Anti-aging drugs attempt to preserve or improve health and biological efficiency regardless of age. However, developing anti-aging drugs that are effective in humans has been difficult and elusive.
Taisho Pharmaceutical Co., Ltd. of Japan and Insilico Medicine of Hong Kong have recently conducted collaborative research to discover novel anti-aging therapies. “It is believed that aging is a universal phenomenon that we cannot stop. However, emerging scientific evidence has shown that one may be able to reverse some of the age-associated processes,” said Jimmy Yen-Chu Lin, Ph.D., CEO of Insilico Medicine Taiwan, a fully-owned subsidiary of Insilico Medicine, in a press release.
The discovery and development of drugs are essentially the most crucial translational science objectives that aim to improve human health and wellbeing. However, developing novel drugs is a highly complicated, expensive, and prolonged process that usually costs 2.6 billion USD and averages 12 years in length. Therefore, industries are urgently trying to address the challenge of figuring out how to minimize costs and the time it takes to develop a new drug. However, the combination of artificial intelligence (AI) and novel experimental technologies is expected to make the search for new pharmaceuticals cheaper, quicker, and more successful.
This collaboration combines Insilico’s cutting-edge AI drug discovery technology with Taisho’s experience in drug development, with the goal of prolonging human healthspan and longevity. “Through this collaboration, we will adopt our AI-powered drug discovery suites together with Taisho’s validation platform to explore the new space of anti-aging solutions,” said Dr. Lin. “We’re delighted to collaborate with Taisho pharmaceutical, a well-recognized leader in the pharmaceutical industry and healthcare sector,” said Dr. Lin.
In this collaboration, Insilico Medicine will be in charge of early target discovery. To accomplish this, PandOmics and Chemistry42, the target discovery and generative chemistry components of its Pharma.AI platform, will be used. Its deep biology analysis engine, in addition to its PandaOmics Discovery Platform for multi-omics target discovery, will locate new targets for anti-aging therapeutics. The Chemistry42 platform is capable of locating novel lead-like compounds via an automated, machine learning drug design and scalable engineering platform.
“The drug discovery process consists of many phrases and often takes decades. In preclinical phases, the failure rates are over 99%. Our AI can be used in all phases and, in some cases, leads to superhuman results. Our AI is exceptionally good at finding the molecular targets in specific diseases and inventing new chemistry,” said Alex Zhavoronkov, CEO of Insilico Medicine. Optimistically, the normal approach to design, synthesize, and validate a new drug candidate generally requires at least two years for completion. However, AI can accomplish the same tasks in just 46 days, which is 15 times faster than the finest pharmaceutical corporations.
Tokyo-based Taisho will evaluate the computer-generated molecules as soon as anti-aging therapeutic candidates have been found. With over a century of experience, Taisho Pharmaceutical Holdings possesses the greatest proportion of Japan’s pharmaceutical market for over-the-counter drugs.
“It is our great honor to be collaborating with scientists of Taisho Pharmaceutical, one of the top 100 pharmaceutical companies in the world operating since 1912,” said Alex Zhavoronkov, Ph.D., founder and CEO of Insilico Medicine, in a press release. “The high level of scientists we are interfacing, and our previous successes in the application of the Pharma.AI platform for discovery of novel targets and molecules in fibrosis, and previous experience in senolytic drug discovery gives us confidence that this collaboration will be successful.”
This method of drug development is becoming more popular as most large biopharma companies have comparable collaborations or internal projects. Sanofi has signed an agreement to employ UK start-up Exscientia’s AI platform to seek for metabolic disease medications, while Roche subsidiary Genentech is relying on an AI system from GNS Healthcare in Cambridge, Massachusetts, to aid the company’s quest for effective cancer therapeutics. If the proponents of these strategies are correct, AI and machine learning will open the door to a new era of drug development that is faster, cheaper, and more effective.
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