Lantern Pharma Inc, an artificial intelligence (AI) company developing targeted and transformative cancer therapies using its proprietary AI and machine learning (ML) platform, RADR, with multiple clinical stage drug programs, today announced a substantial increase in the power and capabilities of RADR focused on improving the drug development process for immune checkpoint inhibitors (ICIs). These capabilities are expected to address the multiple challenges facing the increased usage of ICIs in cancer therapy. Since gaining regulatory approval in 2011, ICIs have improved the lives of tens of thousands of cancer patients as either monotherapies, and more recently, in combination regimens with other therapies.
The success of ICIs has resulted in multiple competing ICI molecules, often from the same class, in overlapping cancer indications. Additionally, recent clinical trial failures reveal headwinds to the desired expansion of ICIs for a broader range of cancers and patient groups. Currently, there are over 5,200 ongoing clinical trials involving ICIs, many of these lacking adequate biomarker strategies or guidance from AI enabled approaches to optimize the selection of patient responder populations.
Also Read: Jasper Health and Covet Health Form Partnership
“We are expanding the functionality of our RADR AI platform in ways that aim to solve the very meaningful and important challenges of future checkpoint inhibitor development. We initially began this effort by identifying meaningful combinations with checkpoint inhibitors that might be the most effective with our LP-184 and LP-284 drug candidates,” stated Panna Sharma, Lantern’s CEO and President. “Our latest RADR advancements add a new level of speed, scalability, and precision in the identification of rational combination therapies that have the potential to overcome known shortcomings of ICIs. The current clinical trial landscape of ICIs is at a critical juncture, with dozens of new indications being pursued.
Unfortunately, the majority of these trials are unlikely to succeed unless the right cancer subtypes are pinpointed and unless the right combinations with other molecules are pursued. ICIs have the potential to benefit from the ability to predict which patient groups and which cancer subtypes will respond to the drug or drug combination, which is a fundamental part of our AI platform, RADR, as we recently demonstrated in our collaborative 2023 ASCO poster.”
In a recent study presented at the 2023 ASCO meeting, RADR’s algorithms demonstrated an 88% accuracy rate in predicting which melanoma (skin cancer) patients exhibiting resistance to anti-PD1 therapy will respond to Elraglusib, a GSK-3ϐ inhibitor being developed by Actuate Therapeutics, which previously entered into a multi-year research and development collaboration with Lantern Pharma to leverage the RADR platform.
SOURCE: Businesswire