Speaker Profile

Shruti Krishna Desai

Biography

Desai’s current work focuses on the enablement of faster and smarter navigation through currently siloed data in immune-oncology. This includes developing customizable and scalable data analysis pipelines for various biological assays, to be compatible with cloud infrastructure, enabling integration and cross function analysis of disparate datasets, and developing data visualizations that help in retrieving important and relevant clinical information that enables faster and smarter scientific research.

Talk

iCore : Leveraging Google Cloud Platform to optimize Translational Research in Immuno-Cancer Therapy
The nascent nature of precision medicine opens the need of appropriate technologies to enable cancer cure through informed decisions with improved diagnosis, treatment and Quality of Life for the patient. Through collaborative research, immuno-oncology provides a great opportunity to bring a paradigm shift in precision medicine using big data, though not without huge challenges!

Ethical and accurate recruitment and management of patient in a multi-site clinical trial is a known problem. Since few laboratories would possess the expertise for the varied diagnostic tests, standardizing the logistics of clinical samples and reconciliation of data is needed. Data sharing, security, accessibility and interpretation of the expanse of data from disparate health care systems across pre-clinical and clinical phases remains a challenge.

iCore leverages cloud platform to organize, aggregate and analyze data. Choices of programming frameworks, analytics pipelines, support for machine learning and AI with flexible computational resource allocation in a secured cloud environment positions iCore to deliver better than the existing siloed systems.

iCore simplifies major bottlenecks by connecting various data silos, providing a single study and patient view along with the ability to interrogate across disparate datasets to gain better insights leading to better decision making.