generative AI Archives - Medical Design Sourcing

NVIDIA exec on how ‘NIMs’ can help biopharma navigate the challenges of deploying generative AI

[Image courtesy of Nvidia]

The buzz surrounding generative AI may be undeniable, but its real-world impact on heavily-regulated sectors like drug discovery continues to evolve. Consequently, most drug candidates, circa 90%, continue to fail. Kimberly Powell, vice president of Healthcare at NVIDIA, believes that a new microservices-based offering known as NIMs (NVIDIA Inference Microservices) could help pharma firms navigate this maze. “NIMs were built for the healthcare space, which has very private data,” Powell explained. Healthcare companies, including drug developers, “don’t always want to go to a cloud service. They want to do it in their own environment. We want to give them that capability,” she added.

To date, NVIDIA is offering about two dozen new healthcare microservices with more to follow.

NIMs intend to help scale AI deployment across infrastructures

NIMs, which …

Denmark teams up with Novo Nordisk Foundation, NVIDIA to launch visionary AI research center

A total of 15,128 NVIDIA H100 Tensor Core GPUs (pictured here) will be used in the Denmark AI Innovation Center. The hardware can support the development of advanced AI applications, from protein structure prediction to quantum computing research.

A collaboration between the Novo Nordisk Foundation, the Export and Investment Fund of Denmark (EIFO), and NVIDIA will establish a national AI Innovation Centre in Denmark focused on accelerating research and innovation in fields including healthcare, life science, and quantum computing. The initiative is led on the Danish side by the Novo Nordisk Foundation, which has committed roughly DKK 600 million (around $90 million) toward the initial costs of the center, and the Export and Investment Fund of Denmark (EIFO), which has contributed another DKK 100 million.

In a press briefing, Kimberly Powell, NVIDIA’s VP of healthcare, highlighted Denmark’s “…

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

AI basics from Medtronic Chief Technology and Innovation Officer Ken Washington

Medtronic SVP and Chief Technology and Innovation Officer Ken Washington [Photo courtesy of Medtronic]

Medtronic SVP and Chief Technology and Innovation Officer Ken Washington was recently briefing the 15 general managers who run each of the operating units at the world’s largest medical device manufacturer.

In the middle of the first chart in his presentation on artificial intelligence, one of the leaders stopped him.

As Washington tells it, they said, “I just don’t understand all these different buzzwords around AI. Can you tell me what are the different types of AI? How does it all work? And what’s the difference between generative AI and deep learning?”

Washington — who joined Medtronic in June 2023 after serving as VP and GM of consumer robotics at Amazon and CTO at Ford Motor Co. before that — pulled out an easel, grabbed a marker, and walked the group through t…

ConcertAI acquisition will boost CancerLinQ data capabilities with AI focus

The AI oncology startup ConcertAI recently acquired CancerLinQ, one of the largest oncology real-world data and quality of care technology service entities. Originally developed by the American Society of Clinical Oncology (ASCO) in 2013, CancerLinQ aims to use real-world data and technology to improve cancer care and advance evidence-based research.

CancerLinQ has developed one of the “deepest, broadest, most generalizable, least biased single standalone data sources that exists in oncology,” according to Jeff Elton, CEO of ConcertAI. This real-world data asset encompasses clinical data across more than 7 million patients, 100 care sites and more than 10 EMR systems.

Boosting CancerLinQ’s scope and capabilities

The acquisition will bring considerably more resources to CancerLinQ, which had a dedicated staff of between 50 and 60 people in comparison to ConcertAI, which has more than 1,100 employees. Under terms of the deal, ASCO will mainta…

Unlocking generative AI requires reshaping culture, operations, and talent dynamics

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In drug discovery and development, generative AI and natural-language processing (NLP) tools promise more than incremental productivity gains. For companies that can integrate such tools strategically into their workflows, the tools open the door to a fundamental rethinking of operational processes. For instance, generative AI tools can accelerate drafting of research articles, novel target identification, and the creation of SOPs for recipe and formulation. NLP, conversely, can mine unstructured scientific data and complex research papers. Because roughly 80% of healthcare data is unstructured, NLP promises to unlock previously inaccessible insights, transforming raw data into actionable knowledge.

But deploying such tools at scale requires a mix of strategic thinking, curiosity and new approaches to cultivating talent. As we enter 2024, life science organizations must rethink their approach to ad…

EDC fading in prominence as AI and cloud gain ground

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In a year or two, the clinical trial industry may move beyond electronic data capture (EDC), a technology that has been the cornerstone of clinical data management for decades, projects Raj Indupuri, CEO of eClinical Solutions. Given the potential of electronic medical records (EMR) to feed directly into data infrastructure, the need for EDC may be moot — or at least diminished.

More automated data-collection processes

Already, clinical trials are pulling considerable data from external sources, whether that be outside labs providing supplemental test results or real-world data generated through biomarkers, genomics sequencing, wearables, and other sources circumventing conventional data capture processes.

“There’s more and more data that we’re collecting directly from patients or other sources,” Indupuri said. “And the amount of data that we’re collecting through EDC — or …

AWS-NVIDIA gen-AI alliance epitomizes Big Tech’s growing interest in drug discovery

Highlighting the complexity of proteins, this 3D structure shows rhodopsin, a protein crucial for vision. [Adobe Stock]

The allure of healthcare has long captivated Big Tech giants. Over the past fifteen years or so, several prominent companies in the sector have ventured into the life sciences sector with ambitious projects, only to often find themselves retreating.

The dynamic appears to be changing, particularly in drug discovery, thanks in part to burgeoning data science maturity, the runaway success of generative AI (gen-AI), growing appetite for the cloud across healthcare and continued computational breakthroughs.

Tech companies are also realizing the diversity and uniqueness of healthcare data. “In less than a decade, [healthcare] will become the largest data generation industry,” said Kimberly Powell, vice president and general manager of healthcare at NVIDIA. “That’s one reason why large t…

50 of the best-funded biotechs of 2023

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As the year draws to a close, it is clear that molecular science and diagnostics is the hottest funding area in the biotech industry. In an analysis of 50 of the best-funded biotechs of 2023 focused on human health, molecular and science and diagnostics startups collectively attracting roughly $945 million, dwarfing the figures in other segments. The next popular two niches, gene therapies and oncology, had average funding levels of approximately $245 million and $170 million, respectively. While AI has received a significant amount of attention this year, biotechs specializing in that field garnered an average funding of only about $66 million. Outside of the life sciences, startups with a broader focus on AI raised a cumulative average of $202.47 million, based on an analysis of close to 1000 companies.

Caris Life Sciences has raised nearly $1.7B to date

In terms of best-funded companies overall,…

Nvidia-Genentech AI drug discovery alliance unites computing brawn with biological brains

NVIDIA BioNeMo AI molecular modeling software can uncover complex biochemical interactions through AI-driven molecular modeling techniques. [Image courtesy of NVIDIA]

Technically, graphics processing and AI hardware powerhouse Nvidia is also a drug discovery company. It may not discover drugs in-house, but it has developed BioNeMo, a comprehensive generative AI platform for drug discovery and Clara, a collection of healthcare frameworks, applications, and tools, including for biopharma. Nvidia partners include Amgen, AstraZeneca, GSK and Insilico Medicine.

Similarly, biotech pioneer and Roche subsidiary Genentech is also an AI company. It has experience in applying machine learning to an array of disease areas, and has extensive biological and molecular datasets and research capabilities. Its initiatives include alliance with firms such as Recursion Pharmaceuticals and Reverie Labs that focus on using AI for nov…

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…

Balancing on a tightrope, pharma’s generative AI journey straddles fear and FOMO

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Pharma and biotech companies have had a spectrum of responses to the surge in generative artificial intelligence (AI). A recent Washington Post article describes an unnamed biotech firm that banned employees from using OpenAI’s ChatGPT despite its capability to bolster productivity given concerns over potential data leaks. At the same time, the burgeoning AI landscape have created a fear of missing out, or FOMO, among businesses, including the pharma sector. “There’s this fear of missing out that I think is driving everybody to do something,” said Scott Snyder, chief digital officer at Eversana. On a tightrope of fear and FOMO, the pharmaceutical industry’s journey with generative AI continues with some companies taking more of a wait-and-see approach and others forging ahead with the technology to, for instance, discovery novel compounds.

Eversana is among those that ar…