Integrating antibody–drug conjugate bioanalytical measures using PK–PD modeling & simulation Review
zumab, and established that both proteolytic degrada- tion and deconjugation were responsible for the faster clearance of T-DM1 cf. trastuzumab. Of note, the pro- teolytic clearance of T-DM1 was found to be similar to trastuzumab. Even more complex PK models have also been developed to characterize the plasma PK of TmAb, CmAb and unconjugated drug, where the purpose was either to incorporate the target-mediated drug disposition of ADCs in the model [11,12] and/or to incorporate different DAR components in the model without directly measuring them [11–13]. ADC concentrations reported as CmAb does not
provide quantitation of number of drug molecules attached to mAb. Therefore, ADC concentrations are also reported as conjugated drug concentrations (mostly for cleavable linker) or as the concentrations of
linker). While quantitation of individual DAR spe- cies in plasma is challenging, it has been done for T-DM1 and couple of THIOMABTM
drug conjugates
(TDCs) [6,14]. Mathematical characterization of the PK data from individual DAR provides a unique insight into the behavior of each DAR species and the ADC. Bender et al. [6] have characterized the plasma PK of each DAR species of T-DM1 in rat and monkey using the model shown in Figure 3A. Their model fittings suggested that deconjugation of DM1 from DAR3- DAR7 occurred at a faster rate than the deconjugation from DAR2 or DAR1. DM1 deconjugated 34% faster from DAR3–DAR7 moieties versus DAR2, and DM1 deconjugation from DAR1 was the slowest step in the deconjugation chain with 2.7-times slower deconjuga- tion than DAR2, in cynomolgus monkeys. They also suggested that the different deconjugation rates of DM1 from different DARs also give an impression that the higher DAR species were eliminated faster from the body compared with lower DAR species. Sukuma- ran et al. [14] have characterized the plasma PK of indi- vidual DAR species of MMAE-based TDCs using the model shown in Figure 3B. Since TDCs are site-specific ADCs, mathematical characterization of PK for each DAR species of TDCs provide unique insight into the site of conjugation. Their model fittings revealed that conjugation of MMAE on the light chain is relatively stable, since they found the deconjugation of MMAE from the heavy chain to be four-times faster than the light chain. The results from the model fitting also indicated that the deconjugation rate of drug, clear- ance of total antibody and tumor killing potency of TDCs were directly proportional to DAR.
Tumor PK of ADC The processes involved in plasma-to-tumor exchange of ADCs and released drugs are complex and mostly
future science group Key term
Preclinical-to-clinical translation: Process of translating preclinical discoveries, data and observations into possible clinical outcomes.
nonlinear. Consequently, the plasma concentrations of these analytes do not accurately represent their concen- trations inside the tumor. Thus, in order to establish a reliable exposure–response relationships for ADCs, it becomes important to accurately measure/predict the tumor concentrations of ADC and the released drug. Since measuring the tumor PK of ADC and the released drug in the clinic is extremely challenging, most of the tumor disposition experiments for ADC and the released drug are performed preclinically. Even the preclinical
tumor disposition experiments individual DAR species (mostly for noncleavable
are cumbersome since they often require the use of radiolabeled material for quantitation [15,16]. Neverthe- less, there have been efforts for establishing empirical PK models that can simultaneously characterize the plasma and tumor PK of ADC and its components [17]. Although this kind of empirical fit-for-purpose models serves the purpose of data characterization preclini- cally, their predictive power and value for extrapolating the plasma versus tumor PK relationship to the clinic is limited. As a result, most of the PK modeling efforts for the tumor disposition of ADC has been toward the development of mechanism-based systems model that can a priori predict the concentrations of ADC and the released drug in preclinical and clinical tumors [8,9]. One such PK model developed for characterizing and predicting the PK of ADC and the released drug in plasma and tumor is shown in Figure 4. While this systems model can be very useful for preclinical-to- clinical translation of ADCs and understanding the disposition of ADC and its components [8,9], it requires significant amount of upfront investment from bioana- lytical scientists to quantify chemomeasures and bio- measures that are required to operate the model [18]. However, as mentioned in the ‘Cellular PK of ADC’ section, it is worthwhile to quantify chemomeasures and biomeasures early in the ADC development pro- cess. The model in Figure 4 also requires the plasma PK of ADC and released drug in order to enable the pre- diction of tumor concentrations. Using two different ADCs (i.e., brentuximab-vedotin and A1mcMMAF) it has been preclinically demonstrated that the model is able to a priori predict the tumor concentrations of ADC and the released drug [8,9]. The model has also been successfully used as part of a PK–PD model to predict the progression-free survival and objective response rates of brentuximab-vedotin in the clinic [8]. The sensitivity and pathway analysis of the tumor PK model provides unprecedented insight into the tumor dis-
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