Abstract
For decades, policies regarding generic medicines have sought to provide patients with economical access to safe and effective drugs, while encouraging the development of new therapies. This balance is becoming more challenging for physicians and regulators as biologics and non-biological complex drugs (NBCDs) such as glatiramer acetate demonstrate remarkable efficacy, because generics for these medicines are more difficult to assess. We sought to develop computational methods that use transcriptional profiles to compare branded medicines to generics, robustly characterizing differences in biological impact. We combined multiple computational methods to determine whether differentially expressed genes result from random variation, or point to consistent differences in biological impact of the generic compared to the branded medicine. We applied these methods to analyze gene expression data from mouse splenocytes exposed to either branded glatiramer acetate or a generic. The computational methods identified extensive evidence that branded glatiramer acetate has a more consistent biological impact across batches than the generic, and has a distinct impact on regulatory T cells and myeloid lineage cells. In summary, we developed a computational pipeline that integrates multiple methods to compare two medicines in an innovative way. This pipeline, and the specific findings distinguishing branded glatiramer acetate from a generic, can help physicians and regulators take appropriate steps to ensure safety and efficacy.
Highlights
Defining relevant probes as those with variability induced by activation, we found that 4-fold more probes had significantly higher variability across the generic batches than across the GA batches (Figure 1A and Table S3)
Through Gene Set Enrichment Analysis (GSEA), [30] we found that FoxP3 targets genes were enriched in GA samples compared to medium (FDR-adjusted q = 0.008) to a more significant degree than in generic samples compared to medium (FDR-adjusted q = 0.036, Figure 2D and Figure S2A)
[38] We found that among the genes upregulated by generic relative to medium, there was a significant enrichment in CD16dim monocytes (FDR q = 0.132, where the significance threshold is 0.25)
Summary
[4] In addition to biosimilars, recent efforts have focused attention on the need for regulatory approaches to generic versions of non-biological complex drugs (NBCDs) [5] which include liposomal drugs, low-molecular weight heparins, iron-carbohydrate drugs, and glateramoids [6]. One such glatiramoid is glatiramer acetate (GA, Copaxone), which provides significant benefit for patients with multiple sclerosis (MS). The lists of genes and pathways resulting from this traditional analysis were intriguing, but we recognized the need for new methods to integrate multiple lines of evidence and provide a clear and comprehensive picture of the differences in immunological impact that would contribute to the broader discussion of safety and efficacy
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