Oxford Nanoimaging (ONI) recently launched the Aplo Scope super-resolution microscope that pushes imaging precision to 20 nm. The Aplo Scope integrates lasers, optics, chemistry, and software in a compact footprint, helping researchers capture and analyze molecular interactions at the nanoscale. With its user-friendly design and portability, ONI aims to simplify super-resolution microscopy and potentially reduce…
Complexity’s counterpoint: Understanding protocol optimization
In recent years, the clinical research landscape has been marked by a steady rise in protocol complexity with more endpoints and procedures across all trial phases and therapeutic areas. This trend, driven by the increasing sophistication of trial designs, is evident across trial phases and major therapeutic areas. Resulting in more endpoints and procedures on…
2024: The year AI drug discovery and protein structure prediction took center stage—2025 set to amplify growth
The global AI drug discovery market, valued around $1 to $1.7 billion in 2023, will be worth a multiple of that by the decade’s end. Analysts project the sector could be worth $9 billion or more. 2024 Nobel Prize in Chemistry Recipients: David Baker Demis Hassabis John Jumper Achievement: Computational protein design and structure prediction…
Drug development in 2025: 5 expert predictions cover synthetic data, hybrid trials and more
In 2024, we saw the expanded use of synthetic data and natural language processing transform drug discovery and development. In a batch of predictions published in December of 2023, one expert predicted that synthetic data was set to “take off” in drug research. In 2025, the pendulum could begin swinging back the other way, according…
PathAI launches AI tool for analyzing fibrosis in cancer tissue samples
The digital pathology firm PathAI has released PathExplore Fibrosis, an AI-based tool that analyzes fibrosis and collagen structures from H&E-stained whole-slide tissue images. The software quantifies fibrotic areas and collagen fibers from standard pathology slides, replacing specialized staining techniques and microscopy equipment. The tool processes large datasets of tissue images, designed to work with existing…
Scientists develop new machine-learning model to predict immunogenic neoantigens
Researchers at Cleveland Clinic’s Global Center for Immunotherapy, in collaboration with Bristol Myers Squibb, have published a comprehensive study on how the immune system remodels the tumor microenvironment in response to immune checkpoint therapy. This research represents the most detailed analysis of this process to date. Under the leadership of Timothy Chan, MD, PhD, Chair…
The future of RWD and RWE in healthcare decision-making: Applications of novel real-world data collection methods for healthcare decision-making
Real-world evidence and real-world data The use of real-world evidence (RWE) to support regulatory and reimbursement decision-making received increasing attention over the past decades. The US FDA provides a definition of RWE as “the clinical evidence about the usage and potential benefits and risks of a medical product”1. RWE can be used across the entire…
Intrepid Labs’ self-driving lab reimagines drug formulation
The pharma industry has long relied on tried-and-true drug formulation approaches sometimes rooted in trial and error, but this reliance on the familiar has created a bottleneck in the development of new and better medicines. University of Toronto Professor Christine Allen, Ph.D., co-founder and CEO of Toronto-based Intrepid Labs, points out that the traditional drug…
Inside BioXcel Therapeutics’ AI-driven drug reinnovation strategy
Friso Postma, vice president of AI for drug discovery at BioXcel Therapeutics, prefers the term “augmented intelligence” to “artificial intelligence.” His company uses AI tools to support human experts in drug repurposing efforts. Postma, who holds a PhD in signal transduction from the Netherlands Cancer Institute, transitioned to AI from wearable digital health devices. “I…
Demystifying deep learning: An accessible introduction to neural networks in health research and epidemiology
As machine learning and deep learning technologies advance thanks to advances in computation, algorithms and data availability, the possibilities of the technology continue to expand in medicine. While these AI-driven approaches have real potential, such systems demand large volumes of representative data, careful privacy and security scrutiny and thoughtful long-term strategic planning. In this Q&A, Kathryn…
Revised time series model forecasts Lilly’s Mounjaro sales to triple in 2024
Eli Lilly is experiencing meteoric growth in 2024, driven by surging demand for its metabolic therapies. In the first quarter, Lilly’s revenue jumped 26% year-over-year to $8.77 billion, propelled by strong sales of diabetes drug Mounjaro and weight loss treatment Zepbound Lilly also significantly raised its full-year 2024 outlook. The company now expects revenue in…
When will drug development have its ChatGPT moment? Inside ambitious AI initiatives at Sanofi and Medable
In episode 4 of Ai Meets Life Sci, Kayleen Brown, managing editor at DeviceTalks and Brian Buntz, pharma and biotech editor, chat with Helen Merianos, Ph.D., head of R+D portfolio strategy at Sanofi and Michelle Longmire, MD, CEO of Medable. The focus? The two-fold application of AI in their respective companies’ technologies, both for scientific advancement…
Inside Amgen’s ATOMIC strategy to use ML to accelerate clinical trials
Amgen has developed a machine learning platform to slash clinical trial times through smarter site selection. Known as ATOMIC, short for Analytical Trial Optimization Module, the system crunches disparate datasets to predict optimal trial locations, expedite enrollment and trial processes. Early results indicate more than a two times increase in enrollment speed at ATOMIC sites.…
EDC fading in prominence as AI and cloud gain ground
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…
At AWS re:Invent, Pfizer exec frames digital as a core business strategy
In the midst of a global pandemic, Pfizer, under the leadership of its chief digital and technology officer Lidia Fonseca, achieved what was once thought impossible. The company, with the partnership of BioNTech, developed a COVID-19 vaccine in only 269 days, a process that traditionally would have taken 8 to 10 years. While prior research…
Genmab’s data-driven strategies speed up drug commercialization
Genmab’s senior vice president, global head of data science and AI, Hisham Hamadeh, describes the company’s journey to becoming “a data-driven decision-making company.” In one sense, there is little choice but to do so. “We’re swimming in data like never before. We’ve seen the volumes of data, the ability to compute on that data, and…
50 of the best-funded biotechs of 2023
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…
How Lantern Pharma and Code Ocean partnered on oncology drug development
A vision for data-driven drug development in oncology When Peter Carr, principal software architect of Lantern Pharma, stepped into his full-time role in September 2020, the company was on the cusp of a transformation. While AI had been a focus for a number of years, a fresh infusion of cash provided a possibility of expanding…
The evolution of drug discovery: Opportunities and obstacles with ML and AI development
The potential for artificial intelligence (AI) and machine learning (ML) to reshape drug discovery and development is immense. From expediting learning and driving discoveries to managing large-scale data sets and generating fresh insights, the true scale of AI’s influence on the industry is only starting to be understood. But with great potential comes great responsibility.…
eClinical Solutions Q&A: The quest to transform raw data into drug discovery gold
Top pharmaceutical companies sponsor over a hundred clinical trials annually, generating vast amounts of data. Harnessing this deluge is a monumental task. eClinical Solutions, led by CEO Raj Indupuri, tackles this through advanced applications of data analytics and machine learning with an emphasis on AI in clinical trials optimization. Specifically, eClinical Solutions taps AI/ML for…
Investments in AI and ML help PV teams transform safety case processing
Thanks to automation in pharmacovigilance, the next generation of safety is here — and with it, there is an immense opportunity for firms that can change how they work and maximize the opportunity automation creates. Leading safety teams are seeing up to 80% efficiency gains on key workflows by investing in touchless case processing, automating…
Quantum computing promises new frontier in drug discovery and bioinformatics
Quantum computing — described by pop astrophysicist Neil deGrasse Tyson as “computing with atoms” — is an emerging technology with a potential for immense computational speed and power. For some problems, quantum computers can be exponentially faster than classical computers, while for others the speedup may be more measured. The promise for drug discovery could…
Why AI alone won’t resolve drug discovery challenges
Big Pharma and researchers are sharpening their focus on AI to speed drug discovery. But the path to fully AI-driven drug discovery faces substantial hurdles, according to Adityo Prakash, CEO of Verseon. “When it comes to drug discovery, AI has a data problem with which the pharmaceutical industry has not yet come to terms,” he…
The Allen Institute is employing AWS Cloud and machine learning to decode brain mysteries
High-resolution mapping of the human brain involves managing and interpreting a colossal amount of data. Shoaib Mufti, the head of data and technology at the Allen Institute for Brain Science, described the organization’s approach to these challenges in a recent interview. The project uses artificial intelligence to analyze millions of data points from brain imaging…
Contrastive learning-based model ConPLEx elevates drug-protein interaction predictions
Drug discovery, traditionally a labor-intensive process, often involves extensive computational work during experimental screening. Advances in AI, however, promise to streamline this process. To that end, a team from MIT and Tufts has introduced ConPLex, a computational model that uses large language model techniques, similar to those behind ChatGPT. The model analyzes vast amounts of…