TechCrunch News 2024年12月03日
Orakl Oncology combines data and biology to bring new drugs to cancer patients
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癌症发病率不断上升,尤其是在年轻人中,但大多数新药化合物无法通过临床试验。Orakl Oncology是一家利用人工智能优化临床试验设计的初创公司,致力于解决肿瘤药物研发效率低下的问题。该公司将数据和生物学相结合,创建患者肿瘤的虚拟模型,并开发预测药物疗效和验证药物效果的工具。Orakl Oncology希望通过其创新技术,加速精准医疗药物的发现,将更多有效的药物输送到患者手中,应对癌症治疗的挑战。

🤔 **癌症发病率上升,尤其是在年轻人中,但新药研发进展缓慢,临床试验成功率低。** 许多新药化合物无法通过临床试验,这并非意味着药物本身不好,而是临床试验设计可能存在问题,需要更有效的方法来测试新分子,尤其是在近年来创新进展缓慢的癌症领域。

🧬 **Orakl Oncology利用人工智能优化临床试验设计,创建肿瘤虚拟模型。** 该公司将数据和生物学相结合,创建了结合真实患者背景和组织的虚拟模型(器官类器官),并结合40多个患者变量进行分析,克服了数据量不足的挑战,最初专注于结直肠癌和胰腺癌。

🚀 **Orakl Oncology开发了O-Predict和O-Validate两款产品,分别用于预测患者对药物的反应和验证药物效果。** O-Predict更适合药物开发人员,而O-Validate则可以服务于人工智能和数据驱动的生物技术公司,帮助加速药物研发和临床试验过程。

💰 **Orakl Oncology已获得近1500万欧元的融资,将用于组建商业团队,推动产品商业化。** 这家初创公司希望能够加速精准医疗药物的发现,为患者提供更多有效的治疗选择,应对癌症治疗的挑战。

🎯 **Orakl Oncology的创始人Fanny Jaulin希望通过技术创新,加速精准医疗药物的发现,将更多有效的药物输送到患者手中。** 随着癌症成为慢性疾病,现有的治疗手段难以满足需求,她希望能够打通精准医疗药物发现流程的瓶颈,为患者带来更多希望。

Cancer incidence is on the rise, particularly among younger adults, but most new drug compounds fail to progress through clinical trials. According to French entrepreneur Fanny Jaulin (on the right in the picture above), the problem lies with clinical trial design. 

“Just because a drug isn’t successful in clinical trials doesn’t mean it’s not a good drug,” she told TechCrunch. Hence the need for better ways to trial new molecules, especially for cancers in which innovation has failed to make a dent in recent decades.

Her startup, Orakl Oncology, applies AI to this problem, but Jaulin is prompt to admit that her team is far from being the only one doing so. In fact, she thinks AI is becoming table stakes in drug discovery. But that’s not where Orakl’s differentiation lies, she said.

Founded in 2023 as a spinoff from the Gustave Roussy Institute of Oncology, Orakl operates at the intersection of data and biology, which makes it different from companies that only do one or the other, and more akin to Tempus, the AI healthtech that went public earlier this year.

Both sides are complementary; the data side helps deal with the fact that each tumor is unique, while the biology side is the best way to take the complexity of cancer into account, Jaulin said.

The result is hybrid, with avatars that combine the background of real patients with tissue. Currently, this means working on organoids, which are miniaturized, simplified in vitro versions of an organ that can be used for trials. 

As for the data layer, it includes some 40 variables per patient, which makes up for the fact that its corpus is still smaller compared to its larger competitors, and with an initial focus on colorectal and pancreatic cancers.

With this basis in place, Orakl plans to commercialize two products: O-Predict, which helps customers forecast patient response to a drug candidate, and O-Validate, where the process goes the other way around. This makes the former better suited for drug developers, while the latter can also serve AI- and data-led biotech companies, Jaulin said.

This commercialization plans will be funded by the seed round it has just raised, and which comes in addition to the €3 million pre-seed round the startup secured in 2023. Led by European VC fund Singular, it also follows some non-dilutive funding from Bpifrance including the Grand Prix i-Lab, bringing Orakl’s total capital raised to date to nearly €15 million.

While most of the proceeds will go toward building a commercial team to close contracts, it is not what made Jaulin become an entrepreneur. With cancer becoming a chronic disease and a therapeutic arsenal “undersized for what’s at stake,” her long-term goal is to unblock the precision medicine discovery process to “get as many drugs as possible to patients.”

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Orakl Oncology 人工智能 肿瘤药物研发 精准医疗 临床试验
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