutions, analysis becomes a bottleneck that
affects the entire drug development pipeline. Efficiency in upstream
process development is critical, such as understanding peak
protein concentration during the bioreactor phase. Rapid affinity
analysis provides the quick feedback loop necessary to optimize
these bioreactor processes in real time. Accurate titer from dirty
samples like harvest cell culture fluid (HCCF) requires robust
columns that maintain linearity over a wide concentration range.
Downstream robustness is equally important because the
purification monitoring process generates an enormous volume
of samples that must be processed quickly. As columns handle a
variety of sample types from clarified HCCF to high salt samples
from polishing steps, they must be fast, mechanically stable, and
chemically tolerant so they can be cleaned and reused many
times without frequent clogging or chemical degradation.
High-speed analysis allows teams to identify success or failure rates
immediately rather than waiting days for results, reducing downtime
and helping ensure that expensive manufacturing resources are
only allocated to the most promising drug candidates.
Fab F(ab’)2
Fab Bi-specific IgG containing
kappa or lambda light chain
IgG Fc-fusion protein
CaptureSelect CH1-XL
MabCaptureC
MabCaptureC
V
H
C
H1
C
H2
C
H3
V
L
C
L
CaptureSelect FcXP
CaptureSelect KappaXP
CaptureSelect LambdaXP
Figure 2. CaptureSelect affinity resins for analysis of diverse antibody formats, including Fabs, bispecifics, and Fc-fusion proteins.
3Adapting affinity platforms for emerging modalities
The scope of affinity chromatography is continuing to expand
beyond the traditional antibody space into a much broader range
of therapeutic modalities. As molecules become increasingly
complex, the need for robust and rapid analytical approaches is
driving the adoption of affinity-based solutions, particularly in the
context of at-line or in-line process analytical technology. These
methods allow faster and more informed decision-making during
manufacturing.
This expansion is not limited to antibodies but extends to a wide
range of recombinant and therapeutic proteins, many of which
currently lack established affinity solutions due to the highly
specific nature of ligand–target interactions. As a result, there is
a significant opportunity for growth within the affinity space as
new ligands and technologies are developed to address these
unmet needs.
At the same time, the increasing complexity of molecules further
highlights the value of integrating robust, high-speed analytical
tools directly into production processes. This shift enables
continuous monitoring and supports more efficient and adaptable
manufacturing, reinforcing the role of affinity chromatography as
a key technology in the future of bioprocessing.
References
1. Łącki KM, Riske FJ. Affinity chromatography: an enabling technology for large-scale
bioprocessing. Biotechnol J. 2019;15(1):e1800397. doi: 10.1002/biot.201800397
2. Lambiase G, Inman SE, Muroni M, Lindo V, Dickman MJ, James DC. Highthroughput multiplex analysis of mAb aggregates and charge variants by automated
two-dimensional size exclusion–cation exchange chromatography coupled
to mass spectrometry. J Chromatogr A. 2022;1670:462944. doi: 10.1016/j.
chroma.2022.462944
3. Imiołek M, Fekete S, Rudaz S, Guillarme D. Ion exchange chromatography of
biotherapeutics: fundamental principles and advanced approaches. J Chromatogr A.
2025;1742:465672. doi: 10.1016/j.chroma.2025.465672
4. Shim H. Bispecific antibodies and antibody–drug conjugates for cancer therapy:
technological considerations. Biomolecules. 2020;10(3):360. doi: 10.3390/
biom10030360
5. Rath T, Baker K, Dumont JA, et al. Fc-fusion proteins and FcRn: structural insights for
longer-lasting and more effective therapeutics. Crit Rev Biotechnol. 2015;35(2):235–254.
doi: 10.3109/07388551.2013.834293
6. Chen H, Chen J-S, Paerhati P, et al. Strategies and applications of antigen-binding
fragment (Fab) production in Escherichia coli. Pharm Fronts. 2021;3(2):e39–e49. doi:
10.1055/s-0041-1735145
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