Accenture Puts Data Science to Work for Pediatric Leukemia Research - Seite 2

“Integration of genomic and clinical data and getting it into a usable, accessible format is a significant challenge in precision medicine,” said Dr. Meshinchi. “This collaborative effort between TpAML investigators and Accenture data scientists provides a mechanism to more informed analysis of clinical and genomic data, and could help identify patients at high risk of failure with conventional treatments. Validation of these findings can help modify patients’ treatments based on their relapse risk.”

By applying data science and engineering tools, such as Alteryx and Python, and machine learning libraries like scikit-learn, to this corpus of information, Accenture was able to create a code base that clinicians are using to model, understand and potentially predict how patients may respond to specific treatments. Data was made further accessible and consumable using Unity 3D visualization, offering a more interactive way to view the data in a game-space environment, laying a foundation for advanced, dynamic visualizations and VR experiences which could help clinicians potentially identify anomalies, or which they could use as an interface to present findings.

“For years, patients diagnosed with a disease often received the same treatment. And for some people, that treatment worked. However, for others, it did not work – or did so only marginally, or with serious side effects. With genome mapping, in combination with new analytical, scientific and technological advances, it is possible to develop targeted, more precise, personalized treatments for individuals or similar patient populations,” explained Stuart Henderson, global Life Sciences lead for Accenture. “Precision oncology is delivering on the promise of better patient care and health outcomes in remarkable ways and we look forward to seeing more projects like this TpAML investigation.”

This project builds on Accenture research underscoring the importance of data management and sharing to drive precision oncology, and the role of data and genomics in biopharmaceutical development.

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