Introduction
This is Abe from the Lakehouse Department of the GLB Division. I wrote an article summarizing the content of the session based on reports from Mr. Ichimura participating in Data + AI SUMMIT2023 (DAIS).
This time, I would like to talk about the talk "Using Lakehouse to Fight Cancer: Ontada's Journey to Establish a RWD Platform on Databricks Lakehouse". This talk was delivered by Donghwa Kim, senior director of architecture at Montana. He has over 20 years of IT experience and previously designed and implemented DataLeak for Veterans Affairs and CMS.
The theme of this talk is the importance of real-world data and evidence in cancer care. The purpose of the session is to introduce the implementation of real-world data and evidence using the Lakehouse architecture. Target audiences include healthcare professionals, data scientists, and technicians.
Importance of real-world data and evidence in cancer care
First, the lecturer talked about the importance of real-world data and evidence in cancer treatment. Real-world data refers to data collected in actual medical settings other than clinical trials and research. It is important.
US cancer statistics
The lecture also touched on cancer statistics in the United States. The main points are summarized below.
- Approximately 1.6 million people are diagnosed with cancer and over 600,000 die from cancer each year in the United States
- Cancer is the second leading cause of death in the United States, with lung, breast and prostate cancers being the most common
- There are a wide variety of cancer treatments, and it is important to select the most suitable treatment for each individual patient
Given this situation, it is necessary to use real-world data and evidence to evaluate the efficacy and safety of cancer treatment and select the optimal treatment method.
Implementing real-world data leveraging the Lakehouse architecture
The lecturer then described the implementation of real-world data and evidence using the Lakehouse architecture implemented by Montana. The Lakehouse architecture is a new data platform from Databricks that combines the capabilities of a data warehouse and a data lake.
Ontada's RWD platform
Ontada leverages Databricks Lakehouse to build its Real World Data (RWD) platform. The platform offers the following features:
- Efficient collection and management of large amounts of real-world data
- Data governance functions to maintain data quality and consistency
- Generation of evidence using machine learning and statistical analysis
- Visualization tools for evaluating efficacy and safety of therapeutic methods
By utilizing these functions, it is expected that the use of real-world data and evidence in cancer treatment will be promoted, and that it will be useful in the selection of optimal treatment methods and the development of new treatments.
In Summary
Recognizing the importance of real-world data and evidence in cancer treatment, working to implement real-world data using the Lakehouse architecture will enable the selection and development of more effective and safer treatments. was shown. It is hoped that such efforts will continue to spread and lead to improved treatment and quality of life for cancer patients.
Conclusion
This content based on reports from members on site participating in DAIS sessions. During the DAIS period, articles related to the sessions will be posted on the special site below, so please take a look.
https://www.ap-com.co.jp/data_ai_summit-2023/
Thank you for your continued support!
Translated by Johann
