Antibody-drug conjugates (ADC) combine the precision of monoclonal antibodies with the potency of cytotoxic agents to deliver targeted therapies with reduced off-target toxicity. With more than 200 ADCs currently in clinical development and 15 FDA-approved therapies on the market, the field has never been more promising or more competitive.
Yet behind this promise lies significant complexity. ADC development is challenged by high attrition rates, intricate design variables, and lengthy development timelines. To overcome these hurdles, researchers are increasingly turning to advanced assay technologies that address traditional bottlenecks and accelerate decision-making.
In this blog, we examine five critical challenges in ADC development and explore how modern assay solutions are helping to solve them.
Challenge 1: Predicting in vivo efficacy from in vitro data
One of the first obstacles in ADC development is bridging the gap between in vitro findings and in vivo performance. Traditional cell viability assays often fail to reflect the full complexity of ADC biology, including target binding, internalization, intracellular trafficking, and payload release. As a result, promising candidates can generate strong in vitro data yet underperform in animal models or clinical trials.
These disconnects carry significant consequences. Late-stage failures consume valuable resources, extend development timelines, and delay patient access to potentially life-saving therapies. In an increasingly competitive landscape, there is growing pressure to de-risk ADC pipelines earlier and make more informed go or no-go decisions.
The solution:
Modern assay technologies are helping close this translational gap by providing more predictive insights during early-stage development. High-throughput screening across diverse tumor cell panels provides a broader understanding of variability in response, while multi-parameter assays allow simultaneous assessment of binding, internalization, and payload delivery within a single experiment.
Computational modeling and advanced analytics are increasingly being used to correlate in vitro datasets with in vivo outcomes, improving candidate selection and reducing the likelihood of costly late-stage failures.
Challenge 2: Understanding internalization kinetics in real-time
Internalization is a critical determinant of ADC efficacy, yet traditional methods typically rely on endpoint measurements. These approaches provide only a snapshot, leaving researchers without visibility into what happens during the crucial hours after an ADC binds to its target. Without real-time insight, important kinetic differences between candidates, as well as the timing of payload release, can easily be overlooked.
For example, two ADCs may demonstrate similar binding profiles, yet exhibit vastly different internalization rates and trafficking behaviors, ultimately leading to different therapeutic outcomes. This limitation becomes particularly problematic when trying to optimize linker chemistry, where decisions depend on understanding when and where payload release occurs. Insights into pH-dependent mechanisms and the precise timing of intracellular release are also essential to ensure that cytotoxic payloads are delivered efficiently and at the right time.
The solution:
Advanced assay technologies now allow researchers to monitor ADC internalization in real time. pH-sensitive reagents, such as pHSense™, allow dynamic tracking of ADC movement through different cellular compartments with varying pH levels. Live-cell monitoring systems can also be used to generate kinetic profiles, offering a clearer picture of how quickly and efficiently ADCs are internalized.
These tools provide a better understanding of endosomal trafficking pathways and the timing of payload release, supporting more informed optimization of linker design and ADC architecture.
Challenge 3: Assessing potency across heterogeneous tumor populations
Although ADCs hold immense promise in solid tumors, antigen expression varies widely both between patients and within individual tumors. This heterogeneity creates a significant challenge in development, as a candidate that demonstrates strong potency against high-expressing cells may prove far less effective in low-expressing populations.
Another level of complexity is added by bystander effects, where cytotoxic payloads released from targeted cells affect neighboring untargeted cells. Without a clear understanding of how ADCs might perform across this spectrum of expression levels, it becomes difficult to define the therapeutic window or predict clinical outcomes across patient populations.
This knowledge gap has direct implications for patient stratification strategies and the development of companion diagnostics, which rely on establishing clear relationships between antigen expression and therapeutic response. Regulatory agencies also expect to see evidence of efficacy across clinically relevant populations.
The solution:
Modern assay approaches allow researchers to evaluate ADC potency across the range of expression levels observed in real-world tumors. Cell panels that represent expression heterogeneity allow candidates to be tested against both high- and low-expressing populations, while assays that can measure both the direct killing of target cells and bystander effects on neighboring cells can capture the full biological impact of ADC activity.
Quantitative methodologies are also being used to define minimum effective antigen thresholds, supporting patient stratification strategies and informing companion diagnostic development.
Challenge 4: Balancing throughput with data quality in early discovery
Early-stage ADC discovery requires the screening of hundreds of antibody-payload combinations to identify the most promising candidates. However, traditional assay workflows can force a trade-off between speed and mechanistic insight. Low-throughput methods can deliver detailed biological data, but are too slow to support modern discovery timelines. Faster screening approaches may increase capacity, but lack the depth needed to make confident decisions. In addition, many traditional assays require specialized equipment or complicated protocols, creating operational bottlenecks that slow the transition from hit identification to lead optimization.
The ability to generate high-quality data early in the pipeline is essential for making informed go or no-go decisions. In today’s competitive landscape, timelines are under immense pressure, and researchers cannot afford to miss the best candidates simply because their screening capabilities are limited.
The solution:
Next-generation assay technologies are eliminating the traditional trade-off between throughput and data quality. Automated, high-throughput platforms paired with standardized workflows enable consistent, scalable screening campaigns. Multiplex assays that generate multiple readouts simultaneously allow researchers to capture binding, internalization, and cytotoxicity data in a single workflow, dramatically accelerating the screening process while gaining valuable insights.
By combining speed with robust, information-rich datasets, these platforms accelerate candidate prioritization and support more confident progression into lead optimization, ultimately improving the efficiency of entire development processes.
Challenge 5: Demonstrating payload delivery and mechanism of action
In ADC development, demonstrating that a candidate kills target cells is only the beginning. Regulatory agencies and scientific reviewers require comprehensive mechanistic data that proves exactly how an ADC achieves its therapeutic effect.
When a candidate underperforms, researchers need to be able to pinpoint exactly where the process breaks down. The failure may occur at the level of target binding, internalization, trafficking, linker cleavage, payload release, or downstream target engagement. This level of information is critical for Investigational New Drug (IND) applications, where regulatory bodies expect detailed evidence of the candidate’s mechanism of action.
The solution:
Advanced assay technologies now allow researchers to map the complete ADC journey, from initial target engagement through internalization, payload release, and final target interaction. This approach provides a step-by-step understanding of ADC behavior within cells.
Orthogonal assay strategies allow confirmation of the mechanism of action of ADCs through multiple independent methodologies, strengthening confidence in findings and supporting regulatory submissions. In addition, modern tools can identify precisely where suboptimal ADCs fail, accelerating troubleshooting and informing decision strategies for next-generation candidates.
The path forward
The five development challenges outlined above are deeply interconnected. Solving one often requires addressing the others simultaneously. Thankfully, the ADC field’s rapid growth is being matched by equally rapid innovation in assay technology, creating new opportunities for researchers to evaluate candidates with multiple approaches, capturing the full complexity of ADC behavior.
With over 200 ADCs currently in clinical development, the winners will be those who can evaluate candidates most effectively and make informed decisions earlier in the pipeline. Modern assay platforms are democratizing access to sophisticated evaluation tools that were once available only to large organizations, leveling the playing field and accelerating innovation across the industry.
The next wave of approved ADCs will likely come from labs that embrace these innovations, leveraging them for more successful ADC development pipelines.
Ready to see how these solutions work in practice? Our on-demand webinar features Revvity scientists demonstrating cutting-edge approaches to ADC evaluation, from pHSense™ internalization monitoring to high-throughput screening strategies.
