NeoGenomics, Inc. and ConcertAI, LLC announced a broad collaboration to advance large-scale hematological research solution to investigate real-world clinical practice and outcomes in hematological malignancies. Few diseases are as complex as hematological malignancies; The number of alternative treatments considered for patients at different points throughout their care is more varied and individualized than what is seen in diagnosis and management of solid tumors. Hematological malignancies require surveillance of patients over multiple time periods with numerous clinical and diagnostic measures to assess sustained response to treatment or relapse.

Combining ConcertAI's longitudinal clinical data with NeoGenomics' comprehensive biomarkers derived from hundreds of hematological tests company are able to establish a robust and definitive RWE hematology solution. The collaboration advances molecular and genetic data solutions for the entire drug development lifecycle, from early clinical development to post-approval epidemiological studies. The scale and volume of the combined dataset, which covers over one million patient lives across 1,000+ oncology clinics, provides coverage of key biomarkers throughout the entire patient treatment journey and across multiple lines of therapy, which enables valuable insights for research purposes.

This is the first population-scale hematology data set, which is both large and broad enough to minimize selection bias and thus offering an actionable representation of the hematological prevalent disease in the US. The multi-modal combination of EMR and rich biomarker data allows for the latest causal inference methodologies, increasingly preferred by the FDA and other regulatory bodies, and clinical AI methodologies with assurance of high representativeness and generalizability. With rich cytogenetics, morphology, flow cytometry, FISH, and molecular hematological data, this collaboration now has the potential to apply the latest Generative Artificial Intelligence and other complementary approaches that are historically limited by data set sizes and lack of standardization.

Hematological diseases can be stable under treatment for years and then enter a period of non-response and relapse. New AI approaches offer the potential to define predictable patterns, linked to specific biomarker patterns, aligned to different treatment approaches, and directly associated with outcomes. This approach can inform new therapeutic programs, clinical trial designs, and treatment strategies.

In First Quarter, the companies will be launching a hematology-focused collaborative version of ConcertAI's Clinical Trial Optimization solution, supporting study design, and optimizing all aspects of trial planning, with multiple clinical development initiatives planned.