#drug-discovery

#drug-discovery

At Sanofi, AI has shifted from experimentation to becoming a vital part of our infrastructure. It now powers our R&D decisions, our supply chain and manufacturing processes, and most importantly how we discover and develop medicines. All businesses that have implemented AI in an impactful way face challenges, such as skills gaps and uncertainty, but you move beyond that by embedding AI deeply into teams and systems. This enables AI to become a key, reliable source of sustained productivity and innovation.

Now, researchers have created an artificial-intelligence system that vastly simplifies and accelerates the process of chemical synthesis. The system, which is called MOSAIC and is described in a study published in Nature on 19 January, recommended conditions that researchers were able to use to generate 35 compounds with the potential to become products like pharmaceuticals, agrochemicals or cosmetics without needing to do any further trawling or tweaking.

There's vastness far closer to us that transcends even the stars. It may seem impossible but there are, in fact, more possible chemical compounds in our world than stars across the sky. And it's not close: A conservative estimate suggests the number of small, drug-like molecules out there is somewhere around 10^60, while the number of stars in the observable universe lingers around 10^22 (perhaps 10^24 by some estimates).

The biggest story in tech is AI's increasing capacity to take on tasks once reserved for human beings. But the agents driving that change aren't machines. They're humans-inventive, ambitious, enterprising ones. Our third annual roundup of some of the field's most intriguing players includes scientists and ethicists, CEOs and investors, big-tech veterans and first-time founders. These 20 innovators are tackling challenges from training tomorrow's AI models to speeding drug discovery to reimagining everyday productivity tools.

In those five years, AlphaFold 2 and its successor AI models have become almost as fundamental and ubiquitous tools of biochemical research as microscopes, petri dishes, and pipettes. The AI models have begun to transform the way scientists search for new medicines, promising faster and more successful drug development. And they are starting to help scientists work on solutions to everything from ocean pollution to creating crops that are more resilient to climate change.

Silicon Valley's obsession with software has created a blind spot, and it might be where the next AI revolution begins, said Reid Hoffman. The LinkedIn cofounder said on an episode of the a16z podcast published Monday that the tech industry's "everything should be done in software" mindset has become a limitation. That belief, which fueled decades of Silicon Valley success, now risks keeping innovators from seeing new opportunities, Hoffman said.

Neural networks are some of the most promising artificial intelligence (AI) models. These systems process data similarly to the human brain, passing information through a complex network of nodes in the same way information goes through layers of neurons. That makes them capable of solving complicated problems in minimal time, which is particularly advantageous in the medical industry. Drug discovery is a vital but challenging process.

The desire to stop your own tragedies from happening to someone else may be a strong motivator. However, the process of drug discovery has always been grindingly, gruelingly slow.

Testimony revealed the presence of baby oil and multiple bags of Astroglide lubricant in hotel room 2115, raising questions about their intended use.

The incident began with a traffic stop that revealed a raccoon named Chewy in the driver’s seat, humorously holding a meth pipe.