A checklist for unlocking the promise of AI in clinical trials

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AI algorithms offer a myriad of advantages for clinical trials. AI techniques can, for instance, support patient enrollment and site selection, improve data quality and enhance patient outcomes. AI algorithms — combined with an effective digital infrastructure — can also help aggregate and manage clinical trial data in real time, as Deloitte has noted. Last week, a startup revealed an AI system that can accurately predict clinical trial outcomes.

Yet for organizations to fully realize AI’s promise is not simple. The task requires oversight, transparency and diverse collaboration. Core considerations include educating users to build trust in AI tools and ensuring the clinical precision of medical-grade AI algorithms. From unraveling the ‘black box’ of algorithms to safeguarding patient privacy, this article provides a checklist to help organizations responsibly incorporat…

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Butterfly Network posts Q2 results, announces new AI marketplace

The Butterfly Network IQ+ system [Image courtesy of Butterfly Network]Butterfly Network (NYSE:BFLY) shares rose today on second-quarter results that topped the consensus forecast.

Shares of BFLY ticked up 3.8% at $2.44 apiece in midday trading today. MassDevice’s MedTech 100 Index, which includes stocks of the world’s largest medical device companies, dipped 0.7%.

The Burlington, Massachusetts–based handheld ultrasound developer posted losses of $28.7 million, equalling 14¢ per share. Butterfly posted sales of $18.5 million for the three months ended June 30, 2023. It recorded a $7 million bottom-line gain on a sales decline of 3.8%.

Losses per share came in 2¢ ahead of expectations on Wall Street, while sales topped projections of $18 million.

“During the quarter, we conducted a full strategy reevaluation; chose a focused, impactful plan, completed a reorganization to give us time to fund the plan, and implemented growth initiative…

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eClinical Solutions Q&A: The quest to transform raw data into drug discovery gold

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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 a strong emphasis on AI in clinical trials optimization.

Specifically, eClinical Solutions taps AI/ML for automated data mapping, classification, review and mining insights. This enhances efficiency, speeds up cycle times and ensures quality as data complexity grows. The company’s Elluminate platform integrates and structures data, supporting advanced analytics.

Powerful techniques like anomaly detection algorithms can automatically flag potential data issues for human review. ML also classifies and categorizes data to focus reviewer time on the most critical areas. Fostering an innovative cultur…

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Investments in AI and ML help PV teams transform safety case processing

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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 pharmacovigilance processes across intake and assessment, review, full data entry, medical review, quality review and submission.

A new opportunity in AI and ML

The life sciences industry is rapidly growing in scale and complexity, with organizations generating increasingly large volumes of safety data. The pharmaceutical industry, healthcare providers and consumers have reported more than 18.6 million adverse events to the U.S. Food and Drug Administration (FDA) in the last 10 years, 216% more than the prior 10 years.

Safety case da…

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Machine learning model flags patients with high risk of surgical complications

Improving the health of high-risk patients before their surgeries can lower mortality rates and cut healthcare costs. [Image by Gorodenkoff via Adobe Stock]

A newly developed machine learning model for surgical patients is automatically flagging those at high risk of complications to improve their odds of survival and reduce healthcare system costs.

Each day, the software reviews electronic medical records for patients scheduled for surgery and identifies those who might benefit from individualized coordinated care or prehabilitation to improve surgical results.

Researchers and physicians at the University of Pittsburgh and University of Pittsburgh Medical Center (UPMC) trained their algorithm on medical records for more than 1.2 million surgical patients. To help predict whether patients might suffer from complications after surgery, they focused the model on deaths from strokes, heart attacks and other…

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July 2023 edition: Life-saving LVADs, supplier innovations and AI breakthroughs



LVADs save lives: So why aren’t more available?

What’s new in 3D printing: medical devices, research, innovation, automation and partnerships

AI breakthroughs in medtech: 7 ways to enhance healthcare

Life-saving LVADs, supplier innovations and AI breakthroughs

Kyree Miller recalls the day his heart stopped beating.

“I remember the entire room going white,” he said. “And I actually turned over on my side and I said, ‘Tell my mom I love her.’”

A couple of weeks later, the heart failure patient — who was only in his 20s at the time — received his first left ventricular assist device (LVAD) implant while he waited for a heart transplant. One year passed, then two, then three. Finally, after surviving on LVAD technology for seven years, his new heart came.

“When you get your transplant, there’s a whole new energy that you get. … But I can honestly say there was a whole new energy that I got when I had my LVAD,” Miller said.

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Medical imaging AI startup Flywheel wins Series D round backed by NVIDIA, Microsoft and HPE

[Image courtesy of Flywheel]

Minneapolis-based Flywheel has received $54 million in a Series D round backed by NVIDIA, Microsoft, Hewlett Packard Enterprise and other strategic investors.

Flywheel will invest the cash to fuel growth in core verticals, the pharmaceutical and public sector healthcare sectors. A notable Big Pharma customer is Genentech. The company also aims to ramp up expansion into emerging areas such as healthcare providers, payers, IT service providers and software vendors. Finally, Flywheel intends to extend its global footprint, especially in key markets in Europe.

Current challenges in medical AI

Medical imaging has long faced challenges with data complexity and a mosaic of metadata and formats, including DICOM (Digital Imaging and Communications in Medicine) to JPG or TIFF and modalities spanning MRI, CT, PET and ultrasound. Despite some standardization, fragmented formats prevail fr…

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Working backwards: AWS’s strategy for pharma’s cloud-enabled transformation

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The meteoric rise of the AI sector is hard to fathom. Projections from Precedence Research suggest that the global AI market could balloon by 2600% from 2022 to 2032, hitting $1.87 trillion — an annual growth rate of 39%.

In pharma, AI and data science demand is surging though overall growth is sluggish. Despite advances such as the rapid development of COVID-19 vaccines, the broader sector has struggled to keep up with the overall stock market. But the future could tell a different story. McKinsey projects that the pharma and medical products sector could gain 9% in EBITDA from cloud computing.

To tap this potential, cloud vendors are allying with pharma companies. “Nine of the top 10 pharma companies in the world have a large majority of the workloads running on AWS,” noted Tehsin Syed, general manager of AWS Health. These workloads encompass diverse areas including IT infras…

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Why a smart approach to AI-driven drug discovery prioritizes sustainability

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The fact that the biopharmaceutical industry has a large carbon footprint is well established. A 2022 study from My Green Lab confirmed that biotech and pharma are still among the globe’s top polluters. The research highlights that a mere 4% of the largest publicly-traded biotech and pharmaceutical firms have climate commitments in line with the UN’s Intergovernmental Panel on Climate Change (IPCC) to cap warming at 1.5°C by 2030.

Yet climate change remains the most pressing threat to human health, potentially causing 250,000 additional deaths per year, as the World Economic Forum has noted.

AI as a doubled-edged sword in sustainability

For biopharma, AI-driven drug discovery could serve as a double-edged sword when it comes to sustainability. On the one hand, these technologies promise to enable new discoveries and optimized processes that could slash emissions.

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Google Cloud partners with Mayo Clinic on generative AI

Google Cloud and Mayo Clinic will team up on generative AI for healthcare, the two organizations said today.

They intend to develop new capabilities for healthcare organizations to increase productivity, automate repetitive tasks and make administrative processes more efficient. Mayo Clinic and Google Cloud said they are also working with several unidentified healthcare organizations through this partnership.

Previously: The cloud is transforming medtech: Amazon, Microsoft, Google, J&J, Philips and GE Healthcare leaders explain

Mayo Clinic is already using Google Cloud’s Enterprise Search in Gen App Builder and looking for ways that search and generative AI can retrieve information more efficiently and effectively from healthcare records, research papers and clinical guidelines across a variety of formats and locations.

“Our prioritization of patient safety, privacy, and ethical considerations, means that generative AI can have a s…

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Medical device industry ramps up for the CSA Act’s software changes

Change is coming for software development teams at medical device manufacturers through the Computer Software Assurance (CSA) Act.

Carla Neves is quality manager and medical devices product owner at Critical Manufacturing. [Photo courtesy of Critical Manufacturing]

By Carla Neves, Critical Manufacturing

The Computer Software Assurance (CSA) Act of 2022 aims to improve quality and cost-efficiency in validating computer systems for medical device manufacturing. Although it has not been finalized, manufacturers, software developers, and consultants have fully embraced it and are ramping up for implementation.

Transitioning to risk-based validation after more than 20 years of document intense compliance will likely dominate medical device software operations for many years to come, as will building out the manufacturing execution system (MES) infrastructure to support it and developing the innovations that t…

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HeartBeam partners with Samsung to boost at-home cardiac care

HeartBeam has announced a strategic alliance agreement (SAA) with global tech giant Samsung.

The alliance, announced today, builds upon an existing SAA between Samsung and Livmor, whose assets HeartBeam acquired earlier this year.

Livmor created the FDA-cleared wearable Halo atrial fibrillation detection system — an FDA-cleared, Samsung-Galaxy-watch-based arrhythmia detection tool. Meanwhile, HeartBeam recently secured a pivotal patent related to artificial intelligence capabilities for its AIMIGo system — a personal, portable vector electrocardiogram (VECG) system. Also, this month, HeartBeam submitted AIMIGo for FDA 510(k) clearance.

This collaborative venture between HeartBeam and Samsung will explore opportunities to leverage HeartBeam’s proprietary technology and expertise in cardiac symptom assessment and monitoring. The two companies think their technologies could boost the standard of cardiac diagnostic capabilities.

HeartBeam’…

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