AI in drug discovery Archives - Medical Design Sourcing

Iambic Therapeutics and NVIDIA partner to slash cancer drug development timelines

Using generative AI in drug discovery, Iambic Therapeutics (formerly Entos) has advanced its IAM1363 drug candidate from program launch to clinical studies in fewer than 24 months — a process that often takes several years. Iambic Therapeutics’ AI drug development milestone relied on an alliance with NVIDIA researchers and engineers and through the use of AI tools, including NeuralPLexer, a generative AI model designed to predict the three-dimensional structure and binding interactions of protein-ligand complexes.

The company has since developed the next generation of the model, dubbed NeuralPLexer2 that boasts higher accuracy and new features for biomolecular structure prediction and drug design.

IAM1363 is a selective, brain-penetrant inhibitor designed to treat HER2-driven cancers. It is designed to target metastatic tumors throughout the body, including the brain, while offering a wider therapeutic index and reduced toxicity over existing therapies. Read more

GLP-1s, ADCs, AI and the future of pharma

Pharma’s potential breakthroughs in AI, ADCs, and GLP-1 receptor agonists raise a critical question: can innovation outpace the relentless rise of chronic disease?

The IQVIA Institute for Human Data Science sheds light on this theme, among many others, in its 80-page Global Trends in R&D 2024 report.

Pillar 1: GLP-1 receptor agonists targeting metabolic disease

Speaking of next-gen metabolic therapies in particular, Murray Aitken, the executive director of the IQVIA Institute for Human Data Science, sees significant potential. Market projections for GLP-1 drugs are bullish, with some analysts projecting sales potentially hitting $100 billion by 2030. “It’s exciting because if the market for these drugs becomes as big as anticipated, it means they are truly being disruptive in a positive way to human health for hundreds of millions of people worldwide,” said Aitken

New metabolic therapies are sorely needed as the obesity epidem…

Big Pharma clicks soared, but new cell therapies made you buzz: What drove biopharma interest in 2023?

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The big Big Pharma names you couldn’t ignore

Despite biopharma’s 2023 layoffs and challenges, innovation won your clicks last year with over 130,000 of them on our Pharma 50 report alone. But while giants dominated, your clicks showed disruptive tech wasn’t far behind. The next-most popular article was a roundup of 100 trailblazing cell and gene therapy companies with more than 80,000 views. Other hits included companies putting AI in drug discovery and development, and the ever-popular biotech startup watch – proof that solutions, not just statistics, attract attention. Rounding out the top five was a roundup of biotech job cuts and openings.

2023 biopharma innovation in the spotlight on Linkedin

But over on LinkedIn, innovation was also a driver of interest. Topics on women’s health, such as Organon doubling down on women’s health, novel approaches to mental illness at…

Skynet with benefits: Can AI and humans become a drug discovery superorganism?

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Will the credit for future mega-blockbuster drugs, in some cases, go to a carefully-programmed AI discovery system connected to a “self-driving lab” that verified its potential?

Certainly, AI is hyped, but so are potential profits of potentially AI-optimized drugs. The exploding volumes of scientific data highlight a shift often overlooked: what does “inventor” even mean when human brilliance relies on AI and vast datasets no single person can comprehend? This future depends in part on connecting the dots between data experts, lab scientists with domain knowledge, and the machine learning systems capable of pattern recognition humans can’t even fathom. But the crux isn’t simply generating more data, and making it a shared, dynamic force fueling breakthrough discoveries — a force deeply integrated with computation and human expertise.

Breaking through the data bottleneck

Amgen, Deepcell tap NVIDIA’s AI to drive drug discovery and advance cell morphology research

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In 2023, generative AI (GenAI) entered the mainstream, capturing the attention of both the public and a growing number of biotechs. One of the most prominent Big Tech firms driving the trend is NVIDIA, which has forged alliances with biotechs ranging from Genentech, Recursion Pharmaceuticals and Evozyne, among others.

The momentum is continuing in early 2024, with NVIDIA announcing renewed pacts with Amgen and DeepCell. Amgen will use NVIDIA’s drug discovery generative AI platform BioNeMo Cloud service to accelerate molecule screening and optimization processes. Meanwhile, NVIDIA’s partnership with Deepcell hinges on advancing cell morphology studies with generative AI. “There is a very big moment happening in the world of pharmaceuticals and how drugs are being discovered,” said Kimberly Powell, vice president of Healthcare at NVIDIA, in a call with journali…

How Accenture and AWS are upgrading Merck’s IT and drug discovery R&D engine

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Historically, the pharma sector has exhibited a degree of caution in adopting emerging technologies such as cloud computing and AI, given the sector’s stringent regulatory requirements, data security concerns, and the complexities involved in integrating new systems into legacy processes.

The situation is beginning to shift considerably with the COVID-19 pandemic, in particular, acting as a catalyst, compelling many Big Pharma companies to accelerate their digital initiatives. Pfizer, Sanofi, Novartis, AstraZeneca, and other Big Pharma companies have unveiled ambitious initiatives tapping cloud computing and AI technologies, aiming to streamline various aspects of drug discovery and development.

Inside the Accenture-AWS-Merck pharma alliance

For instance, Merck in 2021 forged an alliance with Accenture and AWS to update its IT infrastructure and facilitate advanced drug discover…

Insilico Medicine taps AI to nominate small molecule inhibitor ISM9274 as a preclinical cancer therapy

Clinical-stage AI company Insilico Medicine has nominated a novel small molecule inhibitor known as ISM9274 as a preclinical candidate for cancer treatment.

The company used its PandaOmics AI platform to analyze genomic data from more than 90 tumor types and identified CDK12 as a promising target for multiple cancers including triple-negative breast cancer, lung cancer, and pancreatic cancer.

Next, it used its AI drug discovery engine Chemistry42 to design ISM9274 to selectively inhibit CDK12 and CDK13. Preclinical studies showed ISM9274 demonstrated potent antiproliferative activity across 60 cancer cell lines representing 13 tumor types. It also showed efficacy in animal models as both monotherapy and in combination with other therapies.

“Our target discovery philosophy is to find an optimal balance between commercial tractability, novelty and confidence,” said Alex Zhavoronkov, founder and CEO of Insilico Medicine.

The company’s AI platfo…

Eversana partners with AWS to accelerate generative AI in pharma

Life sciences commercial services company Eversana is one of the latest to throw its hat into the generative AI ring. Tapping a partnership with Amazon Web Services (AWS), Everasana is focusing on developing generative AI technologies in the pharmaceutical industry.

Also this month, the startup Synthetica Bio announced it would use generative AI to boost drug discovery innovation while Nvidia announced it would invest $50 million in the biotech Recursion to support its AI drug discovery efforts. Earlier this year, Nvidia debuted a cloud service for generative AI in drug discovery known as BioNemo.

Eversana’s approach to generative AI in pharma

Eversana aims to ‘pharmatise’ AI. The company’s chief digital officer Scott Snyder explains: “When we talk about pharmatising, it’s overlaying all of the unique needs, requirements, and goals of pharma, but layering it on to the innovation capability of generative AI.”…

What Google DeepMind’s introduction of AlphaDev sorting algorithm could mean for drug discovery

Researchers at Google’s DeepMind AI team have used AI to create advanced sorting algorithms, which although not specifically designed for drug discovery, could potentially benefit the field.

Published in Nature, DeepMind’s latest work demonstrates the use of deep reinforcement learning to create more efficient routines for sorting and hashing. These algorithms find use in various computational tasks, especially in computationally heavy processes such as drug discovery and simulations.

The researchers from DeepMind created an AI focused on code generation. To this end, they adapted the AlphaGo AI, a system known for defeating a human champion in the game of Go in 2016. The researchers created the AI system, known as AlphaDev, after staging a “game” approach, in which the AI treated a set of computer instructions like game moves. The AI then learned to “win” by sorting lists of three and five items as efficiently as possible. The resulting algor…

Insilico Medicine wins IND approval for AI-designed USP1 inhibitor for cancer trials in U.S. and China

Insilico Medicine has made a significant breakthrough with its AI-designed USP1 inhibitor, ISM3091. The US Food and Drug Administration (FDA) has accepted Insilico’s Investigational New Drug (IND) application for this promising drug, marking a significant milestone for AI-assisted drug discovery.

“The FDA’s acceptance of our IND for ISM3091 signifies that the FDA recognizes its potential value, and we can now open clinical trial sites across multiple centers and begin to study ISM3091 in human patients who may benefit from novel therapies,” said Dr. Sujata Rao, senior vice president, head of global clinical development at Insilico Medicine.

The company’s discovery and development of drug candidates, including ISM3091 and ISM001-055, which has also progressed to the clinic, showcases the efficiency and cost-effectiveness of AI in accelerating drug development. ISM001-055, a potentially first-in-class small molecule inhibitor for idiopathi…