A Mechanistic Pharmacodynamic Modeling Framework for the Assessment and Optimization of Proteolysis Targeting Chimeras (PROTACs)

Abstract

The field of targeted protein degradation is growing exponentially. Yet, there is an unmet need for pharmacokinetic/pharmacodynamic models that provide mechanistic insights, while also being practically useful in a drug discovery setting. Therefore, we have developed a comprehensive modeling framework which can be applied to experimental data from routine projects to: (1) assess PROTACs based on accurate degradation metrics, (2) guide compound optimization of the most critical parameters, and (3) link degradation to downstream pharmacodynamic effects. The presented framework contains a number of first-time features: (1) a mechanistic model to fit the hook effect in the PROTAC concentration-degradation profile, (2) quantification of the role of target occupancy in the PROTAC mechanism of action and (3) deconvolution of the effects of target degradation and target inhibition by PROTACs on the overall pharmacodynamic response. To illustrate applicability and to build confidence, we have employed these three models to analyze exemplary data on various compounds from different projects and targets. The presented framework allows researchers to tailor their experimental work and to arrive at a better understanding of their results, ultimately leading to more successful PROTAC discovery. While the focus here lies on in vitro pharmacology experiments, key implications for in vivo studies are also discussed.

Targeted Degradation of CDK9 Potently Disrupts the MYC Transcriptional Network

“…KI-CDK9d-32 achieves near 100% maximal degradation and a DC50 of 0.89nM following 4 hours of treatment in MOLT-4 cells (Figure 1C (ii)), making this, to our knowledge, the most potent CDK9 degrader reported. Consistent with the “hook-effect”, which is often observed with PROTACs and reflects the saturation of both protein members of the ternary complex with their respective binding elements and rendering the formation of a ternary complex unfavorable above a certain concentration threshold 25 , we observed limited degradation efficiency starting at 355 nM for the early time-points. Further assessment of the kinetics of degradation showed that this effect became increasingly negligeable as treatment time elapsed.…”

Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development

“…QSP models that contain sufficient biological resolution to project efficacy and toxicity end points can serve a unique role for early evaluation of the therapeutic index, which can then be refined as more clinical data becomes available. Finally, the burst of many novel and complex modalities (e.g., bispecifics, tri‐specific antibodies, ADCs, and PROTACs) in oncology requires a deeper and quantitative understanding of the distribution and delivery of active moiety to the site of action and the patient's systemic (including immune) response, QSP modeling could provide an in silico hypothesis testing strategy based on preclinical data, when clinical data are lacking or sparse to enable traditional population PK/PD or E–R analyses to inform dose selection 67–70 . QSP models have demonstrated their utility in amalgamating information from in vitro, preclinical, and early clinical investigations to optimize dosages and regimens for these innovative modalities, especially in the realm of bispecific T‐cell engaging biologics; we anticipate that more examples will emerge in the future that illustrate expanded use of QSP in dose optimization.…”

Proximity-Based Modalities for Biology and Medicine

“…, neurodegenerative diseases and infective diseases). New empirical rules set specifically for bifunctional molecules, , as wells as relevant mechanistic pharmacological PK/PD models − that could be further refined by the increasingly available preclinical and clinical data sets of PK/PD studies of PROTACs, are potential solutions to address these challenges.…”