- Expansion of RADR® platform adds new AI capabilities for the automated identification of new and effective combination therapy regimens for immune checkpoint inhibitors (ICI)
- Additional functionality includes the creation and testing of molecular signatures of ICI response and resistance with a highly scalable, machine-learning based system designed to improve ICI clinical trial outcomes
- Worldwide, ICIs generated $41.5 billion in annual sales in 2022 and are projected to reach $67.8 billion by 2025, according to GlobalData
- Future ICI growth hinges on new approvals for novel ICI candidates and biomarker-guided strategies to position ICI combination regimens in new cancer indications, in earlier lines of treatment, and in historically difficult to treat populations
Lantern Pharma Inc. (NASDAQ: LTRN), 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.
“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.
The continued growth of ICIs, especially the approval of new ICIs, will be predicated on: 1) efficiently identifying new biomarker or molecular signatures for optimal patient selection, stratification, and management, and 2) rapidly developing combination regimens that overcome treatment challenges facing current and emerging solid and hematological cancer indications. Lantern’s latest RADR® AI developments will focus on addressing these challenges by building automated and highly scalable computational analytics to generate clinically relevant tumor-specific and tumor-agnostic molecular signatures to guide the identification and development of drug combinations that can prolong ICI durability of response and improve patient survival. These developments will leverage RADR® to uncover molecular drivers of response and resistance influencing ICI treatment outcomes by coupling pathway and network-based analytics with the simultaneous screening of millions of targets from complex clinical and biological data sets. This capability will be powered by tens of billions of new data points from immunotherapy and checkpoint inhibitor studies that Lantern has begun to add to its RADR® platform.
Lantern plans to deploy its new RADR® ICI predictive module with biopharma partners and to identify potential combinatorial strategies for LP-184 and LP-284, the first of Lantern’s drug candidates developed internally with the assistance of the RADR® AI platform. The ICI market is projected to reach $67.8 billion in annual sales by 2025, according to GlobalData, with future growth dependent on approvals from precision-based approaches guiding the development and positioning of new combination therapies.
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