AI in MedTech 2023: A Personal Perspective

1. Introduction: A Year of Unprecedented Advances in MedTech

What a remarkable year it has been for MedTech! At Deviceology, we’ve been truly astounded by the rapid advancements in AI and their profound impact on medical technology. It feels like every day brings a new breakthrough, reshaping how we approach healthcare innovation, challenging traditional healthcare paradigms and opening new frontiers in patient care and medical research.

Here at Deviceology, my Co-founder Richard Bunney and I have been both amazed and inspired by the rapid evolution of MedTech. The sheer velocity of change has been nothing short of extraordinary. It’s a thrilling era where technology is not just aiding but actively shaping medical practices and outcomes. AI, in particular, has emerged as a pivotal force, driving innovations that were once the realm of science fiction into today’s clinical reality.

Amidst this surge of technological advancement, regulatory authorities and international standards boards have faced significant challenges. Keeping pace with the rapid development of AI applications in healthcare has necessitated a revaluation and adaptation of existing regulatory frameworks. It’s a delicate balancing act between fostering innovation and ensuring patient safety, data security, and ethical compliance.

For us at Deviceology, it’s not just about observing these monumental changes; it’s about being a proactive force in this exhilarating journey. Our commitment extends beyond mere adaptation to these advancements; we strive to be at the forefront, championing the democratization of healthcare across the globe. By helping our clients break down barriers and deliver more health equality though technology, we aim to make cutting-edge medical care accessible to all. 

Guiding our clients through the labyrinth of technological and regulatory complexities is a part of this mission. We are dedicated to ensuring that together, we not only navigate but also capitalise on the full potential of AI in MedTech, transforming healthcare delivery for a more equitable and healthy world.

In this blog I delve into the latest trends, breakthroughs and real-world applications for just a few of these developments and try to identify the implications for our industry and our species. 

2. Current Trends in AI and MedTech

2.1 Generative AI’s Impact in Healthcare

Generative AI is reshaping healthcare with its diverse applications across our industry. A prime example is the work of DeepMind and its AI product, AlphaFold. AlphaFold has made significant strides in protein folding, a complex problem in biology. By predicting the 3D structures of proteins accurately, it is revolutionising drug discovery and has vast implications for understanding diseases and developing new treatments. This innovation exemplifies how generative AI can lead to more efficient processes, personalised patient interactions, and groundbreaking advancements in medical research and product development. More about DeepMind later in the blog. 

2.2 Breakthroughs in Medical Technology

The field of medical technology has seen several groundbreaking advancements recently, driven by AI and innovative research. Here are just a few notable examples:

Gene Editing with CRISPR (CRISPR Therapeutics): One of the pioneers in this field, CRISPR Therapeutics, is utilising CRISPR/Cas9 technology to develop gene-based medicines. Their work focuses on serious diseases, including treatments for sickle cell disease and beta-thalassemia.

AI-Driven Drug Discovery (Atomwise): Atomwise uses AI for drug discovery, focusing on the use of deep learning algorithms to predict how different potential medications might interact with targets in the human body. This approach can significantly reduce the time and cost of drug development.

Onavital+ (Onalabs Inno-hub, S.L.): Onalabs, a pioneering company in the realm of health monitoring, has introduced Onavital+, a cutting-edge wearable device designed to revolutionise personal health tracking. Onavital+ offers a comprehensive approach to health monitoring, far beyond traditional wearable devices. It leverages advanced sensor technology to provide continuous, non-invasive monitoring of crucial physiological parameters such as heart rate, temperature, oxygen saturation, and even stress levels. This device is particularly innovative in its ability to translate complex biological data into actionable insights, empowering individuals with a deeper understanding of their health. 

What sets Onavital+ apart is its emphasis on scientific rigor and precision that underpin its development. The device’s ability to provide real-time health data makes it an invaluable tool not only for users seeking to proactively manage their health but also for healthcare professionals who can leverage this data for more informed patient care. Onavital+ represents a significant leap in wearable health technology, offering a new level of accessibility and insight into personal health management.

Robot-Assisted Surgery (Intuitive Surgical): Intuitive Surgical’s da Vinci system is a pioneering example of robot-assisted surgery. The system enhances a surgeon’s capabilities by providing a magnified 3D high-definition view of the surgical site and translating the surgeon’s hand movements into smaller, precise movements of the da Vinci instruments.

AI in Radiology (Aidoc): Aidoc specialises in AI-based radiology solutions. Their software assists radiologists by flagging acute abnormalities in real time, helping to expedite patient care in critical cases.

Telemedicine and Virtual Health Consultations (Teladoc Health): Teladoc Health is a leader in telemedicine, offering virtual healthcare services. Their platform enables patients to receive medical consultations remotely, improving access to healthcare for those in remote or underserved regions.

I think we can all agree that these examples, and many others, underscore the dynamic and innovative nature of the MedTech industry in 2023 harnessing the power of IA and technology to transform healthcare. 

3. AI’s Transformative Impact in Medical Diagnostics

In recent years, the infusion of artificial intelligence into medical diagnostics has marked a turning point in healthcare. Below I offer some of my favourite examples of how AI is revolutionising the field, enhancing diagnostic accuracy and significantly improving patient safety. From advanced imaging analysis to predictive analytics in patient monitoring, AI technologies are providing healthcare professionals with powerful tools to diagnose and treat with greater precision and efficacy. I explore some of the leading examples of these technologies, each demonstrating the profound impact AI is having on the future of medical diagnostics.

3.1 Enhancing Diagnostic Accuracy

Paige.AI (Paige Prostate): Paige.AI focuses on transforming pathology through AI. Their flagship product, Paige Prostate, aids pathologists in accurately detecting prostate cancer from biopsy slides. This tool enhances diagnostic precision, allowing for more reliable and faster cancer detection, which is crucial for effective treatment planning.

IDx-DR: As a pioneer in AI diagnostics, IDx-DR provides an innovative solution for detecting diabetic retinopathy. This FDA-approved system autonomously analyses retinal images, offering a significant advancement in eye care by enabling early detection and treatment of this diabetes-related eye disease, which can prevent vision loss.

AliveCor (KardiaMobile): AliveCor’s KardiaMobile is a groundbreaking personal EKG device. Utilising AI, it analyses EKGs to detect atrial fibrillation and other heart conditions directly from a smartphone. This device makes cardiac monitoring more accessible and convenient, crucial for early detection and management of heart conditions.

Tempus (Tempus|xT): Tempus is revolutionising oncology diagnostics with AI. Their platform, Tempus|xT, analyses vast genomic data to personalise cancer treatments. By tailoring therapy based on individual genetic profiles, Tempus is at the forefront of precision medicine, improving treatment efficacy and outcomes for cancer patients.

3.2 AI in Patient Safety

MedAware: MedAware is making significant strides in patient safety through its AI-driven medication error prevention system. By identifying prescription errors and harmful drug interactions in real-time, MedAware helps reduce the risk of medication-related complications, which is a critical factor in patient care and safety.

CLEW Medical: Specialising in intensive care, CLEW Medical’s AI platform provides predictive analytics for patient monitoring. It offers clinicians real-time risk assessments and insights, improving decision-making in critical care settings. This technology is vital for early intervention in life-threatening situations, enhancing patient outcomes.

Epic Systems (Sepsis Detection Algorithm): Epic Systems has developed an AI-based algorithm for early sepsis detection, integrated into their electronic health record system. By identifying early signs of sepsis, a potentially life-threatening condition, this algorithm enables timely medical intervention, showcasing the importance of AI in enhancing patient safety.

Again, these examples highlight how AI is being employed to improve diagnostic accuracy and patient safety across various medical specialties, underscoring the transformative impact of AI in healthcare.

Worth a Special Mention: DeepMind’s Transformative AI Contributions

When we were reviewing the myriad of MedTech AI developments at Deviceology for this piece that will contribute to the transformation of our industry there were two developments by DeepMind that we felt were worth a special mention: the breakthroughs in protein structure prediction with AlphaFold and the innovative strides in materials discovery with Graphical Networks for Material Exploration (GNoME). These advancements aren’t just scientific milestones; they represent a the start of a new era.

Protein Discovery with AlphaFold: Unraveling the Mysteries of Biology

DeepMind’s AlphaFold has made an unparalleled contribution to science by predicting the structure of over 200 million proteins. This breakthrough represents a monumental leap in our understanding of biology. The achievement of mapping these proteins, once considered an insurmountable challenge, now provides in-depth insights into the fundamental building blocks of life. For us at Deviceology the implications of this development are profound; understanding protein structures is crucial for multiple areas:

Drug Design: AlphaFold’s database can significantly accelerate the drug discovery process. For instance, it can aid in identifying protein structures that are potential drug targets, thereby speeding up the development of new medications for diseases that currently have limited treatment options.

Disease Comprehension: The detailed understanding of protein structures aids in uncovering the mechanisms of various diseases at a molecular level. This knowledge is vital for developing effective treatments and understanding how different diseases progress.

Biomaterials Development: The insights gained from AlphaFold’s database can revolutionise the development of biomaterials. For example, it can lead to the creation of more compatible and efficient materials for use in medical implants and prosthetics.

Targeted Drug Delivery Systems: With a better understanding of protein interactions, we can develop drug delivery systems that are more precise, ensuring that medication is delivered directly to the intended site of action, thereby increasing efficacy and reducing side effects.

Regenerative Medicine: AlphaFold’s insights can boost advancements in regenerative medicine. By understanding how proteins interact and function, we can better mimic natural biological processes, leading to more effective tissue engineering and regenerative therapies.

These applications are not distant future possibilities; they are imminent realities, thanks to the groundbreaking work of DeepMind and their partners. AlphaFold’s database is a treasure trove of information that is already beginning to transform how we approach medical science and technology. The prospects for innovation in the Medical Devices industry are immense and rapidly becoming reality. 

Materials Discovery: Charting New Territories with AI

DeepMind’s groundbreaking development in materials discovery, known as Graphical Networks for Material Exploration (GNoME), is reshaping the landscape of material science and holds immense promise for the Medical Devices industry. GNoME, which uses deep learning to expedite the discovery of new materials, has predicted structures for a staggering number of new materials. Remarkably, more than 700 of these have been synthesised in the lab and are now undergoing tests. 

Ju Li, a professor of materials science and engineering at MIT, likens GNoME to AlphaFold’s role in protein structure prediction. GNoME’s achievements have significantly expanded our knowledge of stable materials, almost tenfold to 421,000. This expansion of material knowledge is crucial for the Medical Devices industry, offering a wealth of possibilities for innovation and advancement.

One of the key strengths of GNoME lies in its ability to predict the decomposition energy of material structures, a critical factor in determining their stability and usability in engineering applications. Initially, GNoME’s precision in predicting material stability was around 5%, but this quickly improved through iterative learning, ultimately achieving over 80% accuracy for certain models.

A prime example of GNoME’s potential impact can be seen in the development of lithium-ion battery conductors. GNoME identified 528 promising conductors, a discovery that could lead to significantly more efficient batteries. For the Medical Devices industry, this could mean longer-lasting, more reliable power sources for a range of devices, from implantable medical devices to portable diagnostic equipment. 

The work being done at DeepMind, particularly through GNoME, is not just a series of scientific achievements; it’s a series of doors opening to future innovations in medical technology. The ability to discover and utilise new materials will undoubtedly revolutionise the way we develop medical devices, paving the way for more efficient, effective, and patient-friendly solutions.

Recognising the significance of these developments, we at Deviceology are excited to announce we will be doing a deeper dive into DeepMind’s groundbreaking work in an upcoming blog post. This in-depth exploration will discuss the parasitical applications of their contributions and the potential impact on medical technology and healthcare in 2024. Subscribe now to make sure you don’t miss any upcoming blogs from us!

My final thoughts

Reflecting on the breathtaking advancements we’ve discussed, it’s clear that 2023 has been a pivotal year in the realm of MedTech. From the awe-inspiring developments at DeepMind with AlphaFold and GNoME to the transformative applications in diagnostics and patient safety, we stand at the cusp of a new era in healthcare. 

In my role at Deviceology, alongside my co-founder Richard Bunney, we’ve witnessed first hand how these AI breakthroughs are not just reshaping our industry, but are fundamentally altering the very fabric of healthcare. The potential for AI to democratise healthcare, enhance patient outcomes, and accelerate the pace of scientific discovery is immense. These advancements are not just incremental; they represent leaps in our ability to understand and interact with the complexities of the human body and the materials we use to support it.

At Deviceology, we are more than just observers of this evolution; we are active participants, committed to supporting our clients who are harnessing these technologies to break down barriers in healthcare. Our focus extends beyond simply leveraging these advancements for commercial success; we are driven by a vision to make state-of-the-art medical care accessible to all, contributing to a more equitable and healthy world. We take on the compliance burden for our clients so they can focus on what they do best; innovate. 

As we look towards 2024, I am filled with a sense of excitement and responsibility. The advancements in MedTech AI applications and the evolution of regulatory frameworks present both opportunities and challenges. Our goal at Deviceology is to be a guiding force in this landscape, offering our expertise to ensure that our clients not only navigate these changes successfully but also thrive and contribute to the betterment of healthcare globally.

I invite you to join us in this conversation and share your perspectives. Which AI developments from 2023 have caught your attention? What breakthroughs do you think will shape the future of MedTech? Your insights are invaluable as we collectively navigate and shape this exciting journey. Use the comments below to let me have your thoughts and subscribe to our blog so as not to miss out on future insights, so we can continue the conversation together. 

Let’s embrace the future of MedTech, a future that we hope includes innovation, inclusivity, and improved health for all.