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…
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,…
UBS: Generative AI is no silver bullet for drug discovery
Imagine a world where the process of developing life-saving drugs is as streamlined as a modern assembly line. In such a reality, generative AI in drug discovery might churn out promising compounds with similar efficiency and precision as a factory robot assembling a car. Moreover, such technology could chip away at the steep cost and…
PsychoGenics’ SmartCube prompts a reevaluation of CNS drug discovery
In an era of rapid AI progress, the quest to pioneer the first AI-developed drug candidates has led to an increasing number of these drug candidates entering clinical trials. One contender is ulotaront, an antipsychotic drug, that fared well in a phase 3 schizophrenia study published in NEJM in 2020. Sunovion discovered the drug in…
A current perspective on machine learning’s role in advancing clinical trials diversity
The year 2020 was a watershed moment for many reasons, but notably, it cast a light on the pervasive health and social inequities that have long marred the U.S. The COVID-19 pandemic hit diverse populations disproportionately hard, as Deloitte and others have noted. Additionally, the tragic deaths of George Floyd, Breonna Taylor and others provoked…
Codagenix taps synthetic biology and machine learning in vaccine development
In the quest to outsmart viral foes such as SARS-CoV-2, RSV and influenza, Codagenix, a clinical-stage biotech firm based in Farmingdale, New York, has engaged a unique arsenal: the intersection of synthetic biology and machine learning. Their weapon of choice is a blend of live-attenuated virus design and codon deoptimization technology. Their process involves introducing…
How EEG and machine learning are transforming epilepsy clinical trials
Epilepsy is a brain disorder that triggers recurring seizures. It is the fourth the most common neurological disorders in the world, according to the Epilepsy Foundation. The Centers for Disease Control and Prevention estimates that 65 million people worldwide have active epilepsy. In 2015, 1.2% of the total U.S. population — 3 million adults and…
Accelerating R&D with FAIR data
In 2016, the FAIR Guiding Principles for scientific data management and stewardship were published, laying out guideposts for scholarly data producers to make their data discoverable and usable in the future. The FAIR principles seek to ensure that data is Findable, Accessible, Interoperable, and Reusable. At the time of their publication, they articulated and centralized many points…
Digital transformation will give scientists their time back and speed the development pipeline
The pandemic exposed the innovation divide between the digitally transformed and those that lagged. Strict regulation made life sciences and bio/pharma organizations hesitant to modernize too quickly away from proven legacy methods and technologies, resulting in varying levels of digital transformation. But since the pandemic, organizations now recognize the necessity of digitalization and smart automation…
Cutting through the noise of machine learning for drug discovery
While the topic of AI in drug discovery has received considerable attention in recent years, mature deployments of techniques such as machine learning in the industry remain rare. “The chemistry domain is qualitatively different from any other problem that machine learning has exhibited real success in,” said Jason Rolfe, CTO of Variational AI (Vancouver, Canada). …
On ePRO and ensuring data integrity
As clinical trials have become more decentralized, there has been an increased focus on the need for more patient-centric drug development. This focus has led to a variety of eClinical applications. Electronic patient-reported outcomes (ePRO) and other electronic clinical outcome assessment (eCOA) approaches can transform trials to make them more pragmatic, patient-centric and efficient. Such…
MIT researchers tout new machine learning technique for assessing drug molecules
MIT researchers are touting a new machine-learning technique called DeepBAR that can quickly calculate the binding affinities between drug candidates and their targets. DeepBAR produces precise calculations in a fraction of the time compared to conventional techniques, according to the researchers. They think the software could potentially accelerate drug discovery and protein engineering. “Our method…