On June 29, 2020 Lantern Pharma (NASDAQ: LTRN), a clinical stage biotechnology company focused on leveraging artificial intelligence ("A.I."), machine learning and genomic data to streamline the drug development process and to identify the patients that will benefit from its targeted oncology therapies, reported that it surpassed the milestone of 450 million curated data points being utilized in its proprietary A.I. and machine learning-powered platform, RADR (Response Algorithm for Drug Positioning and Rescue) (Press release, Lantern Pharma, JUN 29, 2020, View Source [SID1234561531]).
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RADR leverages genomic, transcriptomic, clinical and drug sensitivity data points across more than 145 drugtumor interactions to predict the potential response cancer patients will have to potential drugs, therefore enabling a more personalized approach to therapy that is aimed at better outcomes. Lantern is establishing collaborations and partnerships to expand the functionality of RADR, including algorithms that can operate 200 to 300 percent faster than its existing algorithms, enabling the company to develop robust, gene signatures that can be used to guide patient enrollment in trials and as a companion diagnostic (CDx). During the most recent data enrichment campaign, Lantern focused on significantly increasing the depth and amount of data for: nonsmall cell lung cancer, ovarian cancer, glioblastoma, and gliomas. Reaching this milestone of over 450 million curated data points for oncology drug development will bring greater precision and speed in helping Lantern with its objective of personalizing oncology therapy with reduced risk and cost.
"Our approach in leveraging machine learning to develop biologically relevant, multi-gene signatures in days or weeks allows our team to more efficiently review and test novel insights about the complex mechanisms that can drive patient response to a drug," said Panna Sharma, CEO of Lantern Pharma.
As a pioneer in the application of machine learning to oncology-focused drug development and clinical trial design, Lantern has published gene signatures derived from RADR as posters and presentations at both ASCO (Free ASCO Whitepaper) and AACR (Free AACR Whitepaper). Lantern’s pipeline of compounds includes one candidate in an active Phase 2 clinical trial for metastatic, hormone-refractory prostate cancer using a genomic signature for patient selection; another candidate in preparation for a Phase 2 clinical trial in non-small cell lung cancer in a targeted patient population; and a third candidate in two pre-clinical programs for biomarker-defined solid tumors and glioblastoma.
Mr. Sharma continued, "Because of the increasing availability of large-scale biomarker, genomic and patient data, and rapidly maturing technologies like artificial intelligence and machine learning, oncology is undergoing a monumental shift in the way cancer drugs are discovered, developed, studied, targeted, and commercialized. Lantern is at the forefront of this transformation. For Lantern, exceeding 450 million data points is a significant milestone in our work, and demonstrates our commitment to leveraging paradigm changing technologies that transform oncology drug development with the ultimate objective of cost-effectively personalizing treatment for patients."
Lantern Pharma is ahead of the initial platform development schedule, reaching 400 million data points by the end of 2020, which puts Lantern on track to reach over 1 billion data points earlier than expected. The developmental focus on increasing the number of data points, and improving the performance of the algorithms is expected to yield additional targeted indications for Lantern’s current pipeline of drugs, and also help to uncover additional compounds and therapies that can be in-licensed or acquired and subsequently developed in a more efficient manner that leverages the insights from Lantern’s data-driven, A.I.-enabled approach.
The market opportunity for RADR as a platform for the development of targeted oncology therapies is significant. The highly scalable RADR platform can be leveraged in multiple real-world applications, in addition to drug development, including: identifying potential drug combinations, predicting synergies with immune-oncology agents, developing companion diagnostics (CDx) and evaluating compounds for therapeutic efficacy and optimal positioning. Lantern is a pioneer in the adoption and implementation of data-driven and machine-learning enabled processes for drug development. The intersection of A.I., machine learning and genomics is considered a rapidly growing trend as researchers and investors turn to big data approaches to transform the cost, risk and timeline of oncology drug development.
"Lantern Pharma is using genomics, machine-learning and big data in an effort to develop potentially life-saving cancer drugs, and our ability to fulfill this mission with greater efficiency and speed will be enhanced by focusing on the overall strength and scale of our platform," concluded Mr. Sharma.