First in Human Dose and Regimen Prediction for an ADC IND

The investigational ADC targeted a novel antigen over-expressed in multiple solid tumors, using a non-standard payload. Despite limited preclinical tumor response data, the client needed to select an appropriate FIH dose and regimen in order to design a critical monkey GLP toxicity study. Additionally, with several ADCs in their pipeline, it was important to efficiently integrate knowledge across assets and inform FIH decisions for each of these programs. 

MetrumRG developed a mechanistic, QSP-based pharmacokinetic-pharmacodynamic (PKPD) model, integrating data from in vitro assays, in vivo PKPD studies,  and scaled to human-level simulations.  As the model was based on principles of biology and physiology the methodology could be easily adapted and applied to other assets in the client’s pipeline. Simulations were used to predict the most appropriate dosing regimen and inform the design of the cynomolgus monkey GLP toxicity study, which was critical to get right in order to expedite the path to an IND and first-in-human (FIH) trials.

The QSP model facilitated a thorough comparison of various clinical dose schedules in silico. This built confidence in the eventual dosing schedule decision, ensuring it was both clinically feasible and aligned with the client’s goals. The QSP approach provided a risk analysis framework, enabling the team to assess the impact of assumptions made during model development where knowledge gaps persisted. Virtual population analyses were conducted to explore expected clinical variability and uncertainties, helping the client assess tumor growth inhibition (TGI) projections under different dose schedules and clinical scenarios. The analysis directly supported the client’s Minimum Anticipated Biological Effect Level (MABEL) metrics and led to recommended dosing for the GLP studies.

Providing essential insights critical to the design of the monkey GLP toxicity study not only helped the client make more informed decisions regarding their ADC's clinical development, but also strengthened their ADC platform by integrating knowledge across multiple assets in their pipeline. The collaboration ultimately enabled the client to specify a rational FIH dosing strategy, accelerating their path to clinical development.