While physiologist have made significant progress in decoding biochemical and electrical signals in multicellular systems, the field of mechanical signals remains relatively unexplored. However, a groundbreaking discovery looms on the horizon and has the potential to change the landscape of tissue: magnetically actuated extracellular matrices, or MagMA.

MagMA to revolutionize tissue engineering

As described in a pioneering article published in the “Device” journal by Rios and colleagues, they envisioned a substrate capable of dynamically applying mechanical forces to cells, precisely guiding their alignment and behavior. This substrate has the property of influencing cell anisotropy, meaning the properties that organized cells in tissues exhibit concerning the direction of the stimulus.

To grasp the concept of anisotropy, it is possible to consider a tree trunk seen in cross-section, with its succession of growth rings. As intuitive, the mechanical responses to twisting and pressure will differ if applied transversely or longitudinally concerning the trunk’s rings. The same principle applies to muscles, which exhibit different structural and functional properties and behaviors based on how constituent cells are organized in the tissue and how mechanical stimulus is applied concerning force, direction, and temporal variability.

According to the authors, MagMA — a magnetically actuated platform poised to revolutionize the field of tissue engineering — can influence cell behavior and enable the programming of morphological and functional anisotropy within tissues, particularly in skeletal muscles.

One of the potential applications of MagMA involves dynamically programming the alignment of muscle fibers. In the context of skeletal muscle tissue engineering, the ability to control the directionality of muscle fiber alignment is crucial for a wide range of applications, from regenerative medicine to biohybrid robotics. By employing dynamically guided mechanical stimulation using MagMA, researchers can achieve coordinated alignment and contractility of muscle tissues.

MagMA will offer higher value and flexibility in future solutions

Previous muscle engineering techniques had significant limitations in achieving such coordination properties. Programming cell properties and functions could only occur at the time of implantation and remained unchanged later, without any corrective intervention if the tissue’s operating conditions changed—that is typically occurring in human tissues. In contrast, MagMA allows real-time adjustment of stimulation parameters, enabling researchers to modify patterns of muscle cell alignment even after implantation. This potential capability could offer higher value and flexibility in future solutions.

A significant advantage of MagMA is its capacity to separate the mechanical and biochemical effects of muscular exercises. Several studies demonstrated that exercise could lead to significant increases in muscle strength and alterations in fiber characteristics. To achieve this, rehabilitative practices used passive mechanical stimulation techniques to facilitate the recovery of patients’ muscular functionality.

However, research by Rios and colleagues revealed that mechanical stimulation alone is not equivalent to exercise, suggesting that synergistic effects may result from the combination of biochemical and mechanical stimulation. This discovery opens the door to exploring MagMA’s effects in combination with other forms of stimulation, further expanding the possibilities of tissue engineering.

The development of MagMA marks a true revolution in tissue engineering. With the introduction of dynamic mechanical stimulation, this platform enables real-time control of cell alignment and behavior within artificially created tissues. The robustness and adaptability of the technology make it applicable to a wide range of cell types and chemical characteristics of hydrogels, further expanding its utility.

While acknowledging the need for deeper studies and continued development of operational models closer to real tissues, the MagMA platform is potentially a true game-changer in the field of tissue engineering. Its ability to program anisotropy in artificially created tissues, such as skeletal muscles, opens a realm of possibilities for regenerative medicine and biohybrid robotics.

As researchers continue to explore its developmental potential and refine applications, making them more robust and flexible, it is possible to anticipate a new era in tissue engineering that combines the precision of mechanical control with the complexity of biological systems.

Evolution and Benefits of DHTs in Neurology Trials

DHTs – like wearables, mobile health apps, and telemedicine platforms – have for example significantly impacted the design and execution of neurology trials. In a recent review paper appeared on Nature, Mittermaier et al. reported a substantial increase in the use of DHTs, from 0.7% in 2010 to 11.4% in 2020, with projections suggesting up to 70% of clinical trials incorporating wearable sensors by 2025. The shift from simple tracking methods to more complex measures like speech and cognition demonstrates the growing sophistication of DHT applications.

The use of DHTs in neurology trials produced consistent benefits on many levels. The continuous remote monitoring facilitated by DHTs allows for the collection of diverse, longitudinal data, offering insights into disease physiology and outcomes. This evolution has given rise to digital phenotyping and the creation of digital twins for precision medicine. The advantages extend beyond research efficiency, with decentralized and virtual trial settings reducing the burden on participants by minimizing travel time and costs.

Challenges and Considerations

While DHTs present promising opportunities, challenges such as the digital endpoint harmonization and the digital divide must be addressed. In particular, the Lancet and Financial Times Commission emphasized the need for investments in digital infrastructure to bridge the gap in internet access and technology literacy, ensuring equitable participation in clinical trials.

Importance is also associated with the need to build a solid and shared regulatory framework; and to generate consensus about data reliability methods. The incorporation of novel digital endpoints requires a standardized evaluation framework. Considerations of trustworthiness, explainability, usability, and transparency are crucial in evaluating Biometric Monitoring Technologies within DHTs. Authentication issues in virtual trials also necessitate innovative solutions, including biometric authentication and continuous user identification through AI models.

Maintaining data quality remains a challenge in real-world settings, with artifacts from the environment, devices, and patient behavior impacting reliability. Strategies for assessing data completeness and developing signal quality indices, as demonstrated for example in epilepsy studies, contribute to enhancing the credibility of DHT-derived measures.

Healthcare Industry Driving Change

Healthcare industry is rapidly becoming an engine of change for the use of DHTs in clinical trials. AstraZeneca has launched Evinova, an healthtech business focusing on providing digital solutions for clinical trials in the life sciences sector. Operating independently within the AstraZeneca group, Evinova offers established digital technology solutions globally, aiming to optimize clinical trial design and delivery. The company will supply solutions to AstraZeneca while extending services to pharma, biotech companies, and clinical research organizations. Evinova’s products, including AI and machine learning algorithms, reduce the time and cost of developing medicines, enhance patient experiences, and support digital remote patient monitoring and digital therapeutics. The portfolio covers clinical development support, automatic costings, and assessments of operational feasibility, along with software for comprehensive clinical program and trial management. Evinova, with support from CROs Parexel and Fortrea, collaborates with Accenture and Amazon Web Services to accelerate industry adoption and expand global reach.

Another example is CliniScout Recruit by Healthware – a digital service for recruiting subjects to clinical trials. It has been used in various studies in Europe with great results. As recruitment is one of the largest single challenges in clinical trials, the benefits are significant. Additionally, another of Healthware’s DHT services for clinical trials is CliniScout ePRO. It improves subject engagement and communication, as well as streamline the collection of real-world and quality-of-life data. The comparison to traditional tools like paper diaries and phone calls is remarkable, which also has been demonstrated in patient surveys of CliniScout users.

Conclusion: Shaping the Future of Clinical Trials with DHTs

In conclusion, the growing utilization of DHTs in neurology trials marks a transformative shift towards decentralized and virtual clinical research. While presenting unprecedented opportunities for data collection and trial efficiency, careful consideration must be given to address challenges, ensuring equitable access and maintaining data reliability. As DHTs continue to shape the future of clinical trials, collaborative efforts between stakeholders, regulatory bodies, and technology developers are essential to maximize their potential benefits and minimize potential pitfalls.

In what may be a revolutionary development, a group of scientists has unveiled an artificial intelligence (AI) system capable of remotely assessing the motor performance of people with Parkinson’s disease (PD).

Parkinson’s Disease: Human Assessment vs. AI

Parkinson’s disease is a rapidly growing neurological disorder for which there is no known cure. Regular clinical evaluations and medication adjustments are key to managing symptoms and improving quality of life for those affected. However, access to neurological care is limited, leaving many Parkinson’s patients without proper treatment or diagnosis, especially in underserved regions and for the elderly living in remote areas. In a study published in Nature, Md Saiful Islam et al. focused on a simple but effective motor task known as the finger tapping test, commonly used to assess bradykinesia, a key Parkinson’s symptom characterized by slowed upper limb movements. The researchers enrolled 250 participants from around the world, who performed the finger tapping test in front of a webcam. Three experienced neurologists independently rated the recorded videos on a scale of 0 to 4, based on the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS).

The AI Model Used in the Research

The results of the comparison between human and AI assessments were impressive. Inter-rater reliability among expert neurologists was excellent, with an intra-class correlation coefficient (ICC) of 0.88, indicating a high level of agreement in their assessments. The researchers then developed computer algorithms to extract objective measurements from the finger tapping task, based on MDS-UPDRS guidelines and strongly correlated with neurologists’ assessments.

The artificial intelligence model trained on these measurements outperformed two MDS-UPDRS-certified evaluators, with an average absolute error (MAE) of 0.58 points compared to the evaluators’ average MAE of 0.83 points. Although the artificial intelligence model lagged slightly behind experienced neurologists (0.53 MAE), it showed great potential in assessing Parkinson’s severity. This innovative methodology can be replicated for similar motor tasks to provide an objective and accessible means of remotely assessing people with Parkinson’s and other movement disorders, even in areas with limited access to neurological care.

Implications of the Research

The implications of this research are far-reaching. Imagine that anyone, regardless of location, could perform a motor task using a computer webcam and receive an automated assessment of the severity of their motor performance. This progress will face several challenges, including collecting data in home environments, developing metrics that can be interpreted as digital biomarkers, and creating user-friendly platforms for remote assessments.

In addition to Parkinson’s disease, this technology offers the opportunity to assess and track other movement disorders such as ataxia and Huntington’s disease, where finger touch provides valuable insights into disease severity. In addition, the tool can be expanded to allow longitudinal monitoring of symptom progression, fine-tuning of Parkinson’s treatment, and assistance to people with episodic symptoms.

Limitations of the study

However, the study acknowledges some limitations, such as potential problems with tremors affecting the accuracy of evaluations and the need for a larger and more diverse dataset to improve the artificial intelligence model. As this technology advances, it is crucial to address ethical considerations regarding data security, user privacy, and algorithm bias.

The study results potentially fill a gap in the diagnostic component of the Parkinson’s patient pathway, while the support for behavioral modifications is already covered significantly by specific digital health apps.

The Soturi App for a personalized Parkinson’s treatment

Another notable solution is the Soturi app, specifically designed for Parkinson’s disease (PD) patients by Newel Health, which has been supported by a grant from the Michael J. Fox Foundation. The app was co-designed with PD patients and health experts. The goal is to create an algorithm that analyzes the data collected to optimize and personalize drug treatment for Parkinson’s. To this end, exercises and other services are provided to engage the patient and facilitate the collection of motor data automatically (via a wearable band) and ongoing symptoms.

Conclusions

Advancements in artificial intelligence and digital health apps bring us closer to more accessible and accurate assessments of Parkinson’s disease and its behavioral therapy at a distance. Although there are challenges to overcome, the potential benefits for patients worldwide are undeniable and offer hope for improved diagnosis, monitoring, and treatment of these debilitating conditions.

AI has emerged as a transformative force in various fields, and its application in healthcare is no exception.

The use of Large Language Models in healthcare

Large Language Models (LLMs) represent a significant milestone in AI development. They empower machines to comprehend and produce human-like language. Among these models, the generative pre-trained transformer (GPT), particularly the GPT-3.5 model, has gained attention for its capacity to generate intricate responses across various languages. Recent advances in GPT-4 have expanded its capabilities, allowing images to be uploaded as input.

These AI models have the potential to transform the medical field, but understanding how patients perceive and engage with the content generated by these tools is equally crucial to effectively integrate them into healthcare facilities.

The study on patients in treatment for urolithiasis

In a study recently published in the Journal of Digital Health, Seong Hwan Kim and other authors analyzed a case study involving patients undergoing treatment for urolithiasis, a condition characterized by the formation of stones in the urinary tract. The authors examined how AI-powered chatbots, such as ChatGPT version 3.5, impacted patients’ perceptions both before and after receiving information about lifestyle changes aimed at preventing the recurrence of urolithiasis. The goal of this study was to illuminate the evolving relationship between patients and the use of artificial intelligence in healthcare.

Patients involved in the study were asked to complete questionnaires via a self-administered survey. An initial questionnaire was provided before the explanation on lifestyle modifications to prevent the recurrence of urolithiasis, while the next questionnaires were distributed after patients received the explanation generated by ChatGPT.

Inclusion criteria consisted of patients who had been diagnosed with urolithiasis through computed tomography, had undergone ureterorenoscopy treatment, and who were 18-80 years old. Patients who were unable to understand the ChatGPT indications, or to complete the questionnaires, were excluded.

The introduction of AI-based chatbots in healthcare can enhance patient engagement and education. However, the findings of the cited study revealed negative reactions from patients, especially among those with lower levels of education. This implies that this category of patients may have a more negative perception of AI-generated content, potentially due to an insufficient understanding of the digital world.

The perception of AI in healthcare: how is it influenced?

Like any potentially innovative technology, the perception of AI in healthcare is influenced by many factors, including the nature of the technology itself and the features of the individual patient. This influence is justified by one of the health determinants identified by the WHO, namely, the patient’s level of education. While AI has the potential to improve healthcare and clinical outcomes for patients, it must be used in a way that meets the needs of patients according to their educational background. This is particularly important in the medical field, where complete reliance on AI-generated information is pivotal for their well-being.

Urolithiasis can profoundly affect patients’ physical and mental health. Lifestyle changes play a crucial role in preventing the formation of stones, alongside adherence to specific dietary guidelines. AI-powered chatbots, like ChatGPT, can help patients understand and follow these recommendations, summarizing complex information and offering guidance in a straightforward manner.

The reliability of AI-generated content

The reliability of AI-generated content continues to be a significant topic of debate. Chatbots like ChatGPT depend on data collected from the Internet, which may contain inaccuracies and errors. Ensuring the reliability of AI-generated medical information is essential for reducing risks for patients.

For this very reason, future developments of AI chatbots should prioritize the verification of medical content to increase its reliability in clinical settings. Allowing physicians to program the AI themselves should be considered to ensure the accuracy of the information and the responses provided to users.

Despite the challenges, chatbots are being used to simplify low-complexity tasks and improve the flow of information in healthcare. They aid physicians by summarizing clinical information, managing health records, and offering advice from evidence-based data. However, generative artificial intelligence cannot replace human physicians. To ensure responsible use in the medical field, problems surrounding data accuracy and the generation of false information need to be addressed as soon as possible.

Conclusions

In conclusion, the study highlighted how patients perceive AI in healthcare and how this perception is changing, specifically in the management of urolithiasis. As previously mentioned, patients with lower levels of education expressed a negative evaluation after receiving an explanation generated by ChatGPT. Even though chatbots have the potential to improve patient knowledge and engagement, some points need to be resolved to integrate them effectively.

To improve patient perceptions and promote the correct adoption of AI in healthcare, it is necessary to develop user-friendly interfaces, provide clear and accurate information, and prioritize authoritative verification of medical content. Chatbots have their limits, but their continued development and improvement promises to enhance healthcare delivery and its clinical outcomes in the future.

The first application of AI to the pharmaceutical industry is its use in ramping up and improving new drug discovery. The traditional trajectory of drug discovery and development is synonymous with long lead times and exorbitant costs, often taking many years and billions of dollars before a new drug sees the light of day. In addition to this, the R&D process is often marked by uncertain success, and a high failure rate of drug candidates at multiple stages of development.

However, AI is rewriting this narrative. Thanks to their ability to sift through huge amounts of data, AI algorithms can identify promising drug candidates, anticipate their efficacy and even optimise their molecular structures, thus improving their performance. Thanks to this innovative approach, AI is revolutionising the search for new compounds, significantly increasing the likelihood of identifying successful candidates in record time.

Challenges in pharmaceutical reasearch

One of the most formidable challenges in pharmaceutical research lies in unravelling the intricate web of drug interactions within the human body and predicting potential side effects. AI algorithms come into play in this complexity by orchestrating the analysis of intricate molecular dynamics. This predictive capability has the potential to allow researchers to anticipate and mitigate adverse drug reactions, leading to safer drug designs and reduced risks of unforeseen complications, thereby elevating patient well-being to unprecedented levels.

The effectiveness of AI in processing and decoding vast amounts of data can also be seen in patient-centred care. By analysing a patient’s genetic profile, medical history and other relevant factors, AI-driven algorithms enable healthcare professionals to formulate highly personalised treatment strategies. This personalisation not only amplifies treatment efficacy but also reduces the likelihood of unwanted reactions, culminating in superior patient outcomes that align with the ethos of precision medicine.

The clinical trials phase represents a crucial turning point in drug development, but is often characterised by inefficiencies and delays. Here, AI proves to be an indispensable ally by orchestrating the optimisation of clinical trials. It does this by identifying the most suitable patient cohorts, predicting study outcomes with incredible accuracy and even designing study protocols that maximise efficiency. The sum of these AI-enabled interventions manifests itself in reduced study time and financial costs, thus accelerating the availability of treatments for those who need them.

AI alghoritms can accelerate drug development

The influence of AI extends far beyond the creation of new drugs, fundamentally altering the drug repurposing paradigm. By exploring vast archives of medical records and scientific literature, AI algorithms unveil latent possibilities for the repurposing of existing drugs. This approach accelerates drug development while simultaneously opening up new revenue streams for pharmaceutical companies, embodying the industry’s shift towards sustainability.

In pharmaceutical manufacturing, AI takes shape in robotic process automation (RPA), ensuring efficiency and maintaining strict quality control standards. AI-powered robots handle meticulous tasks such as dispensing ingredients, mixing compounds and packaging drugs. In overcoming human fallibility, these robotic systems establish consistency and compliance with strict manufacturing regulations.

 As the scope of AI applications continues to broaden, its transformative impact on the pharmaceutical industry becomes more evident.

From drug discovery and development, to  patient-centred care and  manufacturing processes, AI stands as the cornerstone of this transformation. This fusion of technology and medical science is poised to deliver safer and more effective treatments to a global patient population, paving the way for a future where the boundaries of science fiction dissolve into tangible medical realities. In this light, the integration of AI remains a force of the highest order, driving the pharmaceutical industry towards a horizon filled with new possibilities.

Conditions such as cardiovascular disease, diabetes, obesity, and chronic kidney disease are wreaking havoc on healthcare systems and individuals worldwide. In 2017 alone, dietary risk factors were responsible for close to 11 million deaths and 255 million disability-adjusted life years across the globe. Traditional approaches to managing these conditions reaching their limits, with clinical workforce burnout, resource shortages, and the added strain of the COVID-19 pandemic further exacerbating the issue. Thus, the need for innovative strategies to address these challenges has never been more urgent.

In this context, digital health emerges as a catalyst for revolutionizing healthcare delivery. Digital health encompasses electronic health (eHealth) and mobile health (mHealth), which leverage electronic platforms and mobile technologies, including wearable devices and apps, to provide health information and services. The adoption of these technologies has skyrocketed in recent years, with smartphone subscriptions globally increasing from 2.6 billion in 2016 to a staggering 6.3 billion in 2021. This widespread access to digital health tools positions it as an affordable and scalable public health strategy.

Reshaping dietary management

Among the most exciting prospects of digital health is its capacity to reshape dietary management. These platforms enable individuals to electronically track their dietary intake, streamlining sharing with healthcare professionals or self-monitoring. This increased engagement empowers patients, fostering shared responsibility and decision-making, and strengthening trust between patients and healthcare providers. Additionally, digital health offers the flexibility to access services when and where it is most convenient, addressing issues of patient burden, healthcare inequity, and resource efficiency.

However, despite its vast potential, the efficacy of digital health interventions remains a subject of inquiry, particularly for specific population groups and dietary interventions. While systematic evaluations have assessed the effectiveness of digital health interventions in various contexts, there’s a notable gap in research concerning diet-related chronic conditions. Many reviews have focused on telehealth and telephone interventions, largely overlooking the potential of mHealth and eHealth technologies. Moreover, there’s a lack of comprehensive research on the digital dietary assessment methods used in these interventions. Thus, a critical question arises.

Can digital health truly revolutionize dietary care?

To address this question, a systematic review was conducted by A. Barnett et al., and published on the Journal of Digital Health. The review was aiming to evaluate the effectiveness of dietary interventions delivered through digital health for adults with diet-related chronic conditions. The findings of this review shed light on the current state of digital health’s impact on dietary intake and clinical outcomes.

The review uncovered positive outcomes in various areas, including improvements in diet quality scores, increased fruit and vegetable intake, reduced sodium consumption, as well as reductions in body weight, waist circumference, and HbA1c measures. These results indicate that digital health interventions could lead to significant changes in dietary habits and associated health metrics.

However, it’s crucial to note that while some outcomes showed promising improvements, others yielded only modest or non-significant results. This suggests that the effectiveness of eHealth and mHealth in dietary interventions varies across different aspects of care. Therefore, further research is necessary to pinpoint which specific components influence the effectiveness of digital health interventions.

Moreover, the review highlights the importance of better reporting dietary assessment methods within digital health interventions. Rigorous examinations are essential to confirm the validity of these methods and the content of dietary education provided to patients. This will not only strengthen the credibility of digital health interventions but also enable healthcare providers to offer more effective dietary education more effectively.

Digital health has the potential to revolutionize dietary education and management for individuals with diet-related chronic conditions. The abovementioned systematic review underscores the strides that have already been made, with tangible improvements in diet quality and various health markers. However, it also highlights the need for caution, as not all outcomes show equally positive results.

What’s next?

To unlock the full potential of digital health in dietary care, further research is imperative. Robust trials are needed to better understand the components that make digital health interventions more effective. Additionally, there is a pressing need for improved reporting on dietary assessment methods and the content of dietary education within these interventions.

In essence, these studies on Digital Health state-of-the-art serve as a call to action. They urge the healthcare community to continue exploring the vast opportunities offered by digital health, fine-tuning interventions, and conducting research that will guide their implementation on a larger scale. The road ahead holds immense promise for transforming the way we manage diet-related chronic conditions, ultimately alleviating the strain on healthcare systems and improving the lives of millions around the world.

Anyone who has children of school age notices that most of them are generally uninterested, uninvolved, often bored. It is not that in the past, school was made up of legions of pupils anxious to go to class, to be tested or to do their homework, far from it.

But today there is a feeling that the level of detachment goes beyond a simple dichotomy between the absolute freedom experienced at pre-school age, and the system of rules and assessments that progressively limits this freedom during the course of schooling, replacing it with an adult structure of thought and action.

A generic response to the lack of interest on the part of pupils can cite as causes the progressive cultural impoverishment of society, as well as the progressive devaluation of culture as a means of emancipation and social advancement.

But alongside this, questions of a different kind probably need to be asked.

Does our school system, especially middle and higher education, have a range of programs that serve to form citizens of the modern world? Do we really still need to study subjects that most pupils will forget the day after they leave the school building, and that will be of no use to them in life? Are the subjects that really serve the formation of a ruling class and a modern civil community still those identified by school reforms that are the expression of a world of a century ago?