Behind the Scenes of AI-driven Drug Discovery
ALSO: Weekly Tech+Bio News; 10 Publicly Traded Biotechs Utilizing AI-based Research Platforms
Hi! I am Andrii Buvailo, and this is my weekly newsletter, ‘Where Tech Meets Bio,’ where I talk about technologies, breakthroughs, and great companies moving the biopharma industry forward.
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Now, let’s get to this week’s topics!
Weekly Tech+Bio News:
💰 Johnson & Johnson completes a $2 billion acquisition of Ambrx Biopharma, enhancing its pipeline with next-generation ADCs for cancer treatment, leveraging Ambrx’s synthetic biology platform for targeted oncology therapeutics.
📈 Pfizer shifts focus to biologics, specifically antibody-drug conjugates and bispecific antibodies, in its oncology business, motivated by the Inflation Reduction Act's favorable treatment of biologics over small molecules, planning to increase biologics' revenue share from 6% in 2023 to 65% by 2030.
💰 Alumis secures a $259M in Series C financing, the largest private biotech fundraise of 2024, to launch phase 3 trials of ESK-001 for plaque psoriasis and advance its pipeline of oral therapies targeting immune dysfunction.
🚀 Neuralink's first human patient fully recovers after brain chip implantation, achieving control over a computer mouse with thoughts. Despite the success, concerns arise from the FDA and medical professionals regarding the patient's long-term health and the safety of the technology.
🔬 In the world’s first, scientists at Penn State University achieved a breakthrough by 3D bioprinting layers of skin directly onto wounds in live rats, potentially revolutionizing treatments in dermatology and reconstructive surgery, with a focus on creating more natural-looking reconstructions without scarring or hair loss.
💰 Merck KGaA and C4 Therapeutics announce a $756m collaboration to develop targeted protein degraders against oncogenic proteins, utilizing C4T's TORPEDO platform for drug discovery and aiming to transform cancer treatment.
🔬 Elsevier partners with Iktos to enhance drug discovery, integrating Iktos's AI synthetic planning technologies into Elsevier's Reaxys database, the largest chemical database. This collaboration aims to accelerate the identification of pre-clinical drug candidates and streamline early-stage drug discovery processes.
🛑 Amylyx Pharmaceuticals' ALS drug, Relyvrio, may be withdrawn from the market after failing to show significant benefits in a large phase 3 clinical trial, lacking improvement in ALS functional scale, patient-reported quality of life, overall survival, and respiratory function.
🔬 Algorae Pharmaceuticals nears the launch of its AI-driven platform, AlgoraeOS, set for Q3 2024, to repurpose approved drugs for new medical treatments. Leveraging the Southern Hemisphere's most powerful supercomputer, it aims to streamline drug development and address unmet medical needs more efficiently.
🏛 The U.S. Senate's homeland security committee approves a bill aimed at restricting business with Chinese biotech firms like BGI and WuXi AppTec on national security grounds, focusing on preventing the access of Americans' health and genetic information by foreign adversaries.
🔬 Researchers at the University of Cologne develop a more stable form of artificial nucleic acids, known as threofuranosyl nucleic acid (TNA), featuring an additional base pair for enhanced information storage. This breakthrough paves the way for advances in therapeutic applications, targeted drug delivery, and diagnostics.
💰 Wobble Genomics secures £8.5M for its innovative RNA sequencing technology capable of detecting 'full-length' RNA, aiming to revolutionize fields like drug discovery, research, agriculture, and ecology by overcoming traditional RNA sequencing challenges.
🔬 ImmunoPrecise introduces an advanced AI model for drug discovery, combining stacked LLMs and BioStrand's HYFT Technology to improve the accuracy of biological data analysis and speed up the development of antibody drugs and precision medicine.
Looking Behind the Scenes of AI-driven Drug Discovery
A team of scientists from Hong Kong and New York-based Insilico Medicine and a number of academic collaborators have just announced a paper in which they reported on the generative AI-enabled design of a TNIK inhibitor that targets fibrosis in preclinical and clinical trials.
The results are published in Nature Biotechnology.
There are several reasons why this paper is important:
- the authors utilized AI to discover and prioritize a new anti-fibrotic target, TNIK
- in a separate paper, they performed the "hallmarks of aging assessment" of TNIK, it scored highly in several hallmarks of aging, which makes it relevant for aging research.
- they used Insilico's generative AI for chemistry, Chemistry42, to design a novel molecule with the desired properties, aiming to maximize safety and efficacy
- they performed a large number of in vitro and in vivo experiments, nominating three preclinical candidates for lung and kidney fibrosis
- they performed a clinical safety trial in humans
- (this one is nice!) they also made it easy to get questions about this paper answered by simply "chatting with the paper" via a chat bot.
- they also made a substantial data repository with the raw data from multiple experiments.
Here is a visual overview of the AI-driven process, but make sure to read the actual paper, it is a must read if you are in this space.
10 Publicly Traded Biotechs Utilizing AI-based Research Platforms
According to our intelligence report, The State of AI in the Biopharma Industry, more than 500 life sciences companies in the categories "startups" and "scaleups" are actively using machine learning and deep learning-based predictive and generative capabilities to augment their research strategies.
Some companies are incorporating AI tools to improve specific stages of drug discovery and development, for instance, to better model disease mechanisms or identify drug repurposing opportunities by analyzing omics data. Other companies are building entire end-to-end platforms for hypothesis generation, target discovery, de novo drug design, and even predicting clinical trial outcomes for newly designed candidates.
Below is a list of publicly traded companies with AI-powered platforms, and there is a bonus list of two companies at the end that are currently filing for IPOs.