Director, US Head of Translational PKPD Modeling Johnson & Johnson Harleysville, Pennsylvania, United States
Disclosure(s):
Meghan M. Pryor: No relevant disclosure to display
Objectives: Utilizing data that can be efficiently generated to triage and prioritize compounds plays a crucial role in optimizing PROTACs in discovery. To streamline this process, we leveraged minimal PKPD models to enable early decision-making. While sophisticated ternary complex models for PROTACs have been published, the focus of this work is to apply a minimal PKPD model that supports the low data environment of early discovery efforts. Typical early information for a PROTAC includes parameters that describe maximal protein of interest (POI) reduction (Dmax) and the concentration to reach half-maximal reduction in the POI (DC50). These parameters can be estimated from in vitro exposure response data. Understanding the relationship of these parameters to more commonly used kinetic model parameters describing the maximal increase in POI degradation rate (Emax) and concentration of half-maximal increase in POI degradation rate (EC50) enables early prioritization of the most promising compounds to progress into more resource intensive in vivo efficacy studies.
Methods: We derive a relationship between the kinetic model parameters EC50 and Emax and the in vitro parameters, DC50 and Dmax. Relationships for 4 key POI-related parameters of interest are derived from the indirect effect model equation assuming drug concentrations are maintained for sufficiently long: (1) the reduction in the POI when drug concentrations give half-maximal increases in degradation rate (Css = EC50) , (2) the maximal reduction in the POI achievable (Dmax), (3) the drug concentration required to achieve half-maximal reductions in the POI (DC50), and (4) the drug concentration required to reduce the POI by 50% (DC50,absolute).
Results: The kinetics of POI degradation in the presence of a PROTAC are calculated by solving the equations derived in the methods section. Rearranging the equations and solving for Emax and EC50 yields convenient algebraic relationships to translate the in vitro Dmax and DC50. Emax is calculated as a function of Dmax while EC50 is a function of both Dmax and DC50. Parameter exploration shows the impact of a range of DC50, Dmax, and POI half-life values on POI reduction over time. In a case study using data published by Kofink et al 20221 on their SMARCA PROTAC tool compound ACBI2, we show that these relationships can be used to capture the in vitro degradation kinetics for two cell lines and explore the in vitro-in vivo extrapolation to the in vivo xenograft tumor PD.
Conclusions: A set of algebraic equations is derived relating DC50/Dmax to EC50/Emax that can be used in PKPD models for the early assessment of the relationships between PROTAC concentrations, effects on degradation rates, and effects on the POI. These relationships can be used to inform efficacy drivers, required target coverage, and establish the necessary parameter values/compound properties to achieve the desired target coverage, which together enable efficient compound triage and prioritization.
Citations: [1] Kofink, C., Trainor, N., Mair, B., Wöhrle, S., Wurm, M., Mischerikow, N., Roy, M. J., Bader, G., Greb, P., Garavel, G., Diers, E., McLennan, R., Whitworth, C., Vetma, V., Rumpel, K., Scharnweber, M., Fuchs, J. E., Gerstberger, T., Cui, Y., … Farnaby, W. (2022). A selective and orally bioavailable VHL-recruiting PROTAC achieves SMARCA2 degradation in vivo. Nature Communications, 13(1), 1–15. https://doi.org/10.1038/s41467-022-33430-6
