AI Drug Discovery Is $50-Billion Opportunity for Big Pharma

AI Drug Discovery Is $50-Billion Opportunity for Big Pharma

By Bloomberg, May 18, 2023

Research firm Deep Pharma Intelligence estimates that investments in AI-driven drug discovery companies have tripled over the past four years, reaching $24.6 billion in 2022.

Credit: Michele Marconi

Drugmakers worldwide are adopting artificial intelligence (AI) in the hope of accelerating drug discovery and time to market while cutting costs.

Japan's Takeda Pharmaceutical utilizes AI and machine learning to identify the best molecules for targeting proteins and to comprehend disease characteristics and their variance among different patient populations.

Takeda bought a psoriasis drug that startup Nimbus Therapeutics' algorithm selected in just six months; Nimbus' Jeb Keiper said conventional discovery of the candidate molecule would take two years.

Takeda's Anne Heatherington said, "Any technology that unlocks cutting-edge skills for our employees, reduces manual work, takes the friction out of the system, and frees up time for greater scientific insight and discovery is vital."

Investment company Morgan Stanley estimates using AI in early-stage drug development could yield an additional 50 novel medications generating more than $50 billion in sales over the net decade.

From Bloomberg

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Potentially Deadly AI?

Don't know how much of a real issue this is, but it is being reported by the Swiss Spiez lab, about their own drug discovery platform.  I would like to see a deeper follow up.  Please pass along and I will post. 

Widely Available AI Could Have Deadly Consequences   By Wired, May 18, 2022

In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. Evil project." The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands.

In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity—acting only on desired or targeted cells or neuroreceptors, for instance—and low toxicity to reduce ill effects.

Normally, MegaSyn would be programmed to generate the most specific and least toxic molecules. Instead, Ekins and Urbina programmed it to generate VX, an odorless and tasteless nerve agent and one of the most toxic and fast-acting human-made chemical warfare agents known today.... 

The researchers warned that while AI is becoming more powerful and increasingly accessible to anyone, there is nearly no regulation or oversight for this technology and only limited awareness among researchers of its potential malicious uses.  .... 

From Wired   View Full Article   

Widely Available AI Could Have Deadly Consequences

Misuses of Drug Discovery

ACM NEWS

Widely Available AI Could Have Deadly Consequences,     By Wired, May 18, 2022

In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. Evil project." The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands.

In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity—acting only on desired or targeted cells or neuroreceptors, for instance—and low toxicity to reduce ill effects.

Normally, MegaSyn would be programmed to generate the most specific and least toxic molecules. Instead, Ekins and Urbina programmed it to generate VX, an odorless and tasteless nerve agent and one of the most toxic and fast-acting human-made chemical warfare agents known today.

From Wired

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SMU ChemGen for Drug Discovery

An example of rigorous prep  work that must be done consistently well. 

SMU's ChemGen Completes Essential Drug Discovery Work in Days

Southern Methodist University,  April 14, 2021

Southern Methodist University (SMU) researchers have developed ChemGen, a set of computer-driven routines that emulate chemical reactions in a laboratory, significantly reducing the time and costs of drug discovery. ChemGen accelerates pharmacological optimization from months to days, using high-performance computers like SMU's ManeFrame II shared high-performance computing cluster. The tool computationally generates molecular variants of the original chemical key, mimicking reactions under various combinations of circumstances. SMU's John Wise said, "A research group or pharmaceutical company need only actually synthesize the molecules with the best chances of being improved, leaving the thousands of unimproved molecules in the computer and not on the lab bench."  ... "