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G-KnowMe specializes in creating custom automated pipelines for multiplex data analysis, streamlining the process for scientists to gain insights from their experiments. The variant prioritization and interpretation workflow for clinical reporting on next-generation sequencing-based tests is complex, requiring extensive analysis of large databases and literature. To address this, G-KnowMe has developed natural language processing-driven workflows that assist scientists in the clinical interpretation and reporting for these tests.
G-KnowMe offers clinical interpretation and reporting services for the genome sequencing based tests in Oncology. G-KnowMe domain experts have joined hands with software developers and AI experts to put together state-of-the-art semi-automated in-silico workflows that significantly bring down the time taken to put together the high quality reports. G-KnowMe reports are being offered by a well known diagnostic lab in India and have been very appreciated by the leading oncologists in the country for its content and quality.
Risk Prediction Model Building
G-KnowMe provided services to a cancer diagnostics lab towards creating a prognostic test for predicting the risk of recurrence in triple-negative breast cancer (TNBC) patients using immunohistochemistry (IHC) biomarkers and machine learning techniques. Rigorous validation and statistical analysis were conducted to evaluate the applicability and performance of the developed models. This led to the identification of tumor and patient profiles that required additional data collection for accurate risk prediction.
G-KnowMe target reports provide a comprehensive and up-to-date analysis of drug
targets for aiding drug discovery, biomarker research and clinical trial design. Clinical information is scattered across various databases and research articles. G-KnowMe has built domain specific configurable information extraction pipelines using the cutting edge Generative AI methods to quickly and effectively mine high quality data and present in user friendly dashboards. These reports have helped a client in diagnostics in significantly reducing the time taken from identifying a target to designing the clinical trial.
Clinical Data Management
Our team provided the guidance and technology support to develop an integrated oncology database using common data format that could collate diverse patient data from a variety of sources. The team worked closely with domain experts and informatics specialists of the client organization to develop the common data format, create comprehensive vocabularies using domain expertise in oncology, develop automated data extraction protocol using NLP and tested the database with real world data and problems.