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Lantern Pharma Inc. (NASDAQ: LTRN)

兰特纳制药公司 (NASDAQ: LTRN)

, an artificial intelligence (AI) company dedicated to developing cancer therapies and transforming the cost, pace, and timeline of oncology drug discovery and development, today announced the publication of its PCT patent application (PCT/US2024/019851) covering a novel machine learning solution for predicting blood-brain barrier (BBB) permeability.

，一家致力于开发癌症疗法并转变肿瘤药物发现和开发成本、速度及时间表的人工智能（AI）公司，今天宣布其PCT专利申请（PCT/US2024/019851）已公布，该申请涵盖了一种用于预测血脑屏障（BBB）通透性的新型机器学习解决方案。

The application received a favorable PCT search report indicating no significant prior art, substantially strengthening its path to approval..

该申请收到了一份有利的PCT检索报告，表明没有重大现有技术，大大加强了其获得批准的途径。

The technology has demonstrated to-date exceptional performance in predicting BBB permeability across a wide range of chemical compounds, processing up to 100,000 molecules per hour with industry-leading accuracy. Notably, Lantern's AI algorithms for BBB permeability prediction currently hold five of the top eleven positions on the Therapeutic Data Commons Leaderboard.

该技术迄今为止在预测各种化学化合物的血脑屏障通透性方面表现出卓越的性能，每小时可处理多达10万个分子，并具有行业领先的准确性。值得一提的是，Lantern用于血脑屏障通透性预测的AI算法目前在治疗数据共享平台排行榜上占据了前十一名中的五个位置。

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. Lantern believes that this breakthrough capability can accelerate the drug development process by rapidly identifying compounds likely to cross the blood-brain barrier, a critical factor in developing treatments for central nervous system disorders and brain cancers. These identified compounds can then be accelerated and further developed by researchers in cancer drug development and other fields saving time and cost in early-stage molecular characterization..

Lantern认为，这项突破性的能力可以加速药物开发过程，通过快速识别可能穿越血脑屏障的化合物，这是开发中枢神经系统疾病和脑癌治疗药物的关键因素。这些被识别的化合物可以由癌症药物开发及其他领域的研究人员进一步加速开发，在早期分子特性鉴定中节省时间和成本。

'The publication of this PCT patent application represents a significant advancement in our AI-driven approach to drug development,' stated Panna Sharma, Chief Executive Officer of Lantern Pharma. 'This innovative technology not only enhances our internal development capabilities but also offers transformative potential for our partners and collaborators across the pharmaceutical industry.

“这项PCT专利申请的发布代表了我们在人工智能驱动的药物开发方法上取得了重要的进展，” Lantern Pharma首席执行官Panna Sharma表示。“这项创新技术不仅增强了我们内部的开发能力，还为我们在制药行业的合作伙伴和协作者提供了变革性的潜力。”

The system's exceptional speed and accuracy in predicting BBB permeability positions Lantern at the forefront of CNS-targeted therapeutic development. We look forward to deploying this high-performing BBB model in collaboration with pharmaceutical partners and techbio-driven companies who seek to accelerate their development timelines while working with a partner committed to excellence, especially in the area of high-performing, predictive models for drug development.'.

该系统在预测血脑屏障通透性方面表现出的速度和准确性使其处于中枢神经系统靶向治疗开发的前沿。我们期待与制药合作伙伴及技术驱动的公司合作部署这一高性能的血脑屏障模型，帮助他们加快开发进程，同时与致力于卓越的伙伴合作，特别是在高性能、预测性药物开发模型领域。

The proprietary technology integrates advanced molecular representation techniques with synthetic data augmentation from features engineered from the chemical structure and bioactivity data which are then processed by leading-edge machine learning algorithms. Through integration with Lantern's RADR® AI platform, the system enables rapid and comprehensive assessment of both drug candidates and other molecules of interest for BBB permeability..

该专有技术将先进的分子表征技术与从化学结构和生物活性数据中提取的特征进行合成数据增强相结合，然后通过前沿的机器学习算法进行处理。通过与Lantern的RADR® AI平台整合，该系统能够快速且全面地评估药物候选物及其他目标分子的血脑屏障（BBB）渗透性。

Lantern's wholly-owned subsidiary,

灯笼的全资子公司，

Starlight Therapeutics

星光治疗学

, intends to implement this technology to advance the development of STAR-001 and evaluate additional drug candidates. In addition, Lantern is actively expanding the system's capabilities through the development of sophisticated sub-models that account for complex biological factors affecting BBB permeability.

，打算实施该技术以推动STAR-001的开发，并评估更多的候选药物。此外，Lantern正通过开发复杂的子模型来积极扩展系统的功能，这些子模型考虑了影响BBB通透性的复杂生物因素。

These enhancements are expected to further refine predictions by incorporating advanced features such as protein binding, active transport mechanisms, and disease-state modifications of the blood-brain barrier. This continued evolution of the technology demonstrates Lantern's commitment to maintaining its leadership position in AI-driven drug development..

这些改进预计将进一步完善预测，通过整合高级特性，如蛋白质结合、主动运输机制以及血脑屏障在疾病状态下的变化。这项技术的持续演进展示了Lantern致力于保持其在人工智能驱动的药物开发领域的领导地位。

The PCT application enables Lantern to pursue patent protection in major markets worldwide, with potential coverage extending 20 years from the filing date. The company has initiated expedited review in the United States to accelerate market deployment.

PCT申请使Lantern能够在主要国际市场寻求专利保护，潜在覆盖范围自申请日起延续20年。该公司已在美国启动加快审查程序，以加速市场部署。

This technological advancement reinforces Lantern's position as an innovator in AI-driven drug development and strengthens its ability to develop more effective, targeted CNS cancer therapies. The company expects this development to significantly impact both its internal drug development pipeline and future collaboration opportunities..

这一技术进步巩固了Lantern作为AI驱动药物开发领域创新者的地位，并增强了其开发更有效、更有针对性的中枢神经系统癌症疗法的能力。公司预计这一进展将对其内部药物开发管线及未来的合作机会产生重大影响。

ABOUT LANTERN PHARMA

关于灯笼制药

Lantern Pharma (NASDAQ: LTRN) is an AI company transforming the cost, pace, and timeline of oncology drug discovery and development. Our proprietary AI and machine learning (ML) platform, RADR

Lantern Pharma（纳斯达克股票代码：LTRN）是一家人工智能公司，正在改变肿瘤药物发现和开发的成本、速度和时间表。我们专有的人工智能和机器学习（ML）平台，RADR

®

®

, leverages over 100 billion oncology-focused data points and a library of 200+ advanced ML algorithms to help solve billion-dollar, real-world problems in oncology drug development. By harnessing the power of AI and with input from world-class scientific advisors and collaborators, we have accelerated the development of our growing pipeline of therapies that span multiple cancer indications, including both solid tumors and blood cancers and an antibody-drug conjugate (ADC) program.

，利用超过1000亿个专注于肿瘤学的数据点和包含200多种先进机器学习算法的库，帮助解决肿瘤药物开发中价值数十亿美元的实际问题。通过利用人工智能的力量，并结合世界级科学顾问和合作者的输入，我们加速了涵盖多种癌症适应症的不断增长的治疗管道的开发，包括实体瘤和血液癌以及抗体药物偶联物（ADC）项目。

Our lead development programs include a Phase 2 clinical program and multiple Phase 1 clinical trials. Our AI-driven pipeline of innovative product candidates is estimated to have a combined annual market potential of over $15 billion USD and have the potential to provide life-changing therapies to hundreds of thousands of cancer patients across the world..

我们的主要开发项目包括一项二期临床项目和多项一期临床试验。我们由人工智能驱动的创新候选产品管线估计拥有超过150亿美元的年度市场潜力，并有可能为全球数十万癌症患者提供改变生命的疗法。

Please find more information at:

请在以下位置查找更多信息：

Website:

网站：

www.lanternpharma.com

www.lanternpharma.com

LinkedIn:

LinkedIn:

https://www.linkedin.com/company/lanternpharma/

https://www.linkedin.com/company/lanternpharma/

X: @lanternpharma

X: @lanternpharma

FORWARD LOOKING STATEMENTS:

前瞻性声明：

This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. These forward-looking statements include, among other things, statements relating to: the potential advantages of our novel machine learning solution for predicting blood-brain barrier (BBB) permeability covered by PCT patent application (PCT/US2024/019851); the likelihood that the claims covered by PCT patent application (PCT/US2024/019851) will be subject to an issued patent in the U.S.

本新闻稿包含根据修订后的《1933年证券法》第27A条和修订后的《1934年证券交易法》第21E条所定义的前瞻性陈述。这些前瞻性陈述包括但不限于以下相关陈述：我们新颖的机器学习解决方案在预测血脑屏障（BBB）通透性方面的潜在优势，该方案已提交PCT专利申请（PCT/US2024/019851）；PCT专利申请（PCT/US2024/019851）中涵盖的权利要求很可能在美国获得专利授权。

or any foreign country; the potential advantages of our RADR® platform in identifying drug candidates and patient populations that are likely to respond to a drug candidate; and our intention to leverage the proprietary technology covered by PCT patent application (PCT/US2024/019851) to streamline and transform the pace, risk and cost of oncology drug discovery and development and to identify patient populations that would likely respond to a drug candidate.

或任何外国国家；我们的RADR®平台在识别可能对候选药物产生反应的候选药物和患者群体方面的潜在优势；以及我们打算利用PCT专利申请（PCT/US2024/019851）中涵盖的专有技术，精简和转变肿瘤药物发现与开发的速度、风险和成本，并识别可能对候选药物产生反应的患者群体。

Any statements that are not statements of historical fact (including, without limitation, statements that use words such as 'anticipate,' 'believe,' 'contemplate,' 'could,' 'estimate,' 'expect,' 'intend,' 'seek,' 'may,' 'might,' 'plan,' 'potential,' 'predict,' 'project,' 'target,' “model,” 'objective,' 'aim,' 'upcoming,' 'should,' 'will,' 'would,' or the negative of these words or other similar expressions) should be considered forward-looking statements.

任何非历史事实的陈述（包括但不限于使用“预期”、“相信”、“考虑”、“可能”、“估计”、“预计”、“打算”、“寻求”、“或许”、“应该”、“将”、“会”或这些词的否定形式或其他类似表述的陈述）均应视为前瞻性陈述。

There are a number of important factors that could cause our actual results to differ materially from those indicated by the forward-looking statements, such as (i) the risk that no U.S. or foreign patents are issued with respect to the novel machine learning solution for predicting b.

可能导致我们的实际结果与前瞻性陈述所表明的结果存在重大差异的重要因素包括：(i) 与用于预测b的新型机器学习解决方案相关的美国或外国专利未能获得的风险。

www.lanternpharma.com

www.lanternpharma.com

or on the SEC's website at

或在SEC的网站上

www.sec.gov

www.sec.gov

. Given these risks and uncertainties, we can give no assurances that our forward-looking statements will prove to be accurate, or that any other results or events projected or contemplated by our forward-looking statements will in fact occur, and we caution investors not to place undue reliance on these statements.

鉴于这些风险和不确定性，我们无法保证我们的前瞻性陈述将被证明是准确的，或我们前瞻性陈述中预测或考虑的任何其他结果或事件将实际发生，我们提醒投资者不要过分依赖这些陈述。

All forward-looking statements in this press release represent our judgment as of the date hereof, and, except as otherwise required by law, we disclaim any obligation to update any forward-looking statements to conform the statement to actual results or changes in our expectations..

本新闻稿中的所有前瞻性陈述均代表我们截至本日期的判断，且除非法律另有要求，我们不承担任何更新前瞻性陈述以使该陈述符合实际结果或我们预期的变化的义务。

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Therapeutics Data Commons is a resource to access and evaluate AI methods, supporting the development of AI methods, with a strong bent towards establishing the foundation of which AI methods are most suitable for drug discovery applications and why. It can facilitate algorithmic and scientific advances and accelerate AI method development, validation and transition into biomedical and clinical implementation.

治疗数据共享平台是一个访问和评估人工智能方法的资源，支持人工智能方法的发展，特别倾向于建立哪些人工智能方法最适合药物发现应用及其原因的基础。它可以促进算法和科学的进步，加速人工智能方法的开发、验证，并向生物医学和临床实施过渡。

The Commons curates benchmarks for key therapeutic tasks. Every benchmark has a carefully designed ML task, ML-ready dataset, a public leaderboard, and a set of performance metrics to support model evaluation, providing effective indicators of the performance of ML methods in real-world scenarios. Visit .

Commons 精心策划了关键治疗任务的基准。每个基准都有一个精心设计的机器学习任务、可直接用于机器学习的数据集、公开的排行榜以及一套性能指标，以支持模型评估，提供在现实场景中机器学习方法性能的有效指标。访问 。

https://tdcommons.ai

https://tdcommons.ai

View source version on businesswire.com:

查看 businesswire.com 上的源版本：

https://www.businesswire.com/news/home/20250219931339/en/

https://www.businesswire.com/news/home/20250219931339/zh/

Investor Relations

投资者关系

ir@lanternpharma.com

ir@lanternpharma.com

(972)277-1136

(972)277-1136

Source: Lantern Pharma Inc.

来源：Lantern Pharma Inc.

Released February 19, 2025

2025年2月19日发布