ASH Annual Meeting & Exposition

AACR Summit

We’re excited to attend AACR Summit April 14-19, 2023 in Orlando, FL at the Orange County Convention Center. This year at AACR, meet with one of our many attending team members to learn more about our new class of real world datasets in our clinical molecular RWD comprised of researched great EMR combined with whole exome sequencing, transcriptomics and IEC. We’re going to have a lot of great opportunities and discussions to support life science innovators bringing new therapeutics into the clinic. 

 

Meet With Us


 

Meet with Claudio and our attending team members to learn more about our new class of real-world datasets in our clinical molecular RWD, which combines researched EMR with whole exome sequencing, transcriptomics, and IEC. At AACR, we’ll be discussing exciting opportunities and having important discussions to support life science innovators bringing new therapeutics into the clinic.

Don’t miss out on this chance to hear from Claudio and learn more about the cutting-edge technology and solutions that are driving the future of clinical research.

AACR Poster Presentations

We are proud to be presenting three posters at this year’s 2023 AACR Summit!

 

Abstract #4400

April 18 9:00-12:30 pm
Poster Section 39, #10

Machine learning (ML) on real-world data (RWD) of front-line (1L) metastatic castration resistance prostate cancer (mCRPC) patients for dynamic prediction of time to tx discontinuation (TTD)

Abstract #923

April 16 1:30-5:00 pm

Genomic Landscape of Patients With Non-Small Cell Lung Cancer (NSCLC)

NSCLC is the leading cause of cancer deaths in the US with a low 5-year survival rate, making personalized medicines and combination therapies critical. With ConcertAI’s deeply curated real-world clinico-genomics database of over 11k NSCLC patients, we now have a better understanding of the genomic landscape of NSCLC and insights into commonly occurring co-mutations, opening doors for more targeted therapies to help improve patient outcomes. This database has previously been used to identify biomarkers for sensitivity and resistance to PD-L1/PD-1 checkpoint inhibitors.

Abstract #851

April 16 1:30-5:00 pm
Poster Section 31, #9

Machine learning (ML) model for prediction of pneumonitis using real-world data (RWD) on immune checkpoint inhibitor (ICI)-treated advanced non-small cell lung cancer (aNSCLC)