Lantern Pharma Develops Top-Ranked AI Algorithms to Predict the Blood-Brain-Barrier Permeability of Any Compound

Lantern Pharma, a clinical-stage biopharmaceutical company using its proprietary RADR artificial intelligence (“AI”) and machine learning (“ML”) platform to transform the cost, pace, and timeline of oncology drug discovery and development, today announced that it has developed highly-accurate and industry-leading AI algorithms to predict the ability of a drug or compound to pass the blood-brain-barrier (BBB), a highly selective border that can prevent drugs from entering brain tissues. The BBB prevents an estimated 98% of drugs from entering the brain, which presents a major hurdle for developing drugs to treat brain and central nervous system (CNS) cancers. Lantern’s AI BBB permeability prediction algorithms have a prediction accuracy of 89-92% and represent a rapid and cost-effective way to screen drugs or compounds to determine if they cross the BBB, which can accelerate the development of drug candidates for brain and CNS cancer patients.

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“Lantern’s new BBB prediction module is a major development for our AI RADR platform and continues to demonstrate how Lantern is applying AI to advance, de-risk, and significantly reduce costs in oncology drug discovery,“ stated Panna Sharma, Lantern’s CEO and President. “Biopharma companies can spend millions of dollars annually on intensive wet-lab experiments to attempt to validate whether a drug passes the BBB. Our AI/ML approach offers a rapid and highly-accurate alternative for predicting a drug’s BBB permeability, which will not only advance our drug development pipeline, but will also facilitate opportunities for new high-value business development collaborations with other biopharma companies to develop brain and CNS drugs,” continued Sharma.

The highly accurate AI BBB permeability prediction algorithms use a combination of proprietary automated feature selection methods along with specialized hyper parameter optimization that integrates algorithms using an ensemble approach to quickly provide a compound’s BBB permeability range. This approach allows for high throughput and ultra-fast BBB permeability analysis compared to traditional discovery and evaluation methods.

Lantern’s AI BBB permeability prediction algorithms were evaluated and scored in the BBB drug prediction challenge conducted by Therapeutics Data Commons (TDC), a coordinated initiative to evaluate AI capabilities across therapeutic modalities and stages of discovery. This challenge evaluates and scores how AI/ML algorithms perform in predicting the BBB permeability across 1,975 compounds whose BBB permeability is known. All four of Lantern’s AI/ML BBB permeability prediction algorithms were the top-performing algorithms evaluated by TDC and had high accuracy prediction percentages ranging from 89-92% and high overall performance scores ranging from 0.93-0.96 (out of 1). Lantern expects to continue advancing its AI/ML BBB permeability prediction algorithms to further increase their accuracy, performance, and functionality.

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Lantern’s AI BBB permeability prediction algorithms have been fully integrated into RADR as a BBB permeability prediction module and continue to expand the diverse capabilities and functionality of RADR. Additionally, the RADR BBB permeability prediction module is being made available to the Company’s wholly-owned subsidiary Starlight Therapeutics, to advance their pipeline of brain and CNS cancer indications and will be leveraged to establish additional RADR focused biopharma collaborations for brain and CNS drug discovery.

In addition to providing value for future biopharma collaborations, the RADR BBB permeability prediction module will, more importantly, help to advance opportunities for the discovery and development of new drug candidates for the hundreds of thousands of brain and CNS cancer patients who have a large and unmet need for new and effective cancer therapies.

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