Lantern Pharma Inc., an artificial intelligence (AI) company dedicated to developing cancer therapies and transforming the cost, pace, and timeline of oncology drug discovery and development, announced advancements in the application of its RADR® AI platform to accelerate and optimize the development of antibody-drug conjugates (ADCs). The global ADC market is projected to reach $30.4 billion by 2028, growing at a CAGR of 41.7%, with several recently approved ADCs achieving blockbuster status with annual sales exceeding $1 billion. Major biotech and pharmaceutical companies have recently completed ADC-focused acquisitions valued at over $10 billion, highlighting the sector’s growing strategic importance. Lantern Pharma is actively advancing multiple ADC candidates through preclinical development, including a promising collaboration with the prestigious MAGICBULLET::Reloaded Initiative at the University of Bielefeld in Germany.
In a peer-reviewed study published in PLOS ONE, Lantern Pharma researchers demonstrated how their AI-driven approach successfully identified 82 promising ADC targets and 290 target-indication combinations, while also validating 729 potential payload molecules from a screening of over 50,000 compounds. Notably, 22 of these targets have already been validated in clinical or preclinical settings, demonstrating the platform’s ability to identify clinically relevant targets. The remaining 60 novel targets represent significant potential for new intellectual property, portfolio development of ADC candidates at Lantern Pharma and licensing opportunities with other biotech and pharma companies. The ADC module helped to characterize payload molecules with exceptional potency, exhibiting GI50 values from picomolar to 10 nM (nanomolar) ranges. These payload molecules can be further optimized by leveraging RADR’s comprehensive molecular features database by mapping drug-response relationships with biochemical and molecular structure characteristics. This AI-driven optimization capability could potentially enhance both the selective targeting and therapeutic window of these ADC payload candidates. Lantern Pharma continues to advance the methods and automations outlined in the paper as part of it’s RADR™ AI platform and further enhance the data and computational precision of the module.
“This breakthrough demonstrates how AI can transform the traditionally costly and time-consuming process of ADC development,” said Panna Sharma, CEO & President of Lantern Pharma. “By simultaneously analyzing multiple data types and integrating mutation profiles with target expression, our team was able to identify optimal therapeutic combinations that have the potential to be more effective and safer for specific patient populations. We believe that our data-driven and machine-learning ready approach could reduce ADC development timelines by 30 to 50% and cut associated costs by up to 60% compared to traditional methods of ADC development.”
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The research leverages Lantern’s proprietary RADR® platform to analyze complex datasets including transcriptomics, proteomics, and mutation profiles across 22 tumor types. The platform’s ability to predict mutation-specific responses could enable more precise patient stratification in clinical trials, potentially increasing success rates and reducing development costs. This precision approach to ADC development could be valuable for biotech and pharmaceutical companies looking to advance their ADC portfolio in more targeted indications and is also being actively used by Lantern in the development and modeling of their ADC candidates in preclinical testing and optimization.
“The implications of this research extend far beyond just expanding the repertoire of potential ADC targets,” said Kishor Bhatia, Ph.D., Chief Scientific Officer at Lantern Pharma. “By leveraging our RADR® platform’s advanced AI capabilities, we’ve created a systematic approach that could dramatically reduce both the time and cost of ADC development while increasing the probability of clinical success. Our platform is particularly well-suited for partnership opportunities with pharmaceutical companies looking to accelerate their ADC programs or expand their pipeline with novel targets.”
Key Highlights of the AI-powered ADC module include:
- Demonstrated platform validation through the successful identification of 22 clinically proven targets with established therapeutic potential
- Discovered 60 novel targets that present significant opportunities for new intellectual property development, portfolio expansion, and strategic licensing partnerships
- Developed proprietary mutation-specific targeting capabilities that enable improved clinical trial design, enhanced precision in indication selection, and more accurate patient response predictions
- Established a framework that could reduce ADC development costs by up to 60% and accelerate development timelines by 30-50% for both Lantern Pharma and its collaborators
- Created a highly scalable, machine-learning ready approach that leverages the RADR™ AI platform to systematically evaluate thousands of potential tumor sub-types and indications
- Designed a clear pathway to commercialization through strategic industry partnerships and collaborative development programs
Source: Businesswire