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Artificial intelligence makes a splash in small-molecule drug discovery


In the past five years, interest in applying artificial intelligence (AI) approaches in drug research and development (R&D) has surged. Driven by the expectation of accelerated timelines, reduced costs and the potential to reveal hidden insights from vast datasets, more than 150 companies with a focus on AI have raised funding in this period, based on an analysis of the field by Back Bay Life Science Advisors (Figure 1a). And the number of financings and average amount raised soared in 2021. At the forefront of this field are companies harnessing AI approaches such as machine learning (ML) in small-molecule drug discovery, which account for the majority of financings backed by venture capital (VC) in recent years (Figure 1b), as well as some initial public offerings (IPOs) for pioneers in the area (Table 1). Such companies have also attracted large pharma companies to establish multiple high-value partnerships (Table 2), and the first AI-based small-molecule drug candidates are now in clinical trials (Nat.

Elon Musk's Neuralink rival Synchron begins human trials of brain implant

Daily Mail - Science & tech

Elon Musk's Neuralink rival Synchron has begun human trials of its brain implant that lets the wearer control a computer using thought alone. The firm's Stentrode brain implant, about the size of a paperclip, will be implanted in six patients in New York and Pittsburgh who have severe paralysis. Stentrode will let patients control digital devices just by thinking and give them back the ability to perform daily tasks, including texting, emailing and shopping online. Although the implant has already been implanted and tested in Australian patients, the new clinical trial marks the first time it will be tested in the US. If successful, the Stentrode brain implant could be sold as a commercial product aimed at paralysis patients to regain their independence and quality of life.

How A.I. Is Finding New Cures in Old Drugs


In the elegant quiet of the café at the Church of Sweden, a narrow Gothic-style building in Midtown Manhattan, Daniel Cohen is taking a break from explaining genetics. He moves toward the creaky piano positioned near the front door, sits down, and plays a flowing, flawless rendition of "Over the Rainbow." If human biology is the scientific equivalent of a complicated score, Cohen has learned how to navigate it like a virtuoso. Cohen was the driving force behind Généthon, the French laboratory that in December 1993 produced the first-ever "map" of the human genome. He essentially introduced Big Data and automation to the study of genomics, as he and his team demonstrated for the first time that it was possible to use super-fast computing to speed up the processing of DNA samples.

From Israeli lab: First AI-designed antibody enters clinical trials


Aulos Biosciences is now recruiting cancer patients in Australian medical centers for a trial of the world's first antibody drug designed by a computer. The computationally designed antibody, known as AU-007, was planned by the artificial intelligence platform of Israeli biotech company Biolojic Design from Rehovot, in a way that would target a protein in the human body known as interleukin-2 (IL-2). The goal is for the IL-2 pathway to activate the body's immune system and attack the tumors. The clinical trial will be conducted on patients with final stage solid tumors and will last about a year – but the company hopes to present interim results during 2022. The trial has raised great hopes because if it is successful, it will pave the way for the development of a new type of drug using computational biology and "big data."

AI-based system improves bladder cancer treatment response assessment


In a small but multi-institutional study, an artificial intelligence-based system improved providers' assessments of whether patients with bladder cancer had complete response to chemotherapy before a radical cystectomy (bladder removal surgery). Yet the researchers caution that AI isn't a replacement for human expertise and that their tool shouldn't be used as such. "If you use the tool smartly, it can help you," said Lubomir Hadjiyski, Ph.D., a professor of radiology at the University of Michigan Medical School and the senior author of the study. When patients develop bladder cancer, surgeons often remove the entire bladder in an effort to keep the cancer from returning or spreading to other organs or areas. More evidence is building, though, that surgery may not be necessary if a patient has zero evidence of disease after chemotherapy.

Artificial intelligence hiring levels in the clinical trial operations industry rose in March 2022


The proportion of clinical trial operations companies hiring for artificial intelligence related positions rose in March 2022 compared with the equivalent month last year, with 42.9% of the companies included in our analysis recruiting for at least one such position. This latest figure was higher than the 40.9% of companies who were hiring for artificial intelligence related jobs a year ago and an increase compared to the figure of 41.3% in February 2022. When it came to the rate of all job openings that were linked to artificial intelligence, related job postings rose in March 2022, with 8.1% of newly posted job advertisements being linked to the topic. This latest figure was the highest monthly figure recorded in the past year and is an increase compared to the 3.2% of newly advertised jobs that were linked to artificial intelligence in the equivalent month a year ago. Artificial intelligence is one of the topics that GlobalData, from whom our data for this article is taken, have identified as being a key disruptive force facing companies in the coming years.

Riding on wave of clinical trial reforms, machine learning startup bags $50M to create 'digital twins'


As drug developers and regulators alike increasingly warm to creative ideas for running clinical trials, a machine learning platform created by three physicists is drawing in $50 million from tech VCs. Unlearn bills itself as the only company that can generate "digital twins" of patients for use in clinical trials, so that biopharma companies can test their drugs with fewer real patients than they would need to in traditional trials, but get similarly, if not even more, reliable results. "Our product is not an AI model -- it's a clinical trial," CEO Charles Fisher wrote in an email interview with TechCrunch. He divulged that Germany's Merck KGaA is among three drugmakers using Unlearn's platform in the design of its clinical trials -- although it's not directly for the digital twin service but prognostic information from the digital twins. Whereas there have been efforts and guidance from the FDA to use real-world data to support regulatory decisions, none have quite gone as far as incorporating constructed patient profiles. Unlearn believes its technology can accomplish that through a combination of machine learning and new statistical methods.

Using AI to Accelerate Clinical Trials


Artificial intelligence (AI)-enabled data collection and management can be a game changer for life sciences companies in the drug development process. Once the stuff of science fiction, AI has made the leap to practical reality. Yet, to date, most life sciences companies have only scratched the surface of AI's potential. One area that holds particular promise: digital data flow automation for clinical trials. With the power of AI, companies can rapidly digitize clinical-trial processes so they can complete studies faster.

Artificial Intelligence at the Heart of China's New Drug Discovery


It's not much of a surprise to find Artificial Intelligence (AI) playing a central role in the pharmaceutical industry. Chinese firms are relying on AI to put more drugs on the market, and by extrapolation extend better services. The country is gathering momentum for an artificial intelligence-backed drug discovery boom. All thanks to the nation's emphasis on innovation-driven development, these companies are going through a continuously improving innovation ecosystem, according to industry experts and business leaders. "It is not a question of whether China will become a powerhouse in AI-driven drug development even though it started relatively late (in the field). The only question is when that will happen." said an Industry Leader in AI-based Drug Discovery.

Giving Zebrafish Psychotropic Drugs to Train AI Algorithms - Neuroscience News


Summary: Researchers trained an AI to determine which psychotropic agent a zebrafish had been exposed to based on the animal's behaviors and locomotion patterns. Neuroscientists from St. Petersburg University, led by Professor Allan V. Kalueff, in collaboration with an international team of IT specialists, have become the first in the world to apply the artificial intelligence (AI) algorithms to phenotype zebrafish psychoactive drug responses. They managed to train AI to determine--by fish response--which psychotropic agents were used in the experiment. The research findings are published in the journal Progress in Neuro-Psychopharmacology and Biological Psychiatry. The zebrafish (Danio rerio) is a freshwater bony fish that is presently the second-most (after mice) used model organism in biomedical research.