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Insilico signs $200M AI drug discovery partnership with China’s CTFH

Shortly after publishing a paper demonstrating how its artificial intelligence programs could generate viable lead compounds in just a few weeks, Insilico Medicine has signed a dual-program discovery collaboration with Jiangsu Chia Tai Fenghai Pharmaceutical worth up to $200 million.

Focused on previously undruggable targets in triple-negative breast cancer, the deal includes an upfront payment along with potential milestones and sales-based royalties pegged to any eventual products.

“We are very pleased to establish the partnership with Insilico Medicine, entering the new era of AI-enabled drug development,” Wenyu Xia, general manager of the China-based pharma company, said in a statement. “We look forward to a long-term partnership with Insilico Medicine.”

At Tech’s Leading Edge, Worry About a Concentration of Power

The research scientists’ warnings come amid rising concern about the power of the big tech companies. Most of the focus has been on the current generation of technology — search, online advertising, social media and e-commerce. But the scientists are worried about a barrier to exploring the technological future, when that requires staggering amounts of computing.


Each big step of progress in computing — from mainframe to personal computer to internet to smartphone — has opened opportunities for more people to invent on the digital frontier.

But there is growing concern that trend is being reversed at tech’s new leading edge, artificial intelligence.

Computer scientists say A.I. research is becoming increasingly expensive, requiring complex calculations done by giant data centers, leaving fewer people with easy access to the computing firepower necessary to develop the technology behind futuristic products like self-driving cars or digital assistants that can see, talk and reason.

Qingsong Zhu at Ending Age-Related Diseases 2019

Dr. Qingsong Zhu, the COO of Insilico Medicine, discussed the use of deep learning in creating biomarkers for aging. Initially discussing existing clocks and the problems with animal translation, he went on to discuss what sorts of markers are ideal for age-related research and the details of training and testing a model that works with these markers, showing that a deep model compares favorably to other models.

He also used his model to show that smoking does, in fact, cause accelerated aging.

Researchers design new material using artificial intelligence

Researchers at TU Delft have developed a new supercompressible but strong material without conducting any experimental tests at all, using only artificial intelligence (AI). “AI gives you a treasure map, and the scientist needs to find the treasure,” says Miguel Bessa, first author of a publication on this subject in Advanced Materials on 14 October.

Foldable bicycle

Miguel Bessa, assistant professor in and engineering at TU Delft, got the inspiration for this research project during his time at the California Institute of Technology. At a corner of the Space Structures Lab, he noticed a satellite structure that could open long solar sails from a very small package.

“Metabesity and Longevity: USA Special Case Study” is an 85-page open-access analytical report produced jointly

By and Targeting Metabesity to examine the links between metabesity, Longevity and the USA’s current health shortfalls, including low health-adjusted life expectancy (“HALE”) and the large gap between HALE and life expectancy, despite its extremely high per-capita healthcare expenditures, and to chart policy recommendations to neutralize this vast health vs wealth deficit.


€œMetabesity and Longevity: USA Special Case Study € is an 85-page open-access analytical report produced jointly by Aging Analytics Agency and Targeting Metabesity to examine the links between metabesity, Longevity and the USA €™s current health shortfalls, including low health-adjusted life expectancy ( €œHALE €) and the large gap between HALE and life expectancy, despite its extremely high per-capita healthcare expenditures, and to chart policy recommendations to neutralize this vast health vs wealth deficit.

Link to Special Case Study: https://aginganalytics.com/longevity-usa/

As the issue of aging population intensifies, sick care will become increasingly expensive and ineffective. America needs to rapidly deploy a government-led shift from treatment to prevention, and from prevention to precision health, using deep diagnostics and prognostics in combination with biomarkers of aging, metabesity, health and intervention-effectiveness, to delay the onset of disease with as minimal intervention as possible, as early as possible. Seeking synergies between Longevity research, P4 (preventive, personalized, precision and participatory) medicine and Artificial Intelligence has the potential to enable rapid and widespread policy and infrastructural reforms for USA healthcare to quickly boost National Healthy Longevity, but only with sufficient government commitment.

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