Cytotoxic drugs are frequently utilized as part of traditional chemotherapy regimens to treat various tumors. While these regimens can be effective against certain types of tumors, the non-specific nature of cytotoxic drugs results in the targeting of both rapidly dividing healthy cells and tumor cells, leading to the side effects commonly associated with chemotherapy. The field of targeted therapy seeks to develop safer and more effective therapeutic agents by exploiting subtle differences between normal and tumor cells. Antibody-drug conjugates (ADCs) exemplify this approach. ADCs consist of three components: an antibody, a linker, and a cytotoxic drug. This combination harnesses the targeting capability of a specific antibody alongside the anti-tumor properties of a cytotoxic drug, allowing for the selective destruction of tumor cells.

However, the complexity of such drugs presents additional challenges in process development, particularly during the critical conjugation step. This step is vital as it influences the efficacy and safety of ADCs, alongside the selection of appropriate antibodies, linkers, and cytotoxic agents. One key factor is the drug-antibody ratio (DAR), which refers to the number of drug molecules attached to each antibody. The DAR can significantly impact the pharmacokinetics, efficacy, and toxicity of ADCs. While a higher DAR may enhance efficacy, it can also increase the risk of potential toxicity due to off-target effects. Conversely, a DAR that is too low may lead to inadequate cytotoxic activity. It is also crucial to maintain consistency in the DAR across the entire ADC batch. Achieving this requires precise control during the conjugation process to ensure that each antibody is conjugated with the appropriate number of drug molecules, typically ranging from 2 to 8 per antibody.

In addition, the control of conjugation chemistry must be carefully considered and thoroughly explored. Reaction conditions such as temperature, pH, solvent composition, and reaction time significantly influence the efficiency and specificity of the conjugation reaction. The selection of the buffer system also impacts the conjugation process, which in turn affects the solubility, stability, and aggregation behavior of the ADC. Optimal buffer conditions are essential to maintain the stability and functionality of the ADC during and after conjugation. These conditions must be optimized to prevent antibody degradation or unwanted side reactions. Furthermore, the conjugation reaction must be efficient enough to achieve a high yield of properly conjugated ADCs while minimizing byproducts such as unconjugated antibodies or free drugs. Additionally, it is crucial to ensure the purity of reagents. The quality of the reagents used in the conjugation process—including antibodies, linkers, and cytotoxic drugs—must be exceptionally high to minimize impurities and ensure the reproducibility and consistency of the final product.

The overall development phase of an ADC conjugation process typically begins with the testing and evaluation of an initial set of process parameters. The foundational knowledge gained during this phase is subsequently followed by more detailed studies. Investigating the effects of reaction parameters on ADC quality attributes enables the design of a tailored process. Given the potentially large number of variable parameters, it is highly inefficient to examine every possible combination of reaction conditions in a single experiment. This “one factor at a time” (OFAT) approach can lead to an unmanageable number of experiments. Conducting a vast number of experiments consumes valuable raw materials, and the time required to run and analyze all of these conjugation experiments can significantly prolong the process development phase, resulting in increased costs and delays in preclinical programs. Furthermore, a single experiment does not provide insights into the interactions between parameters. Therefore, methodologies that achieve the same outcomes with fewer individual experiments are preferred.

Design of Experiments (DoE) is a well-established and reliable method for the systematic investigation of process parameters. The fundamental principle of DoE is to systematically plan experiments within a statistical framework, allowing the results to be extrapolated to unstudied parameter combinations. The effects on the conjugate properties can then be calculated within the investigated parameter range. Since only specific statistically selected combinations are experimentally analyzed, the number of experiments required is significantly reduced compared to the OFAT approach. DoE can only be applied to processes that consistently yield conjugates with defined and measurable quality; only then can the effects of varying parameters be distinguished from those that remain constant. Initial experiments conducted during the development phase should instill confidence that the process itself is sufficiently stable for further investigation using DoE. The next step is to select the parameters to be examined. For most biotechnological production processes, certain choices are clear and valid, such as reaction temperature and time, antibody concentration, and reagent stoichiometry.

Additionally, the pH of the reaction solution, the concentration of buffer salts, the timing of reagent additions, the stirring rate, and numerous other parameters can be considered. Analytical techniques for defining product quality typically include traceable ADC characteristics such as drug-to-antibody ratio (DAR), drug distribution, monomer content, cell-killing activity, and antigen recognition. All of these features can be selected as output metrics in the DoE. In addition, properties of process intermediates, such as the linker-to-antibody ratio (LAR), free thiol-to-antibody ratio, and monomer content, can be evaluated within the DoE of individual process steps. It is crucial that these methods are sufficiently accurate to generate precise data that can be further analyzed using statistical models, enabling the detection of even minor differences in product quality resulting from variations in process parameters.

For projects entering early clinical phases, parameter screening by DoE often yields essential insights into the process. Specifically, it helps identify which parameters significantly influence process outcomes and determines the optimal values for these parameters to achieve the desired product properties. For each selected parameter, both upper and lower limits for investigation must be established. Considerations regarding manufacturability, insights from previous development phases, and relevant literature on related conjugation processes inform the selection of the parameter range.

For the conjugation process, it is essential to study the effects of concentration, pH, modifier stoichiometry, reaction temperature, reaction time, and organic co-solvent content. Parameter screening is employed, and the parameter screening DoE is conducted using a fractional factorial design. For all parameters, set points, as well as lower and upper limits, are defined. The experimental plan randomizes the order of experiments to prevent any unintentional grouping of parameters during laboratory execution. More complex response surface models should be considered when analyzing curvature. To optimally control the studied parameters, appropriate equipment is necessary, such as magnetic stirring devices with temperature control. Additionally, careful attention should be given to selecting a suitable scale-down model that accurately reflects the platform for producing clinical materials in the production workshop.

After all the data from the DoE have been collected, the impact of individual parameter changes, as well as the interactions between multiple parameters, can be analyzed using DoE software. Centerpoint experiments provide a measure of the reproducibility of the process under standard conditions, helping to identify the parameters that significantly affect output properties, such as the LAR and the monomer content of the modified antibody. The DoE approach can also evaluate the effects of individual parameters and combinations of parameters, such as temperature and pH. Typically, the number of statistically significant parameters in the conjugation process is much smaller than the total number of parameters studied. This indicates that only a few parameters determine the success of the conjugation within the selected range, and these inputs must be tightly controlled during the ADC production process. In addition to identifying the parameters or combinations that influence the process outcome, the strength of the DoE approach lies in its ability to infer the process outcome based on unexpected values. When multiple parameters are examined, the resulting DoE dataset can be visualized as a two-dimensional or three-dimensional plot. If the data supports a linear model, a statistical model of the entire process can identify the most suitable set of parameters to achieve the desired output value. Conversely, if the data analysis suggests nonlinear behavior of the process output in response to parameter changes, additional experiments are necessary to develop a response surface model that accurately describes the process.

In order to fully understand the process, it is advisable to screen and refine parameters for each ADC developed. By meticulously controlling key influencing factors, the conjugation process can be optimized to produce high-quality ADCs with desired properties, such as potent cytotoxicity, favorable pharmacokinetics, and minimal off-target toxicity. When time or resources are limited, applying the same conjugation technology to different antibodies allows for the transfer of DoE information obtained from one ADC process to another. This transfer can provide valuable guidance for development direction.

Duoning offers specialized bioprocessing technologies for antibody-drug conjugate (ADC) products, addressing the requirements of various stages from process development to commercial production. We provide a comprehensive platform for single-use product supply, which includes liquid preparation and storage equipment suitable for both laboratory and large-scale production, as well as related fluid management solutions. Additionally, we conduct research and verification on material compatibility and extractable/leachable for specific organic solvents utilized in the process.

DuoMix?/Mini DuoMix? series mixing systems are designed to support a wide range of applications, from 2 to 20 liters for benchtop use to 3,000 liters for production-scale operations. These systems feature powerful mixing capabilities that can quickly achieve homogeneous conditions. Additionally, they offer a variety of impeller structures, and their optimized design minimizes shear stress on the target product. Beyond basic functions such as stirring and weighing, the systems can be optionally equipped with monitoring elements for pH, temperature, and conductivity, as well as auxiliary peristaltic pumps. The DuoMix? and Mini DuoMix? series are compatible with single-use mixing bags made from Duofilm? 001, which can be customized to fit the specific hardware system or process being utilized. This customization ensures that application requirements are met effectively, including buffer preparation and pH adjustment, batch homogenization in chromatography, virus filtration, serving as a recirculating tank in tangential flow filtration, and functioning as a conjugation reaction container under specific conditions.

Mini DuoMix? single-use benchtop mixing system

To better support users in process development and scale-up, and to ensure that the mixing time, shear stress, and other conditions of the selected equipment meet product and application requirements, we can provide targeted application cases and computational fluid dynamics (CFD) data for the equipment. This will make your work easier and more efficient.

CFD simulation diagram of 2,000 L mixing equipment. For more detailed information, please contact our technical support team.

For ADC products, the presence of small molecule cytotoxins can complicate the cleaning validation of process equipment, particularly purification equipment. In this context, Duoning offers single-use purification flow paths, including single-use insert plates for ultrafiltration, to prevent contact between the drug solution and the holder, thereby simplifying the cleaning validation process. Additionally, Duoning provides a comprehensive set of tubing assemblies designed for use with single-use ultrafiltration and chromatography systems, ensuring that all liquid contact materials for the purification process are ready for use and disposable. This approach enhances the safety of personnel and the environment.

Schematic diagram of single-use ultrafiltration assembly and chromatography assembly

In addition, we offer comprehensive filtration solutions, including cartridge filters, disc filters, capsule filters, and hollow fiber filtration modules, all available in a complete range of pore size specifications. Furthermore, for the downstream purification of ADC, our chromatography resins, which are based on various working modes, can be used in combination. These modes include anion/cation exchange and hydrophobic interaction chromatography resins. This product line employs a specialized matrix and modification technology platform to ensure the robustness and reproducibility of the chromatography process.

Reference:

N.Kommineni, P.Pandi, N.Chella, et al., Antibody drug conjugates: Development, characterization, and regulatory considerations. Polymers for advanced technologies, 2020.

S.Tang, C.Wynn, T.Le, et al., Influence of antibody–drug conjugate cleavability, drug-to-antibody ratio, and free payload concentration on systemic toxicities: A systematic review and meta-analysis. Cancer and Metastasis Reviews, 2024.

Y.Matsuda, B.A.Mendelsohn, An overview of process development for antibody-drug conjugates produced by chemical conjugation technology. Expert Opinion on Biological Therapy, 2021.

Y.Matsuda, Z.Tawfiq, M.Leung, et al., Insight into Temperature Dependency and Design of Experiments towards Process Development for Cysteine-Based Antibody-Drug Conjugates. Chemistry Select, 2020.