Pharmaceutical manufacturers are tasked with monitoring and reporting safety events (adverse events, product quality complaints, special situations, etc.) to protect patient safety. This process – detecting, documenting, evaluating, reporting, and following up – is essential to meeting regulatory standards and ensuring optimal patient outcomes. However, many of these critical events are not being captured today. …
Merck taps Atropos Health to accelerate real-world evidence generation
Building on existing integrations with cloud leaders AWS and Google Cloud and collaborations with Arcadia and TD2, Atropos Health is now partnering with Merck. This new collaboration will tap Atropos Health’s GENEVA OS (Generative Evidence Acceleration Operating System) and related tools with the aim of speeding the generation of real-world evidence. Under the agreement, Merck’s…
Optimizing Data Pipelines in Life Sciences with AI-Driven Integration and FHIR
Sponsored by Infor. Data management in life sciences is inherently complex. Data is fragmented across multiple systems — such as clinical trials, lab systems, regulatory databases, and electronic health records (EHRs) — in inconsistent formats. For example, patient information in the EHR is typically transferred using legacy technology. Additional data streams from wearable devices,…
Accelerating life sciences with AI
This case study is sponsored by Infor. Artificial intelligence can revolutionize clinical interoperability by building bridges across data silos. Machine learning’s vast analytical capabilities enable the comprehensive analysis of large volumes of historical data from multiple sources, providing a more holistic view of patients’ overall health. Its ability to uncover patterns and anticipate future needs…
The roadmap to effective AI-driven drug development
Generative artificial intelligence (GAI) has captivated the world, and for good reason. Platforms like ChatGPT have demonstrated capabilities that gave the general public a deeper understanding of AI’s capabilities. AI, too, is showing potential in drug discovery. From designing novel drug molecules to predicting protein structures, AI is offering a new path forward, potentially accelerating…
How the duo of cryo-EM and AI is unveiling protein dynamics in unprecedented resolution
Over the past few decades, structural biology has undergone a quiet renaissance, thanks in large part to technological advances in cryogenic electron microscopy (cryo-EM) and computational techniques. Cryo-EM has emerged as a powerful tool for determining the high-resolution structures of proteins and protein complexes, complementing traditional methods like X-ray crystallography and nuclear magnetic resonance (NMR)…
From gatekeeper to strategist: The evolution of the CISO role in drug development
There’s an old joke about chief information security officers (CISOs) being gatekeepers of new technologies and initiatives – the infamous “Department of No.” Imagine a bouncer who, strangely, doesn’t let anyone in, saying the club is already too full, even when it’s clearly empty. But that image is outdated — especially in risk-focused industries like…
Moving beyond buzzwords: When will a rising AI tide lift all Big Pharma boats?
For all of the talk about AI in drug discovery and development, few Big Pharmas are putting up big bucks in AI spending. A CRB survey from late 2023 painted a conservative picture: about half of drug developers planned on allocating between $1 and $10 million for data and AI projects over the next two…
Biotech bounces back at JPM 2024 on optimism, breakthroughs and calculated bets, but uncertainties persist
At the dawn of 2024, there’s a sense of renewed optimism in the biotech sector despite recent sector-specific challenges. This week, the JP Morgan Health Care Conference witnessed strong deal-making activity. For instance, Merck agreed to acquire cancer drug developer Harpoon Therapeutics for roughly $680 million, highlighting continued interest in oncology cancer therapies. Meanwhile, Novartis…
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…
A year in review: AI’s evolving role in drug discovery and development in 2023
In the realm of drug discovery, AI is making waves, and 2023 could potentially be a pivotal year for this technology. As the technology enters the popular consciousness, pharma employees are wondering “why they can’t have similar AI-driven tools for their professional tasks,” said Diane Wuest, head of digital R&D at Sanofi, in a recent…
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…
iBio’s chief reveals strategy behind AI-driven bispecific antibody discovery plans
Biotech firm iBio (NYSEA:IBIO) has incorporated EngageTx, a machine learning-driven technology, into its development roadmap. This T-cell engaging antibody panel assists in generating bispecific antibodies targeting cancer cells. In particular, the firm is developing a novel Trophoblast Cell Surface Antigen 2 (TROP-2) bispecific molecule to target TROP-2-positive cancers. In addition to their focus on oncology,…
The Brain Knowledge Platform aims to illumine the brain’s cellular universe
Despite substantial progress in brain research, our understanding of the human brain remains limited. “We really don’t understand the fine circuitry of the brain — even in a relatively simple organism like a mouse,” confessed Ed Lein, a senior investigator at the Allen Institute for Brain Science. But AI in neuroscience research promises to change…
Decoding Bayer’s digital health leap and its implications on drug discovery and personalized medicine
The German multinational pharma and biotech colossus Bayer is taking further steps to ramp up its focus on digital health by launching a new business unit. In 2022, Bayer invested $9.5 million in Woebot Health, an AI-powered behavioral health platform company. In 2020, it launched a venture known as G4A Digital Health Partnership Program to…
Science unbound: AI and open data accelerate the pace of discovery
Scientists have long been perceived and portrayed in film as old people in white lab coats perched at a bench full of bubbling fluorescent liquids. The present-day reality of scientific research is quite different from old stereotypes, with AI-driven scientific breakthroughs emerging as a major driving force behind new discoveries. Scientists are increasingly data jockeys…
Behind the scenes: Dr. Andy Beck, PathAI CEO, talks PathExplore
In a recent conversation with Dr. Andy Beck, co-founder and CEO of PathAI, we had the opportunity to discuss PathExplore, an AI-driven platform that aims to transform the way tumor microenvironment (TME) analysis is conducted. Traditional methods such as manual pathology, multiplex immunofluorescence and single-cell omics often face limitations, including high costs or tissue consumption.…
How AI-based technologies improve clinical trial design, site selection and competitive intelligence
Clinical trials form the cornerstone of evidence-based medicine and are essential to establishing the safety and efficacy of new drugs. However, only some of the information in clinical trial reports is well-structured and searchable via keywords; much of the information is buried in unstructured text. In the past, uncovering actionable insights from this unstructured text…
Drug discovery isn’t rocket science. It’s harder.
Early in my career, my manager used the phrase in the above headline to highlight the difficulty inherent in drug discovery. Over the ensuing years, I have seen that statement repeatedly confirmed by the brutal attrition in the discovery and development of new drugs. There are so many variables that can kill a drug discovery…
Fueling breakthroughs in pharma AI: 3 critical factors
Big data and AI offer massive opportunities to the pharmaceutical industry — in theory. In reality, many companies are struggling to realize the potential of these tools. Some organizations have been hesitant or resistant to leveraging the technologies. Others may have attempted to embrace them early on but are now beginning their second or third…
Ethics matter when deploying RWD and RWE
Because adoption of real-world data (RWD) and real-world evidence (RWE) remains at an early stage, individual biopharma executives are likely to take a central role in ensuring that such data — and the related use of AI — are handled ethically. It becomes imperative that drug developers using RWD ensure transparency, apply consistent rules, peer…
Why Big Pharma is partnering with startups as it becomes more data-driven
Big Pharma’s ability to innovate has grown in recent years, and the industry’s increasing reliance on data could help it sustain momentum in the future. While McKinsey notes that the industry has been relatively slow in adopting technologies such as AI and automation, the industry is growing more tech-savvy. “The acceptance of data is picking up across…
The role of natural language processing in advancing disease research
In any area of disease research, a deep understanding of recent and future trends surrounding a particular condition is crucial to the drug discovery process. But with the volume of scientific literature increasing all the time, it is difficult to manually sift through all the existing information and correlate data in such a way to…
Querying the queries: An AI approach to manage clinical data quality
High-quality clinical trial data serves as the foundation for analysis, submission, approval, labeling and marketing of a compound under study. Widely used throughout the industry, data cleaning ensures that the process deployed to collect data is consistent and accurate. Challenges in collection include data errors during manual data entry, i.e., spelling and transcription mishaps, range,…