AI not only improves data collection and analysis, it impacts which products are engaged in clinical trials, determines necessary medical criteria, helps design the trials and can even choose the best participating facilities. The result is, organizations that leverage AI will be more successful and will go to market faster than those that don’t.
Augmented reality (AR), with the help of artificial intelligence (AI), is providing healthcare professionals with the means to offer patients an unprecedented level of care and personalized treatments, and assisting MedTech and life sciences companies in product design and development. Yet, the potential of AR with AI in health care is still far from fully explored.
As VP of Product Marketing for a MedTech startup, my role is to champion pioneering medical technology, strategically spark interest and drive it out of the design lab and into the field where it will ultimately change, or even save lives. Over the last two decades, I’ve seen the industry evolve in interesting ways, and I’ve learned some enduring lessons about market introduction and launch of market-making technologies post-FDA clearance.
The dramatic increase of medical devices in patient care has yielded many benefits. However, this technology also carries various risks, including risks to patient privacy, that must be addressed.
RFID and IoT technologies can strengthen the medical device supply chain and improve workflows. The following real-life examples illustrate the benefits that can be achieved.
As technology component pricing continues to rise, MedTech manufacturers are applying proven methods and exploring new approaches to maintain profitability and extend product lifecycles.
When considering use cases and data classification methods for machine learning, image quality, power consumption and latency must be considered.
Not all use cases are good candidates for machine learning. In this column we look at cases where AI/ML may be appropriate and when building a traditional algorithm to solve a problem is a better choice.
The regulatory landscape for medical devices is rapidly evolving, catapulted most recently by European Union Medical Device Regulations (EU MDR). In this article, Monali Bhansali, Practice Lead of Regulatory Affairs at Tata Elxsi, highlights challenges and advancements in the MedTech regulatory landscape, and what the future has in store.
Regulatory requirements for computer systems validation (CSV) have long been in place, but their compliance requires considerable time and resources. In the life sciences industry, traditional validation processes add to project timelines and costs, affecting time to market and preventing the deployment of newer versions of software. In addition to improving accuracy and coverage, automated CSV processes can create the same artifacts as manual execution and expedite the upgrade timeline.
