Applying analytical method validation to cell-based potency assays
15th Aug 2024
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Developing an assay for our ADC, SDE-100
The following case study was developed as part of an exemplar project conducted by Sterling’s bioconjugation experts to produce a CD25 specific antibody drug conjugate (ADC) named SDE-100.
SDE-100 is a hybrid ADC which was manufactured to demonstrate our capability to take a novel molecule from process development through to manufacture. Cancerous white blood cells found in leukaemia patients have a high level of CD25 expression. We selected karpass 299 cells for use in this assay, which is a human non-Hodgkin’s large cell lymphoma cell line, that expresses high levels of CD25.
Here, we will describe how Sterling handles a new cell line and the experimental procedure for performing SDE-100’s potency assay. We will then cover our assay development steps, and finally describe Sterling’s assay validation procedure.
Culturing cells for assay
Prior to using the cells in an assay, four weeks were spent culturing the cells and monitoring their growth rate to establish a doubling time. It is important to establish this metric, as the interaction between the cytotoxin, MMAE, and tubulin does not result in cell death until the cell divides or attempts to divide.
It was established that karpass 299 cells’ doubling time took around 30 hours, and required approximately three doublings to generate a significant difference between live and dead cells in order to be readily detected in an assay. Therefore, this period culturing the cells provided information for an initial drug cell incubation time in the early stages of assay development.
During this initial cell culture period, we also prepared a master cell bank and two working cell banks of thaw for use vials. Through using a bank of thaw for use vials, we ensure that cells of the same passage are used for all assays, thereby, reducing inter-assay variability.
Performing cell potency assay
The assay itself was performed using a 96 well plate, with the karpass 299 cells distributed evenly in all wells of the plate. The drug was applied in a concentration series, with a high concentration at the top of the plate and a low concentration at the bottom of the plate. The cells were then incubated with the drug for five days.
After the five-day incubation period, we applied the detection reagent, MTS, a tetrazolium compound. Yellow MTS is reduced to blue purple formazan in the presence of nicotinamide adenine dinucleotide phosphate (NADPH). NADPH is continually produced in mitochondria, the respiratory organelle in living cells, and therefore this reduction and colour change only takes place in live cells. The wells with predominantly dead cells remain yellow, while the wells with predominantly live cells turn blue. After a three-hour incubation we saw a drug concentration-dependent colour gradient from yellow to blue down the plate.
How is this colour change converted to a readout we can analyse?
Blue formazan absorbs light at a wavelength of 490 nm. The number of live cells in each well is in proportion to the amount of formazan, which is also in proportion to the amount of absorbance at 490 nm.
A high level of absorbance is equivalent to a high proportion of live cells in the well, while a low level of absorbance is equivalent to a high proportion of dead cells in the well. By measuring absorbance at 490 nm across the plate, we generated a drug concentration-dependent kill curve or potency curve (see Figure 1). The left side of the curve shows high absorbance readings due to high numbers of live cells when exposed to low drug concentrations. As the drug concentration increases, the number of live cells decreases resulting in reduced absorbance readings. This produces what is known as a sigmoidal dose-response curve.
Figure 1. (left) – Typical sigmoidal dose-response curve showing a reduction in absorbance and, therefore, the number of live cells as the drug concentration increases.
Developing the assay for ADC SDE-100
When developing an assay, a first necessary step is to research the various modes of action associated with an antibody and subsequently, the ADC. Binding to the target may have a cytotoxic effect, perhaps through preventing dimerisation and activation of growth factor receptors. The fragment crystallizable (FC) tail of the antibody may also recruit cytotoxic components of the immune system via antibody dependent cellular cytotoxicity (ADCC), antibody dependent phagocytosis (ADP), or complement dependent cytotoxicity (CDC).
Within the ADC, these cytotoxic effects may be induced in addition to the drug mediated cytotoxicity. It may be necessary to develop a suite of cell-based assays such as ADCC, or CDC assays to test the various modes of action of the ADC. In particular, where a monoclonal antibody has been shown to have a therapeutic effect, it is important to establish that linking this antibody to a cytotoxin does not alter or abrogate those therapeutic modes of action.
Assessing cell death due to intracellular MMAE activity
Here, we will focus on a single potency assay, assessing cell death due to intracellular MMAE activity.
Assessing the literature surrounding a particular ADC and cell type is not only necessary to establish the associated various modes of action, but is also valuable for establishing starting conditions to use in the initial phases of assay development.
An important challenge to overcome when developing a cell assay is biological variation. Sources of variation between cell lines include cell doubling time, antigen density on the cell surface, toxin sensitivity and seeding density. Therefore, when developing a new assay, it is important to optimise incubation time, the length of time the cells are exposed to the drug, cell density, and the concentration series of the drug. The more effectively these variables are defined during the assay development process, the better the quality and reproducibility of the potency curve for a particular assay, and the more accurate and robust the assay will be.
It is also important to clearly define the characteristics of the final potency curve. The criteria Sterling’s experts look for are highlighted in Table 1 below.
Table 1. Required potency curve characteristics
Firstly, the data points themselves must define a curve with the four parameters of an upper and lower asymptote, a linear portion, and an easy to define EC50. There should be a minimum three-fold response difference between the upper and lower asymptotes. It should also be possible to fit a four parameter logistic model to the data with an r-squared of greater than 0.95, indicating a good fit of the raw data to the model.
Finally, to give confidence that the sample and reference are interacting with the cells in the same way, the linear portions of the respective potency curves must be parallel, with parallelism established by both visual inspection and statistical analysis of the curves. Assay parameters that affect these characteristics are as previously described: drug concentration series, drug incubation time, and cell seeding density.
Figure 2 shows a trial of several different drug concentration series applied to cells using an initial fixed cell density and incubation time. As we were able to generate promising potency curves in our initial experiments, this trial demonstrated that the assay we wanted to develop was feasible. It also helped us to establish an appropriate drug concentration series for use in subsequent development steps. In particular, these curves demonstrated a good sigmoidal shape with reasonably well-defined upper asymptote, linear region and lower asymptote.
Figure 2 (left) – Graph shows a trial of several different concentration series
Figure 3 – Trial of different incubation periods and variation in cell density concentration series
Figure 3 looks at the effects of varying incubation periods and cell density. The potency curves on the left show the same drug concentration series applied to varying cell densities for a five-day incubation period. The potency curves on the right show the same drug concentration series applied to varying cell densities for a six-day incubation period.
It is clear the quality of the potency curves after six days is reduced compared to the five-day incubation period. One reason for this could be that after six days, so many cells have died that it becomes difficult to distinguish between live and dead cells in the assay. For this assay, a five-day incubation period was found to be optimal for generating good quality potency curves.
We performed statistical analysis on the five-day curves to determine which was the best quality curve. We focused particularly on the r-squared of each curve to determine which best fit the corresponding data. We also examined the AD ratio, the ratio between the upper and lower asymptotes of the potency curve. We desired the AD ratio to be as high as possible in order to generate data that provided a clear distinction between live and dead cells.
Examining the curves for the five-day incubation, the curve in red presented the best r-squared value, r-squared closest to one, and the highest AD ratio. Following these development steps, the concentration series and cell density were further optimised to generate the final assay that was taken forward to prequalification.
Our cell potency assay did not report absolute potency of each sample, but rather relative potency. In each assay, we test a reference standard and report the potency of each sample relative to this reference.
In the example shown in Figure 4, the reference standard is shown in blue and the control sample, or central potency curve, in purple. The control sample almost perfectly overlays the reference sample.
Figure 4 – Graph showing potencies of low and high DAR concentration series
The graphs show a low drug antibody ratio (DAR) sample in light blue (left) and a high DAR sample in yellow (right). The low DAR sample had a low ratio of drug to antibody and therefore reduced relative potency, which can be seen with the low DAR potency curve shifted to the right compared to control. The high DAR sample had a high ratio of drug to antibody and therefore an increased relative potency, which can be seen with the high DAR potency curve shifted to the left, compared to control.
This data was collected using the final optimised assay setup. This capability to distinguish between high DAR and low DAR samples is another important criterion for potency assays involving ADCs where internalisation and subsequent toxin release is the mode of action. If the assay was not sensitive to DAR, the ADC’s failure to kill the cells would be questioned, as well as whether the assay was an appropriate model for drug activity in vivo.
Cell assay validation
Now, we will explore the validation of the assay, which was performed according to ICH guidelines for a phase one validation.
Figure 5 shows the results for the linearity and range of the assay. Its linearity had statistically significant correlation between nominal and observed relative potencies for all assessments between 50 and 200% relative potency. Accuracy and precision of all data points between 50 and 200% also passed acceptance criteria (shown in Table 2), meaning the assay had a validated range from 50 to 200%.
Figure 5 – Graph showing linearity and range of assay
Table 2 – Table showing accuracy and precision results
Accuracy of the assessments was determined by calculating relative bias, which compares the nominal potency of a particular assessment to the observed potency.
The largest percent relative bias for assessed measurements was 3.3%. This was observed for the 141% assessment, indicating that on average, the observed potency at 141% was 3.3% higher than expected.
Repeatability was determined by measuring relative standard deviation (RSD) across six 100% assessments performed in the same run, with a result of 3.9%.
Intermediate precision was determined over four assessments, performed across two runs, by different operators, using different lots of fetal calf serum in the media, and performed on different days. The percent RSD was 4.5%.
Robustness was determined by comparing relative bias of assessments made using two different cell banks, with the largest percent relative bias at 5.6%.
All these validation criteria: looking at assessment accuracy, variability within a run, between runs, and between different cell banks, passed the validation acceptance criteria.
We also tested system suitability criteria, examining the r-squared for the potency curves, precision of the three replicates measured for each drug concentration, the AD ratio, and the parallelism of the sample and reference curves used to determine relative potency. These system suitability criteria passed the acceptance criteria set for the validation and subsequently were incorporated into the data analysis for sample testing. Data generated using the validated assay must meet these system suitability criteria in order to be acceptable.
Specificity of the assay was examined by comparing relative potency of the ADC, SDE-100, to the relative potency of the lone antibody, HuMax-TAC, and the NAC-quenched toxin linker, vcMMAE.
Figure 6 – Graphs showing potency curves of HuMax-TAC and quenched vcMMAE relative to SDE-100
The potency curves within Figure 6 show that neither HuMax-TAX (yellow), nor NAC-quenched vcMMAE (green), were toxic to the cells across the concentration range tested. The HuMax-TAC control confirmed that the antibody alone did not produce a cytotoxic effect and that the observed cell death was due to the conjugated-toxin. NAC-quenching of vcMMAE produces a charged form of the MMAE toxin which is unable to pass through cellular membranes. The lack of activity for this control shows that the cytotoxic effect occurs as a result of cellular uptake of the toxin-conjugate rather than any extracellular processing or passive uptake of free drug.
Conclusion
This study demonstrates Sterling’s ability to develop and validate a cell-based potency assay to ICH guidelines for the testing and release of a phase I ADC product. This included the selection and banking of a suitable target-expressing cell line; determination of the most appropriate type of potency assay, and optimisation of critical assay parameters such as cell density, drug dilution series and duration of drug exposure. In validating the assay, we proved that the final method is specific to the activity of the ADC, and that neither antibody nor toxin-linker alone exhibit potency. Overall, the data shows that we developed a robust system suitability criterion.
