Predictive Oncology Expands the Application of its Live-Cell Tumor Platform to De-Risk Drug Discovery and Accelerate Pipeline Development

Findings demonstrate real-world applications of Company’s AI platform to support biomarker discovery, clinical trial optimization and target validation

Proprietary tool accounts for patient heterogeneity and increases Probability of Technical Success

PITTSBURGH, Aug. 13, 2024 (GLOBE NEWSWIRE) -- Predictive Oncology Inc. (NASDAQ: POAI), a leader in AI-driven drug discovery, today announced that it has expanded the available applications for its platform to account for patient heterogeneity, de-risk drug discovery, and accelerate pipeline development.

Responding to the historically high failure rate in drug development in Phase II and Phase III clinical trials, the Company is utilizing its artificial intelligence, active machine learning capabilities, in a CLIA wet lab environment, to leverage its extensive biobank of cryogenically preserved patient-derived live-cell tumor samples, across 137 different tumor types accumulated over nearly two decades, to account for patient heterogeneity ahead of any clinical phase development work.

One of the primary reasons for these late-stage failures is that the heterogeneity of human subjects is not introduced until clinical trials are well underway. Predictive Oncology’s platform addresses this challenge by applying its unique assets and resources to introduce patient heterogeneity into the earliest phases of AI-driven drug discovery, thereby increasing the Probability of Technical Success (PTS), a key metric in target selection, clinical trial design and pipeline replenishment.

“The outputs of our platform are used to more comprehensively identify which patient samples responded and why, through the use of our deep machine learning and cellular analysis capabilities.” said Dr. Arlette Uihlein, SVP of Translational Medicine and Drug Discovery at Predictive Oncology. “These analyses utilize genomics, digitized pathology data, and phenotype profiling of heterogenous responses across drug treatments and across heterogenous patient cell populations.”

“Oncology drug discovery and development are time and resource intensive processes that, unfortunately, do not yield high rates of success when considering the relatively small number of compounds that are ultimately approved and made available to cancer patients,” stated Raymond Vennare, Chief Executive Officer of Predictive Oncology. “Our platform has successfully demonstrated an ability to increase the Probability of Technical Success for these compounds. The ability to accelerate drug development timelines would allow pharmaceutical companies to make critical go/no go decisions, redirect resources or reprioritize R&D efforts to pursue parallel or contingent drug development initiatives.