Q: How about solid tumor?
A: Solid tumor can be in leaky and tight tissue.
Q: With only plasma data - would anyone on the panel comment on challenges a modeler may encounter in terms of parameter identifiability, and strategies to pursue for validating model use in the fast development process of a drug?
A: Numerical results demonstrated that, for this minimal PBPK model, vascular reflection coefficients for both tight and leaky tissues (sigma 1 and sigma 2) as well as clearance of the drug can be reliably estimated by using only plasma data. However, due to the simplifying assumption made in this model, it may not be able to address some mAb PK problems such as predicting mAb distribution in a specific tissue and assessing the role of FcRn binding affinities. These questions may be answered by using a full PBPK model. However, to have a proper calibration of such model, tissue data may be required. In addition, one may often has too little data to fit such model due to the large number of parameters involved. To partially alleviate this issue, sensitivity analysis may be used to identify the parameters to which the model outputs are most sensitive. One then only estimates the most sensitive ones with the values of the rest of them fixed as those given in the literature (if available) or using the previously estimated ones through an iterative procedure. Morevoer, to have a reliable estimate of parameters, optimal design methods such as D-optimal and E-optimal may be used to provide a guide on the design of the experiments to collect informative data.
Q: Did you try to model mAb PK in CYNO and use minimal PBPK to scale and predict PK in Human?
A: No, we have not tried.
Q: Can you comment on fitting data for mABs showing nonlinear PK due to TMDD?
A: TMDD for mAbs should be done once having ligand binding data as well as PK in the dose range that enables one to see the distinctive TMDD profile (bending down and then back).
Q: Why the same Cli is used for both tight and leaky tissue?
A: This is a model assumption.
