Arinze N.N. Eze CAMC, MRAeS, MA, MSc’s Post

From AlphaFold to the Next Trillion Dollar Business?  AlphaFold remains one of my favorite AI breakthroughs. Its history, dating back to the days of gaming with AlphaGo, and its impact on drug discovery, make it one of the most fascinating developments in AI and one of the most impactful on human life. I cover it in the blog post below (see first comment)

Google’s Isomorphic Lab’s Drug Discovery platform is an AI-based system that designs compounds with different constraints, almost like a generative model. The lab aims to reduce the discovery stage from an average of five years to two by identifying potential drugs before clinical trials. Isomorphic Lab has partnered with Eli Lilly and Novartis for its first two pharmaceutical partnerships, which are worth up to $3bn combined. Lilly will pay $45mn upfront, with another $1.7bn to be paid when the project reaches performance milestones, such as drugs reaching trials or approval. Novartis will pay $37.5mn upfront with an additional $1.2bn in performance-based incentives. Few previous attempts with AI-discovered drugs have failed in clinical trials as human biology is hard to predict. Some start-ups specializing in AI for drug discovery have had to abandon drugs after studies showed they were not as effective as hoped. #AI #drugdiscovery #IsomorphicLab #EliLilly #Novartis #pharmaceuticals #clinicaltrials #innovation #healthcare #technology #generatieveai

DeepMind Spin-off Aims To Halve Drug Discovery Times Following Big Pharma Deals: The head of Google DeepMind believes its drug discovery spinout will halve the time taken to find new medicines, attracting the attention of the world's biggest pharmaceutical companies which are looking to artificial intelligence to revolutionise the lengthy process. From a report: Speaking to the Financial Times, Demis Hassabis, who co-founded Google's AI unit and also leads the drugs offshoot Isomorphic Labs, said the goal was to reduce the discovery stage -- when potential drugs are identified before clinical trials -- from the average of five years to two. "I think that would be success for us and be very meaningful," he said. Hassabis stated the goal days after announcing Isomorphic Lab's first two pharmaceutical partnerships with Eli Lilly and Novartis, which came to a combined value of up to $3bn, in deals set to transform the finances of the unprofitable group. Isomorphic Labs uses an AI platform to predict biochemical structures, which aids the creation of new drugs by recommending which potential compounds will have the desired impact in the body. Including clinical trials, it often takes up to a decade to discover and develop a new drug, costing on average about $2.7bn, according to research by the Tufts Center for the Study of Drug Development. Large drugmakers, under pressure to fill their pipelines with new potential medicines while existing ones face patent cliffs, when they will face far cheaper generic competition, are eager for new ways to shorten the process. As healthcare systems around the world put pressure on drug prices, pharma companies are also looking for ways to cut costs in research and development. Hassabis said that many drugmakers had also been eager to partner with Isomorphic but the company wanted to focus on collaborations that could improve its technology. Read more of this story at Slashdot.

For the past 2–3 years, biotechnology investors and large pharmaceutical companies alike have been keen to buy late-stage assets—drug candidates that have already been tested in humans, which minimizes the amount of risk a buyer would take on. If decision-makers at the 2024 BIO International Convention in San Diego are to be believed, that’s about to change. Business development heads at pharmaceutical giants including Bayer, Johnson & Johnson, and Novo Nordisk are publicly discussing their willingness to acquire, or at least partner on, preclinical and Phase 1 drug candidates. “Oftentimes, you will actually have more value-creating opportunities with early-to-midstage deals,” Nauman Shah, global head of business development for Johnson & Johnson’s Janssen division, said on stage on Monday. “For us, it’s not necessarily about struggling with finding the capital to fund a large deal.” Indeed, Big Pharma is collectively sitting on a veritable ton of cash: more than $1 trillion at the end of March, according to EY’s latest Beyond Borders report. Arda Ural, EY’s Americas industry market leader for health sciences and wellness, estimated during a webinar at the end of May that pharma firms had $1.4 trillion sitting in balance sheets, “ready to be deployed.” That number goes up several fold if securities are taken into account, Ural said. Last year closed out with $179 billion in biopharma M&A, according to the EY report, mostly driven by a handful of multibillion-dollar megadeals. By and large, the acquired companies—Seagen, Karuna Therapeutics, and Prometheus Biosciences, among others—had drug candidates in mid-to-late-stage clinical studies. Dispatch No. 1 from BIO: https://lnkd.in/gjny-EHn

DeepMind Spin-off Aims To Halve Drug Discovery Times Following Big Pharma Deals: The head of Google DeepMind believes its drug discovery spinout will halve the time taken to find new medicines, attracting the attention of the world's biggest pharmaceutical companies which are looking to artificial intelligence to revolutionise the lengthy process. From a report: Speaking to the Financial Times, Demis Hassabis, who co-founded Google's AI unit and also leads the drugs offshoot Isomorphic Labs, said the goal was to reduce the discovery stage -- when potential drugs are identified before clinical trials -- from the average of five years to two. "I think that would be success for us and be very meaningful," he said. Hassabis stated the goal days after announcing Isomorphic Lab's first two pharmaceutical partnerships with Eli Lilly and Novartis, which came to a combined value of up to $3bn, in deals set to transform the finances of the unprofitable group. Isomorphic Labs uses an AI platform to predict biochemical structures, which aids the creation of new drugs by recommending which potential compounds will have the desired impact in the body. Including clinical trials, it often takes up to a decade to discover and develop a new drug, costing on average about $2.7bn, according to research by the Tufts Center for the Study of Drug Development. Large drugmakers, under pressure to fill their pipelines with new potential medicines while existing ones face patent cliffs, when they will face far cheaper generic competition, are eager for new ways to shorten the process. As healthcare systems around the world put pressure on drug prices, pharma companies are also looking for ways to cut costs in research and development. Hassabis said that many drugmakers had also been eager to partner with Isomorphic but the company wanted to focus on collaborations that could improve its technology. Read more of this story at Slashdot.

DeepMind Spin-off Aims To Halve Drug Discovery Times Following Big Pharma Deals: The head of Google DeepMind believes its drug discovery spinout will halve the time taken to find new medicines, attracting the attention of the world's biggest pharmaceutical companies which are looking to artificial intelligence to revolutionise the lengthy process. From a report: Speaking to the Financial Times, Demis Hassabis, who co-founded Google's AI unit and also leads the drugs offshoot Isomorphic Labs, said the goal was to reduce the discovery stage -- when potential drugs are identified before clinical trials -- from the average of five years to two. "I think that would be success for us and be very meaningful," he said. Hassabis stated the goal days after announcing Isomorphic Lab's first two pharmaceutical partnerships with Eli Lilly and Novartis, which came to a combined value of up to $3bn, in deals set to transform the finances of the unprofitable group. Isomorphic Labs uses an AI platform to predict biochemical structures, which aids the creation of new drugs by recommending which potential compounds will have the desired impact in the body. Including clinical trials, it often takes up to a decade to discover and develop a new drug, costing on average about $2.7bn, according to research by the Tufts Center for the Study of Drug Development. Large drugmakers, under pressure to fill their pipelines with new potential medicines while existing ones face patent cliffs, when they will face far cheaper generic competition, are eager for new ways to shorten the process. As healthcare systems around the world put pressure on drug prices, pharma companies are also looking for ways to cut costs in research and development. Hassabis said that many drugmakers had also been eager to partner with Isomorphic but the company wanted to focus on collaborations that could improve its technology. Read more of this story at Slashdot.

The future of AI drug discovery and development is here. Oncocross and JW Pharmaceutical have joined forces to utilize the power of AI in identifying and verifying new indications for groundbreaking drugs. Oncocross's proprietary AI platform, RAPTOR AITM, will be employed to screen for optimal or additional indications for drug candidates. This means increased accuracy, reduced costs, and shorter development times compared to traditional methods. While working together in the past, JW Pharmaceutical saw positive results in expanding an orphan disease indication for their new drug candidate. Now, they are once again partnering with Oncocross to accelerate the screening process and increase the chances of success in clinical studies for their 'first-in-class' drug pipelines. This collaboration highlights the value and potential of RAPTOR AITM in the market. Oncocross is committed to setting an example for successful partnerships between large pharmaceutical companies and biotech in the AI drug development field. How do you see AI shaping the future of drug discovery and development? --- Hi, 👋🏼 my name is Doug, I love AI, and I post content to keep you up to date with the latest AI news. Follow and ♻️ repost to share the information! #ai #drugdiscovery #pharmaceuticals

At Endogena Therapeutics, leveraging AI has been integral to our approach since the early beginnings. In fact, it led us to discover our drug candidate EA-2353 for retinitis pigmentosa – a rare, degenerative eye disease. We are excited to see the pharmaceutical industry, including leading Swiss companies like Roche and Novartis, also harnessing AI to revolutionize drug discovery. This trend validates our early adoption and reinforces our commitment to pioneering regenerative medicine. Co-founders Matthias Steger PhD, MBA and Gisbert SCHNEIDER (ETH Zürich) are particularly inspired by how AI can enhance efficiency and innovation in bringing new treatments to patients. Discover more about AI's impact on pharma in this article from SWI swissinfo.ch: https://lnkd.in/gxr6S8SF. #AI #DrugDiscovery #Pharmaceuticals #Biotech #Innovation #RegenerativeMedicine #RetinitisPigmentosa #ArtificialIntelligence #HealthcareInnovation #MedicalResearch #FutureOfMedicine #SwissPharma #BigPharma #AIinHealthcare

Artificial Intelligence (AI) in Pharmaceutical Research: Traditional drug development typically spans three to four years, but the integration of AI shortens this process to just 40 to 50 days. In our detailed blog post, we delve into the transformative impact of AI on drug development, highlighting the experiences of Dr Emily Hayes, a dedicated researcher at a leading pharmaceutical company, and Atomwise, an AI-driven drug discovery company. https://lnkd.in/ghYDB7PS

Artificial Intelligence (AI) in Pharmaceutical Research: Traditional drug development typically spans three to four years, but the integration of AI shortens this process to just 40 to 50 days. In our detailed blog post, we delve into the transformative impact of AI on drug development, highlighting the experiences of Dr Emily Hayes, a dedicated researcher at a leading pharmaceutical company, and Atomwise, an AI-driven drug discovery company. https://lnkd.in/ghYDB7PS