COTA and Aetion partner to expand access to real-world data for oncology research
This collaboration enables Aetion and COTA to meet the needs of researchers requiring high-quality, clinically rich oncology data, for both liquid and solid tumor types.
Overcoming challenges to integrating biomarker data into clinical trials
Life sciences researchers and oncologists are learning more about cancer pathogenesis and treatment every day, largely thanks to explosive innovation in the world of biomarkers.
How to use real-world clinicogenomic data to fuel drug development
This blog series talks extensively about the benefits of using real-world data (RWD) to enhance clinical trials and accelerate research into new therapies for a variety of different conditions. Now it’s time to take a closer look at the details.
Enriching access to multimodal data insights with COTA Connect
Today, COTA is introducing COTA Connect: a powerful new capability to link data with a variety of different supplemental data sources, including linking COTA’s robust real-world clinical data to claims, imaging, socioeconomic data, and more.
So you want to train an oncology LLM: Start by getting close to the data
To create targeted LLMs that are suitable for diving into health-related areas like oncology, we must choose our data carefully and get as close to the original source as possible to avoid “playing telephone” with inaccurate information that could affect drug development processes or cancer outcomes.
COTA Wins Google Cloud Customer of the Year Award for using AI to Improve Cancer Care
A panel of senior Google Cloud executives selected COTA from a pool of entries to win *2* Google Cloud Customer Awards. These awards showcase companies from around the world who are using Google Cloud technologies to improve their operations, and their social and governance efforts.
How real-world data is enhancing our understanding of lung cancer recurrence
While the incidence of lung cancer is decreasing over time, and survival rates are on the rise year-over-year, there is still much to learn about how to best treat this disease – and prevent its recurrence after initial therapy.
How to identify and address data biases when creating an ECA
In this blog, we’ll explore the most common biases encountered in ECAs and how to mitigate their impact on research results.
Explore the patient journey with multimodal RWD
The notoriously complex healthcare system produces enormous quantities of data every moment. A typical care delivery network might generate petabytes of clinical, financial, laboratory, and pharmaceutical information on hundreds of thousands of patients each year – yet only a tiny fraction of this data is currently used to inform treatment decisions, support the development of new therapies, and foster better patient experiences and outcomes.
Oncology LLMs: Why’d you have to go and make things so complicated?
Large language models (LLMs) like Chat-GPT and Google’s Bard are rapidly changing the way we interact with datasets that are simply too big, complex, and varied for any ordinary person to comprehend.
