ConcertAI at 2024 ASCO Annual Meeting | ConcertAI

Secure Cloud Access & BYOA

Data configured to the research questions available in our highly secure cloud or within your own secure cloud environment

Scale & Representativeness

The largest and most representative populations assuring highest utility and a minimum of bias

Definitive Quality & Utility

We provide meticulously curated data of the highest quality, setting industry standards

High Recency & Refresh

High currency on cases and the highest rate of refresh in the industry

GenAI & NLP Integration

Enhance information extraction with GenAI and NLP, ensuring data completeness through professional service augmentation and thorough automation review

Trial Design & Simulation

Multi-modal data for FIH, Ph1b/2a, and Ph2b/3 for optimized designs; simulations and digital twins

Accelerated Patient Enrollment

Screen site patients in real time, improving recruitment accuracy and streamlining the enrollment process

Translation to Evidence

Multi-modal data supports translational and FIH insights through evidence generation over the life cycle

ConcertAI 2024 ASCO Publications

Meet at ASCO 2024

CAI ASCO Publications-v2-1158

Efficient site selection for clinical trials using simulated annealing

Abstract: 1558 | Poster Bd #: 429

Authors:

Ian Ruchlin, Vibhor Govil, Deepak Samar, Jitesh Chawla, Pyeush Gurha

Organizations:

ConcertAI

CAI ASCO Publications-v2-5054

Real-world baseline treatment patterns and overall survival (rwOS) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) treated with olaparib in the United States.

Abstract: 5054 | Poster Bd #: 460

Authors:

Furaha Kariburyo-Yay, Daniel George, Himani Aggarwal, Jon Tepsick, Rebekah Yu, Weiyan Li, Chinelo Orji, Lincy Lal, Sameer Ghate

Organizations:

ConcertAI, LLC, Duke University Cancer Institute, Merck & Co., Inc., AstraZeneca

CAI ASCO Publications-v2-e13641

Dynamic machine learning model to forecast patient availability for clinical trials.

Abstract: e13641 | Publication Only

Authors:

Rajeev Kulkarni, Vivek Vaidya, Dhaval Parmar, Abhishek Tibrewal, Ravi Parikh

Organizations:

ConcertAI, Perelman School of Medicine, University of Pennsylvania

CAI ASCO Publications-v2-e13636

A prospective study comparing AI-based clinical trial eligibility screening with traditional EMR-based screening

Abstract: e13636 | Publication Only

Authors:

Jiby Joseph-Thomas, Cristina Green, Abhishek Tibrewal, Frank Dupont, Jen Flach, Amelia Goldstein, Vivek Vaidya, Rajeev Kulkarni, Ravi Parikh

Organizations:

ConcertAI, The Oncology Institute, Perelman School of Medicine, University of Pennsylvania

CLQ ASCO Publications v2 -4169

Predicting real-world overall survival for post-operative pancreatic ductal adenocarcinoma: An ASCO CancerLinQ Discovery analysis

Abstract:4169 | Poster Bd#: 149

Authors:

Kaleem Ahmed, Sheriff Issaka, Clayton Marcinak, Syed Nabeel Zafar

Organizations:

Department of Surgery, University of Wisconsin - Madison, Department of Surgery, University of Wisconsin–Madison, Division of Surgical Oncology, Department of Surgery, University of Wisconsin–Madison

CLQ ASCO Publications v2 -e23237

Electronic clinical quality measure (eCQM) concordance and quality care disparities among patients with breast cancer (BC)

Abstract: e23237 | Publication Only

Authors:

Nehanda Jones, Elizabeth Lipschultz, Adam Blair, Brooke Smither, Jacob Koskimaki, Robert Miller

Organizations:

CancerLinQ

CLQ ASCO Publications v2 -e13739

Disparities in patients with HER2-positive breast cancer receiving optimal treatment: Analysis of the real-world ASCO CancerLinQ dataset

Abstract: e13739 | Publication Only

Authors:

Olga Kantor, Alyssa Jones, Erica Mayer, Mariana Chavez-MacGregor, Tari King, Elizabeth Mittendorf

Organizations:

Brigham and Women's Hospital, Dana-Farber Cancer Institute, The University of Texas MD Anderson Cancer Center