Lantern Pharma Further Enhances Capabilities of its AI Drug Discovery Platform, RADR, with Product Development Roadmap for the Development of Antibody Drug Conjugates

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,  announced expansions and updates to RADR’s product roadmap, which will further enhance its oncology drug discovery capabilities. These RADR advancements will focus on additional innovative AI and ML approaches to develop Antibody Drug Conjugates (ADCs), which are highly specific cancer-targeted antibodies linked to potent anti-tumor small molecules and designed for the treatment of cancer.

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“RADR is an integral component for de-risking and powering the progression of Lantern’s drug programs, and our recent advances in moving from program identification through preclinical development have occurred at speeds rarely seen in oncology drug discovery and development,” said Panna Sharma, Lantern’s CEO and President. “Globally, ADC drug programs are one of the fastest growing drug development markets and are projected to represent a global market potential of over $14 billion by 2027. The expansion of RADR^®’s ADC capabilities will not only build on its demonstrated ability to identify synergistic and effective combinations of antibodies and small molecules, but will also facilitate new high-value ADC-focused business development opportunities and collaborations,” continued Sharma.

Highlights of RADR^®’s ADC Development Roadmap:

Lantern’s strategic RADR^® roadmap for the development of ADCs was implemented this quarter and will include the following expansions and updates:

• Development of additional algorithms that can boost prediction of optimal combinations of ADC components including antibodies, antibody linkers, payloads, and ADC combinations with other anticancer small molecules.
• Generation of additional ML-based ADC biomarker signatures that can predict a cancer’s sensitivity to an ADC and guide future patient selection for clinical trials.
• Use of RADR^® guided selection of new molecule payloads with features of synergy or properties to overcome resistance from existing ADC payloads.
• Creation of AI modules to predict the immunogenicity of ADC antibodies to cancer cell surface antigens.
• Expansion of RADR^®’s 25+ billion oncology-focused data points with the addition of immuno-oncology (IO) datasets.

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The advancement of RADR^®‘s product development roadmap will be accelerated using RADR^®‘s library of over 200+ advanced algorithms and automated ML pipelines. This AI strategy will enable the large-scale analysis of thousands of high-performing model features through their SHapley Additive exPlanation (SHAP) scores and can efficiently identify key genes and pathways that are mechanistically important to drug resistance, quality of patient outcomes, and improved delivery of ADC drug payloads. These features can add potential value to ADC programs and prioritize ADC targets. Additionally, this powerful strategy can be leveraged to inform downstream ADC design by identifying ADC components that, when used together, have a high probability of synergy that can lead to therapeutic response.

Lantern’s RADR^® platform excels at automated, large-scale, biological, and response network analysis, yielding correlations that can be leveraged in both target identification and drug response prediction. This biology-driven AI drug development approach, which leverages over 25 billion oncology focused data points across thousands of data sets, can be used in augmentation with existing structural and bond analysis methodologies to further de-risk ADC drug candidates. This AI-driven approach using RADR^® is expected to deliver an improved understanding of potential clinical indications and patient stratification approaches for ADC development.

Lantern Pharma (NASDAQ: LTRN) is a clinical-stage oncology-focused biopharmaceutical company leveraging its proprietary RADR^® AI and machine learning platform to discover biomarker signatures that identify patients most likely to respond to its pipeline of genomically-targeted therapeutics. By targeting drugs to patients whose genomic profile identifies them as having the highest probability of benefiting from the drug, Lantern’s approach represents the potential to deliver best-in-class outcomes.

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