Dallas’ Lantern Pharma Hits Major Milestone on its AI Platform to Advance its Oncology Drug Research and Development

Lantern Pharma amassed 1 billion data points on its proprietary artificial intelligence platform, which it believes is the most of any company in biotech. Now, the company is able to reduce cost, time, and risk to establish a more sustainable route in oncology drug development.

On the heels of finalizing its IPO in the middle of COVID, Lantern Pharma, a clinical stage oncology biopharmaceutical firm headquartered in Dallas, has reached another major milestone: It has surpassed one billion data points on its proprietary artificial intelligence platform.

The announcement is significant because Lantern believes it is the most amassed by any company in the biotech sector.

Lantern aims to innovate the development of precision therapeutics in oncology. Its platform, RADR, uses machine learning, genomics, and AI to find biomarker signatures that could identify how a patient will respond to its pipeline of cancer treatments. Lantern says the tech could improve patient outcomes by uncovering, rescuing, or developing abandoned and failed drugs. 

Lantern describes the data points collected on the RADR platform as “genomic, transcriptomic, and drug sensitivity data points” that have been curated from its internal studies, published studies, and cancer datasets. In hitting one billion, it allows the company to predict combinations of drugs—from its own pipeline, those already on the market, or an existing drug with a new type of compound—that can be used together.

“We believe that the use of machine learning, genomics and computational methods can help accelerate the revitalization, refocusing and development of small molecule-based therapies,” the company said in a release. “By targeting drugs to patients whose genomic profile identifies them as having the highest probability of benefiting from the drug, this approach represents the potential to deliver best-in-class outcomes.”

The advancement merges real-world oncology data and large-scale biomarker analytics. Lantern said with this news, it can start to explore biomarker signatures that are generated by machine learning algorithms. 

Lantern also now has the opportunity to make the discovery of these oncology drugs faster, less risky, and more cost effective. According to the company, the current failure rates and long processes have led to high developmental costs—and that’s not sustainable for cancer patients.

The task of identifying new cancer therapies and discovering how existing compounds can affect different subtypes of cancer is one that can take years. But, with Lantern’s large scale data and powerful new algorithms, the company said that can be diminished to weeks.

The team plans to start increasing research activity to pursue key cancer indications. That includes looking at glioblastoma, lung cancer, prostate cancer, pancreatic cancer, and most recently, ovarian cancer.

RADR has already begun predicting how Lantern’s own drugs will work with these types of cancer, according to a news release. The one billion (and counting) data points saved months of time for these discoveries.

Lantern currently has three drug compounds, with two programs in clinical stages and two in pre-clinical. They focus on cancers that have “unique and unmet clinical needs,” as well as a clearly defined patient population, the company said.

The drugs are: LP-100 in a Phase 2 trial for the treatment of metastatic, hormone-refractory prostate cancer; LP-300, which is about to enter a Phase 2 trial for non-small cell lung cancer as a combination therapy; and LP-184, which is in pre-clinical development for genomically defined cancers.

Lantern seeks out experienced partners, advisors, and centers for its research, which includes the Fox Chase Cancer Center in Philadelphia and Georgetown University in Washington D.C.

Last year, we told you about the company teaming up with the Developmental Therapeutics Branch (DTB) of the National Cancer Institute (NCI) to help predict how a patient’s tumor may respond to drug therapy.

“Since our IPO in June, our proprietary RADR platform has quadrupled its collection of curated data points and allowed us to meet our goal a year ahead of schedule,” CEO Panna Sharma said in a statement. “Our growing AI platform will be pivotal in uncovering potential new therapeutic opportunities and developing insights into the creation of combination-therapy programs.”

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