Company: LNAI
Filing Date: 2025-05-15
Form Type: 10-Q
Source: 0001731122-25-000765
Chunk: 113

Company: Lunai Bioworks Inc.
Filing Date: 2025-05-15
Form: 10-Q
Item: Part I, Item 8
Chunk 113
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 I is to reduce the plethora of genomic features displaying variations across samples, which is accomplished by systematically eliminating extraneous or inconsequential features while preserving those features that exhibit the greatest potential for accurately detecting cancer.

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    Phase II of the workflow builds upon the foundation of selected biomarkers by focusing on understanding the dynamic interplay among these chosen biomarkers, culminating in the creation of composite panels. The goal of Phase II is to pinpoint biomarker combinations that not only demonstrate robustness in detecting cancer but also maintain their efficacy across diverse contexts. Renovaro Cube believes that its AI algorithms are adept at uncovering multiple combinations across a spectrum of panels, which is supported by Renovaro Cube’s AI-guided panel mining, a proprietary combinatorial optimization technique used by Renovaro Cube’s AI technology. This approach, coupled with the capacity to explore numerous panels, significantly enhances the likelihood of discovering panels that align with specific metric criteria, such as sensitivity, specificity, precision, and recall and allows for tailoring criteria to align with clients’ unique needs, such as the number of biomarkers included per panel, or the inclusion of biomarkers associated with the expression of specific genes. The performance of the top-tier panels is further fine-tuned through the application of machine learning models. Subsequently, the efficacy of these biomarker panels in detecting cancer is validated through independent data sets.

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    Phase III of the workflow involves Renovaro Cube’s collaboration with its clinical partners to validate the performance of the biomarker panels. Through this collaboration, Renovaro Cube can confirm the utility and accuracy of its biomarker panels in real-world clinical contexts. 

AI-Assisted Diagnostics

The process of biomarker discovery
facilitated by Renovaro Cube’s AI technology has yielded a set of data that enables scrutiny of the genomic distinctions and commonalities
inherent in diverse cancer types. This data set can support the diagnosis of cancers when their type or origin remains unidentified.

In addition to this role in biomarker
discovery and the development of diagnostic tests, Renovaro Cube’s AI technology also integrates AI-guided molecular profiling of
patient samples and furnishes diagnostic patient reports. These diagnostic reports reflect the outcomes of molecular profiling, coupled
with interpretations provided by Renovaro Cube’s team, to facilitate the process of cancer diagnostics by a qualified healthcare
provider, who can consider these reports in the context of a patient’s medical history, clinical signs, and symptoms, among other
factors.

Quality Control Process