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PK/RO simulator for anti-PD-1 mAbs
Application for the prediction of disposition and target binding in human for therapeutical antibodies against PD-1 receptor.
InSysBio, LLC
Model structure
A lot of PBPK models describing antibodies are published. There are following differences between InSysBio PBPK model of therapeutic antibodies and published models:
- All parameters from published PBPK models were analyzed and revised if there is no strong experimental support:
- Uptake of antibodies by endothelial cells, binding of antibody with FcRn in endosomes (if there is Fc region), recycling of bound antibody, degradation of free antibody in endosomes were calibrated against in vitro data and then translated to in vivo conditions
- Reflection coefficients (perfusion-limited transport)
- Parameters describing endogenous IgG was fitted against data on level of IgG in blood serum and LN were used.
- None of parameters in our PBPK model is fitted against clinical PK data on therapeutic antibodies
- Description of binding of antibody with membrane-bound target – model takes into account number of receptor molecules per cell and number of cells expressing PD-1 receptor as well as two-step binding with PD-1 receptor on the surface of T cell and subsequent internalization of formed complexes
About
PK/RO simulator for anti-PD-1 mAbs is an application that allows to predict pharmacokinetics (PK) and target binding in human for therapeutic antibodies against PD-1 receptor.
The main objective of the project is a prediction of serum/tumor PK profile of therapeutic mAbs as well as target receptor occupancy in plasma and tumor on the basis of:
- Available in vitro data on anti-PD-1 mAb ($Kd$, \(koff\) values)
- Treatment parameters (dose, regimen, etc)
- Patients characteristics (sex, weight, height, body mass index)
The developed minimal PBPK model was successfully tested on the wide panel of anti-PD1 antibodies. Thus, PK/RO simulator may be used as a tool for dose selection of novel antibodies against PD-1 receptor in first-in-human studies.
Contact e-mail: shchelokov@insysbio.com
Application development: dev@insysbio.com
Website: https://insysbio.com