早期數據顯示人工智能產生的藥物或可延緩衰老

Recently The New York Times reported the following:

Early Data Indicates an A.I.-Generated Drug Could Slow Aging

Artificial intelligence was used to help develop a drug candidate, rentosertib, for a rare lung condition. Its maker says the drug also seems to reduce the biological hallmarks of age.

The NYT - By Cade Metz - Reporting from San Francisco (Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.)

Sept. 7, 2026

Last year, a clinical trial conducted by Insilico Medicine, a company that aims to accelerate drug discovery using artificial intelligence, indicated that one of its drug candidates could help treat patients suffering from a chronic lung disease.

Now, the company says that data from the same clinical trial shows a more intriguing possibility: that the drug could also slow the aging process.

The molecular structure of the drug, called rentosertib, was generated with the assistance of A.I. Results of the new study, published Monday in the journal Nature Biotechnology, show that the drug reduced the biological markers of age as measured by six “aging clocks,” a different kind of A.I. technology designed to predict a person’s morbidity and mortality.

This elaborate clinical trial is a milestone in the widespread effort to improve health care using the same A.I. techniques that underpin popular chatbots like ChatGPT and image generators like Midjourney. Insilico is just one of many start-ups, tech giants and academic labs working to accelerate drug discovery and hone other medical tasks with help from these methods.

The recent rise of aging clocks is helping to push these efforts beyond short-term treatments and into the realm of longevity research. These systems estimate how quickly a person’s body is aging — or even how quickly individual organs are aging relative to the rest of the body. But scientists continue to debate how much useful information these so-called clocks are able to provide.

While Insilico’s clinical trial shows the promise of several A.I. techniques, its drug candidate could still be years away from regulatory approval, even for use in sick patients. And the company has not yet tested its anti-aging effects in healthy patients.

“This drug looks encouraging,” said Eric Topol, a cardiologist and the author of the book “Super Agers.” “But we do not yet have a definitive trial to make the final judgment.”

Insilico began exploring the new wave of A.I. technologies more than a decade ago. Founded in 2014 by Alex Zhavoronkov, a Latvian-Canadian mathematician, physicist and biotechnologist, the company was among the earlier efforts to streamline drug discovery using what are called neural networks.

Using techniques similar to those that train A.I. systems like ChatGPT, Insilico first built a model to analyze a giant pool of data spanning health records for thousands of medical patients; blood tests describing the microscopic proteins created inside their bodies; and myriad academic papers detailing the effects of these proteins. With this system, the company is trying to identify particular proteins that lead to illness and disease.

Insilico then built a second system that analyzes troves of data describing the physical shape of proteins and the way these tiny biological mechanisms bind to other molecules. This system is designed to generate entirely new molecules that could bind to a particular drug target and neutralize its effects.

“It is like scanning a lock and generating a key that fits the lock,” Dr. Zhavoronkov said in an interview.

This is how he and his company developed rentosertib, which is meant to treat a disease called idiopathic pulmonary fibrosis, or I.P.F. Sometimes called “the Alzheimer’s of the lungs,” I.P.F. is a chronic disease that thickens and scars pulmonary tissue, reducing its ability to move oxygen into the bloodstream. The condition can lead to death, even within a few years.

Last year, with its clinical trial, Insilico showed that its drug candidate could significantly expand air capacity inside the lungs of patients who had I.P.F. But that was only part of the trial. Dr. Zhavoronkov said his company also designed the drug in an effort to generally extend a patient’s life span.

Separate from the tests involving I.P.F., the trial used six aging clocks to measure the markers of age in patients both before and after treatment with the drug. Across the 43 patients who participated in the trial, the clocks — which essentially try to predict a person’s age based on measurements of how well their cell, tissues and organs are functioning — showed significant reductions in the predicted age.

Each clock relies on a different analysis of those markers that yields a different prediction. During the trial, all six clocks showed a reduction in predicted age after patients took the drug for 12 weeks.

“This is the first study that shows, very clearly, that predicted biological age can be reduced,” said Vadim Gladyshev, a Harvard Medical School professor who helped build one of these aging clocks.

He acknowledged, however, that the study was far from conclusive, pointing out that the sample size was small and that aging clocks are not always reliable. Most notably, Insilico’s drug has not yet been tested in healthy patients: Because the company conducted its clinical trial solely with I.P.F. patients, the results could be unique to those with this particular condition.

But some experts believe that Insilico’s elaborate study could serve as a blueprint for future longevity research.

“These are methods we will use in future trials,” said Evelyne Bischof, a professor of medicine at Tel Aviv University who specializes in longevity.

Translation

早期數據顯示人工智能產生的藥物或可延緩衰老

人工智能被用於輔助開發一種名為 rentosertib 的候選藥物，用於治療一種罕見的肺部疾病。其研發者表示，該藥物似乎還能減少老化的生物學特徵。

去年，一家名為 Insilico Medicine 的公司進行的臨床試驗表明，該公司的一種候選藥物可能有助於治療慢性肺部疾病患者。 Insilico Medicine 致力於利用人工智能加速藥物研發。

如今，該公司表示，來自同一臨床試驗的數據顯示出更令人感興趣的可能性：該藥物或許還能延緩老化過程。

這種名為 rentosertib 的藥物的分子結構是在人工智能的輔助下產生的。這項週一發表在《自然·生物技術》雜誌上的新研究結果顯示，該藥物降低了六種「老化時鐘」所測量的生物年齡標記。 「老化時鐘」是一種人工智能技術，旨在預測人們的發病率和死亡率。

這項精心設計的臨床試驗是利用人工智能技術改善醫療保健這項廣泛努力的一個里程碑。這些人工智能技術也應用於 ChatGPT 等熱門聊天機器人和 Midjourney 等影像產生器。 Insilico 只是眾多致力於利用這些方法加速藥物研發，並改善其他醫療任務的新創公司、科技巨頭和學術實驗室之一。

老化時鐘的興起正推動這些研究超越短期治療，邁向長壽研究領域。這些系統可以估算人體老化的速度，甚至可以估算單一器官相對於身體其他部位的老化速度。但科學家仍在爭論這些所謂的「時鐘」究竟能提供多少有用的信息。

儘管 Insilico 的臨床試驗展現了多項人工智能技術的潛力，但其候選藥物距離獲得監管部門批准可能仍需數年時間，即使是用于重病患者。而且，該公司尚未在健康的受試者身上測試其抗衰老效果。

心臟病專家、《超級老齡者》(Super Agers)  一書的作者 Eric Topol 說: “這種藥物看起來很有希望”，“但我們還沒有進行最終的臨床試驗來做出最終判斷。”

Insilico 公司在十多年前就開始探索新一代人工智能技術。該公司由拉脫維亞裔加拿大籍數學家、物理學家和生物技術專家 Alex Zhavoronkov 於 2014 年創立，是早期利用神經網絡去使藥物研發流程達到更有效率的公司之一。

Insilico 公司採用類似於訓練 ChatGPT 等人工智能系統的技術，首先建立了一個模型來分析龐大的資料池，這些資料包括數千名患者的健康記錄、描述其體內產生的微小蛋白質的血液檢測結果，以及大量詳細闡述這些蛋白質作用的學術論文。利用這套系統，該公司正試圖辨識導致疾病的特定蛋白質。

隨後，Insilico 構建了第二個系統，用於分析海量數據，這些數據描述了蛋白質的物理結構以及這些微小的生物機制與其他分子的結合方式。這個系統是用來生成全新的分子，這些分子可以結合特定藥物的目標對像並消滅它。

Zhavoronkov 博士在一次採訪中說道: 「這就像先掃描一把鎖，然後造出一支可開啓它的鑰匙」。

他和他的公司正是利用這種方法開發了 rentosertib，一種用於治療特發性肺纖維化（IPF）的藥物。 IPF 有時被稱為 “肺部阿茲海默症” ，是一種慢性疾病，會導致肺組織增厚和形成疤痕，從而降低肺部將氧氣輸送到血液的能力。這種疾病甚至可能在幾年內導致死亡。

去年，Insilico公司透過臨床試驗表明，其候選藥物能夠顯著擴大特發性肺纖維化（IPF）患者的肺部容量。但這只是試驗的一部分。 Zhavoronkov 博士表示，該公司研發該藥物的另一個目的是延長患者的壽命。

除了針對IPF的試驗外，該試驗還使用了六種老化時鐘來測量患者在用藥前後各項年齡指標的變化。在參與試驗的43名患者中，這些時鐘 - 它們本質上是根據測量一個人的細胞、組織和器官運作情況來預測其屬於的年紀- 顯示預測的年齡有顯著降低。

每種老化時鐘都基於不同的指標分析方法，因此預測結果也不同。試驗期間，所有六種老化時鐘均顯示，患者服用藥物12週後，預測年齡有所降低。

曾參與建造了其中一個衰老時鐘的哈佛醫學院教授 Vadim Gladyshev 說道:「這是第一個研究非常清楚地表明預測的生物年齡是可以下降的」。

然而，他也承認這項研究遠未得出結論，指出樣本量較小，而且老化時鐘並非總是可靠的。尤其值得注意的是，Insilico公司的藥物尚未在健康的受試者中進行測試：由於該公司僅針對特發性肺纖維化（IPF）患者開展了臨床試驗，因此研究結果可能僅適用於患有這種特定疾病的患者。

但一些專家認為，Insilico 公司這項精心設計的研究可以為未來的長壽研究提供藍圖。

特拉維夫大學的專門研究長壽的醫學教授 Evelyne Bischof 說:「這些是我們在未來試驗將會採用的方法」。

So, a clinical trial conducted by Insilico Medicine has indicated that one of its drug candidates could help treat patients suffering from a chronic lung disease. Now, the company says that data from the same clinical trial shows a more intriguing possibility: that the drug could also slow the aging process. However, it is also acknowledged that the study is far from conclusive as the sample size is small and that aging clocks are not always reliable. Yet, Insilico’s study could probably serve as a blueprint for future longevity research.

Note:

1. The core idea of the book entitled Super Agers: An Evidence-Based Approach to Longevity written by Dr. Eric Topol is that science and technology have converged to create a breakthrough moment where we can significantly extend human "healthspan"—the number of years lived free from debilitating chronic disease—rather than just extending lifespan.  (Google)