Abstract 847: Applying the principles of convexity and concavity to guide treatment scheduling of ALK inhibitors in non-small cell lung cancer
Authors: West Jeffrey , Desai Bina , Strobl Maximilian , Pierik Luke , Velde Robert Vander , Robertson-Tessi Mark , Marusyk Andriy , Anderson Alexander R. 
Published: April 2023

Abstract
Recently, the US Food and Drug Administration (FDA) has initiated “Project Optimus,” designed to revisit and reform the decades-old maximum-tolerable dose paradigm. Traditional dose selection schemes designed for cytotoxic therapies may not apply for targeted therapies with exposure-response curves that often plateau below maximum tolerable patient toxicity levels. While nonlinear sigmoidal exposure-response curves are ubiquitous in oncology, they are typically used to measure differential response in first-order effects (mean value of drug dose delivered), while second-order effects (variance of drug dose) are generally ignored. Herein we present a paradigm for guiding treatment scheduling based on the convexity (or its converse, concavity) of exposure-response curves - a phenomenon that is widely applicable to targeted therapies. The “curvature” of exposure-response curves (e.g. a convex or concave shape) provides a direct prediction of continuous treatment, compared with high-dose/low-dose treatment. For example, if the exposure-response function is concave near a dose of ‘x’, continuous (daily) administration of x may be less effective response compared to a regimen that switches equally between 120% of x and 80% of x (every other day), even though both regimens use the same total drug. This paradigm is specifically relevant to targeted therapies which, as stated above, are associated with exposure-response plateaus that are concave in nature (to be compared with convex exposure-response curves common in cytotoxic chemotherapies). Analysis of response curves in vitro for a H3122 ALK-positive non-small cell lung cancer (NSCLC) cell line predicts that evolved-resistance lines are generally more concave, while treatment-naïve lines are more convex. In vivo, selection pressure due to treatment selects for resistant phenotypes over time. Previous literature shows resistance to ALK inhibitors occurs gradually, as tumors acquire cooperating genetic and epigenetic adaptive changes. Thus, we hypothesized the existence of a critical point in the time-evolution of ALK-positive tumors where it is optimal to switch from continuous treatment to high-dose/low-dose to mitigate the onset of gradual resistance. In this work, we construct a mathematical modeling framework of gradual resistance, parameterized to data, and predict time-dependent curvature in continuous (8 weeks), volatile (8 weeks) ALK inhibition in vivo. our key insight is that curvature increases in proportion to the amount of resistance in the tumor population. Curvature provides a time-dependent metric which 1) predicts the emergence of resistance and 2) determines the optimal subsequent dosing strategy. We test our key hypothesis in vivo, comparing continuous and volatile treatment schedules of ALK inhibitors to a switching schedule of continuous-volatile (4 weeks each).
Citation Format: Jeffrey West, Bina Desai, Maximilian Strobl, Luke Pierik, Robert Vander Velde, Mark Robertson-Tessi, Andriy Marusyk, Alexander R. Anderson. Applying the principles of convexity and concavity to guide treatment scheduling of ALK inhibitors in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 847.