On May 6, 2024 Lantern Pharma Inc. (NASDAQ: LTRN), a leading artificial intelligence (AI) oncology drug discovery and development company, reported a strategic AI-driven collaboration with French biotechnology company, Oregon Therapeutics to optimize the development of its first-in-class protein disulfide isomerase (PDI)(1) inhibitor drug candidate XCE853 in novel and targeted cancer indications (Press release, Lantern Pharma, MAY 6, 2024, View Source [SID1234642697]). Lantern will be leveraging its proprietary RADR AI platform to uncover biomarkers and efficacy-associated signatures of XCE853 across solid tumors that can aid in precision development. Collaborative efforts are expected to identify biomarker signatures that can be used to stratify tumors most responsive to XCE853 and guide potential future clinical development and patient selection. Oregon Therapeutics is developing XCE853 in various cancer indications, including drug-resistant ovarian and pancreatic cancer, certain hematological cancers and several pediatric cancers including CNS cancers.
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PDIs are promising targets for cancer therapy raising clinical interest recently2 notably for their potential in cancers of poor prognosis like breast cancer3 or ovarian cancer. Up-regulated expression of PDIs was found to be associated with worse clinical outcome in numerous cancers such as hepatocellular carcinoma(4), as well as breast and ovarian cancers(5). PDIs are protein chaperones and are central to maintaining cancer cell metabolism, additionally PDI inhibitors can cause cancer cell death through the accumulation of impaired proteins and dysregulated cellular stress responses. A combination of these effects is known as proteotoxicity, a unique and promising therapeutic strategy that may be especially effective in targeting cancers that are resistant to therapy.
In the US, nearly 612,000 people(6) are projected to die from cancer in 2024 and, resistance to anticancer drugs will be implicated in 90% of those deaths(7). To date, no PDI inhibitor has reached the clinic due to the complexities related to selecting and mapping the molecules that will most accurately target the right PDI enzymes. There are more than 20 PDI enzymes, with each playing a slightly different and often biologically redundant role. Oregon Therapeutic’s lead drug-candidate XCE853 is known to target PDIs of specific interest for cancer. Lantern Pharma and Oregon Therapeutics believe that computational tools, including foundational models, machine learning and large-scale molecular analysis can offer an ideal and streamlined pathway for breaking through these data and decision complexities – making RADR the perfect platform for better informing the role XCE853 can play in effective cancer treatment. (8, 9)
"To date, our first-in-class metabolic inhibitor, XCE853, has exhibited robust preclinical efficacy in both in vitro and in vivo models across multiple cancer types," said Marc-Henry PITTY, MD, CEO of Oregon Therapeutics. "Lantern’s RADR AI platform will leverage the in vitro and in vivo data to potentially advance XCE853 development in a highly targeted manner and will help inform disease indications and biomarker signatures that can aid in the design of future clinical trials and in the pursuit of combination therapies with other approved cancer drugs. Our team is looking forward to efficiently selecting among the landscape of ideal development options and efficiently de-risking future clinical development decisions." Oregon Therapeutics has previously performed preclinical studies indicating that in addition to ovarian and pancreatic cancer, XCE853 may also be particularly active in renal, prostate, lung, breast, and head and neck cancers, and leukemia based on preclinical cell-line studies. Oregon project leader, Sandrine Courtès PhD, who has been developing the collaboration with Lantern Pharma, stated: "PDIs Inhibitors have a great potential, since this molecular target is highly expressed in several cancer types, supports tumor growth and is associated with clinical outcomes."
The collaboration focuses on the integration and interrogation of molecular, genetic and transcriptomic data pertaining to XCE853. This analysis will be powered by RADR and its growing library of over 60 billion data points from many diverse types of biological measurements and oncology experiments, as well as more than 200 ML algorithms focused on problems that are central to real-world cancer drug development. The initial objectives of the collaboration are to:
1) uncover biomarkers and efficacy-associated gene signatures to guide in the eventual stratification and selection of patients for future clinical trials,
2) identify tumor-based response and resistance mechanisms to XCE853 and strategies to overcome treatment resistance, and
3) expand the use of XCE853 in additional therapeutic cancer indications for XCE853.
"Drug development teams have found significant data and modeling challenges in regard to tackling the complexities associated with PDI inhibitors given the challenges with creating meaningful models, and accumulating and deciphering the data," said Panna Sharma, CEO and President of Lantern Pharma. "Our AI platform, RADR, can increase the confidence, insights, and comfort levels in developing data-driven development paths by modeling highly complex scenarios at a scale that only has become possible recently. It’s an ideal approach for Oregon Therapeutics, which has executed a series of highly targeted in vivo and in vitro experiments and is poised to make incredibly important and patient-centric decisions about the clinical future of the molecule. That’s where RADR can play a highly essential and market defining role."
Under the terms of the collaboration, Lantern Pharma is receiving equal IP co-ownership and drug development rights in newly discovered biomarkers, novel indications, and/or new pharmacological use strategies for XC853 and related analogues. Oregon Therapeutics is entitled to financial benefits resulting from the out licensing of the background IP to Lantern Pharma. Lantern Pharma and Oregon Therapeutics are both entitled to additional financial benefits resulting from the out licensing of any collaboration IP to a third party. No further financial details regarding the collaboration were disclosed.
About RADR
RADR is Lantern Pharma’s proprietary integrated AI platform for large-scale biomarker and drug-tumor interaction data analytics that leverages machine learning. It is used to provide mechanistic insights about drug-tumor interactions, predict the potential response of cancer types and subtypes to existing drugs and drug candidates, and uncover patient groups that may respond to potential therapies being developed by Lantern Pharma and its collaborators.
RADR uses an ensemble-based approach to apply its library of algorithms to statistical, correlative, and inferential problems in drug-tumor interactions. This allows the platform to rapidly analyze large amounts of complex data and predict how both patients and tumors will respond to therapeutic combinations. RADR also evolves as new datasets are added, which improves and sharpens the insights generated from the algorithms.
RADR’s highly scalable machine-learning methods are designed to guide drug development and yield new biological insights, while also having the potential to increase response rates and improve outcomes in clinical trials. The robustness and growing number of datasets powering RADR is anticipated to continue to improve machine-learning results, accelerate automation of other features and aid oncology drug development for Lantern and its partners with an ultimate focus on benefitting cancer patients.