A novel method that leverages existing data to conduct comparative analyses of competing assets: Sugemalimab and agents targeting the PD-L1/PD-1 axis as an example

2609 Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Numerous immune checkpoint inhibitors (ICIs) targeting the programmed cell death protein-1/programmed death ligand-1 (PD-1/PD-L1) axis have garnered regulatory approvals. A novel method of comparative analysis that discerns differences/similarities amongst such agents could reduce redundancy and hopefully enhance true competition. Methods: We’ve described an approach for assessing efficacy that assumes changes in tumor quantity result from two simultaneous processes – exponential decay of the treatment-sensitive fraction of tumor at rate d, and exponential growth of the resistant fraction at rate g. Using this method, the USFDA analyzed data from 9934 patients with NSCLC enrolled in registration trials treated with chemotherapy, targeted therapies, and immunotherapies concluding g is inversely associated with survival across treatment types and encouraging prospective studies to evaluate whether g derived from early tumor measurements might serve as an earlier clinical trial endpoint (Gong ASCO 2020). Using data provided by EQRx and CStone we analyzed the GEMSTONE-302 trial comparing chemotherapy +/- the PD-L1 inhibitor sugemalimab in first line NSCLC. Results: 88% of the data could be analyzed. Regression without growth was seen in 10-12% of both arms with indistinguishable d values. Evidence of tumor growth was estimable as a g value in 68-71% with statistically slower g values and longer tumor doubling times (TDT) seen with sugemalimab + chemotherapy [0.0012/day (0.0005-0.0022); TDT 578d] than placebo + chemotherapy [0.0025/day (0.0013-0.0035); TDT 277d] p<0.0001. A comparative analysis with FDA data from 1521 patients who received Combo ICI in front line, finds comparable/slightly slower g values for sugemalimab + chemotherapy using all or a fraction of the data. Conclusions: We used a method of analysis that estimates rates of tumor growth ( g) to analyze the efficacy of the PD-L1 antagonist, sugemalimab, in NSCLC. Because time is included in our equations the intervals of assessment are rendered inconsequential, making this method of analysis ideal for virtual comparisons. We confirmed the value of sugemalimab in the first-line setting by demonstrating its data track very closely with data aggregated from randomized trials reported by the USFDA in patients treated with Combo ICI in front line. Because g values can be estimated with fewer data it can be leveraged for early decisions. [Table: see text]