Review Khot, Sharma & Shah Key term
Model-based drug development: Process where go/no-go decisions regarding drug development are made with the help of simulations performed using PK–PD models.
to be depletable and the other was not. Contrary to the findings of Mugundu et al. for inotuzumab ozo- gamicin, Bender et al. discovered that an individual patient’s toxic response to T-DM1 could not be pre- dicted a priori based on that patient’s baseline charac- teristics. They were also able to use the PK-TD model to perform clinical trial simulations, based on which they concluded that: patients with the downward drifting of platelet–time profiles will be stabilized by the eighth treatment cycle to platelet levels above grade 3 throm- bocytopenia, the dosing regimen of T-DM1 given at 3.6 mg/kg every 3 weeks is safe regimen for patients with HER2-positive breast cancer, and this regimen necessitates minimal dose delays and reductions due to clinically significant thrombocytopenia [30]. Thus, the PK–TD M&S confirmed the optimized clinical dosing regimen of T-DM1. In spite of above-mentioned successes in quantita-
tively characterizing the toxicity of ADCs, our basic understanding about the determinants of ADC tox- icity still remains incomplete. Additionally, clinical attrition of ADCs due to unexpected toxicities remains high [31]. One of the major reasons behind this is the lack of clarity regarding what induces the toxicity of a given ADC. Is it on-target toxicity due to the spe- cific uptake of ADC into target expressing non-tumor issues or off-target toxicity due to nonspecific uptake of circulating ADC or unconjugated drug molecules into certain tissues? Use of PBPK–TD model can help resolve this problem [19,20], by providing an opportu- nity to account for the relative expression of the target antigen on tumor and nontumor issues, and allow- ing one to use tissue specific concentrations of differ- ent analyte to correlate with the toxicity. Addition- ally, since PBPK models are amicable to interspecies translation, PBPK–TD models can be established pre- clinically using animal models and then used to guide preclinical-to-clinical translation of ADCs. Another reason for the toxicity-related failures is the lack of reliable biomarkers that can accurately represent ADC toxicity. For example, it is very hard to assess the dura- tion and extent of ADC-related ocular toxicity due to the lack of reliable biomarkers. Thus, there is an urgent need for the collaboration between bioanalyti- cal scientists and pharmacologist for the development of sensitive and clinically reliable toxicity biomarkers for ADCs. Lastly, the inherent ability of the ADCs to present unique toxicities that are not expected based on individual components of the molecule is an additional
1646 Bioanalysis (2015) 7(13)
reason for our failure to predict ADC-related toxicities. As such, significant amount of novel scientific investi- gations are needed going forward to better comprehend and quantitatively integrate toxicities of ADCs.
Conclusion Bioanalytical data required to understand the PK and PD behavior of ADCs is numerous, complex and mul- tidimensional. While good quality bioanalytical data are enough to draw primary conclusion regarding PK and PD behavior of ADCs, it is imperative to integrate the diverse data generated from various experiments at different stages of ADC development under a common platform, to fully comprehend the PK–PD behavior of ADCs. PK–PD M&S serves as this common platform that enables simultaneous quantitative integration of all the bioanalytical data to enable rational and well informed decision making at each stage of ADC devel- opment. As highlighted in this manuscript, PK–PD M&S can help identify differential stability of different drug conjugation sites, can help triage different linkers based on their in vitro and in vivo stability and can also help identify ideal properties of promising drug mol- ecules. PK–PD M&S can help establish a robust and quantitative relationship between ADC exposure and its efficacy/toxicity preclinically, and can also enable successful clinical translation of these relationships. Lastly, PK–PD M&S can help optimize clinical dosing regimen of ADCs so as to realize the largest possible therapeutic index in the clinic, and can also help pre- dict DDIs of ADCs in the clinic. In sum, integration of bioanalytical measurements using PK–PD M&S is not an option but a necessity for successful development of ADCs.
Future perspective Although there are more than 50 ADCs tested in the clinic so far, our experience with ADCs is still limited. Most of the information about clinical exposure, effi- cacy, and toxicity of ADCs is not in the public domain, which makes it difficult to generalize ADME and phar- macological properties of ADCs. Additionally, most of the ADCs in the clinic have employed only few selec- tive drug-linkers, which makes generalization about the PK/PD/TD behavior of the ADCs premature. How- ever, the number of ADCs in the clinic and the combi- nation of different drug-linkers employed for construct- ing ADCs are bound to increase in near future. With the increasing number of ADC molecules one would have to establish quantitative relationships between the different properties of ADC components (i.e., mAb, linker and drug) and overall PK, PD and TD behavior of the ADCs. Additionally, considering the complexity of ADC molecules, it will be a necessity to impart the
future science group
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