At Biogen Digital Health (BDH), we aspire to transform Biogen and patients' lives by making personalized & digital medicine in neuroscience a reality. Powered by data-science and digital technologies, we drive solutions to advance research, clinical care, and patient empowerment. Our team strives for real impact through excellence, innovation, and collaboration. This role is of key importance to achieve the strategic vision and objective to make Biogen a recognized leader in digital health sciences, hence contributing to our corporate vision & strategy. At Biogen Digital Health (BDH), we aspire to transform Biogen and patients' lives by making personalized & digital medicine in neuroscience a reality.

The dawn of the digital medicine era, ushered in by increasingly powerful embedded systems and Internet of Things (IoT) computing devices, is creating new therapies and biomedical solutions that promise to positively transform our quality of life. However, the digital medicine revolution also creates unforeseen and complex ethical, regulatory, and societal issues. In this article, we reflect on the ethical challenges facing digital medicine. We discuss the perils of ethical oversights in medical devices, and the role of professional codes and regulatory oversight towards the ethical design, deployment, and operation of digital medicine devices that safely and effectively meet the needs of patients. We advocate for an ensemble approach of intensive education, programmable ethical behaviors, and ethical analysis frameworks, to prevent mishaps and sustain ethical innovation, design, and lifecycle management of emerging digital medicine devices.

Digital health is defined as the space where digital technologies, daily life, and health care intersect. The objective of digital health is to enhance the efficiency of healthcare delivery and make medicine more individualised and precise. Information and communication technologies are used to help address the health problems faced by people undergoing treatment. The interconnectedness of health systems development, improved use of computational analysis, smart devices, and communication media are the techniques and tools used in digital health to aid clinicians and their clients with managing illnesses and health conditions while simultaneously promoting good health and well being. Generally, digital health is concerned about the development of interconnected health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their clients manage illnesses and health risks, as well as promote health and wellbeing.

For example, electronic health records store the history of a patient's diagnoses, medications, laboratory values, and treatment plans [1-3]. Wearables collect granular sensor measurements of various neurophysiological body functions over time [4-6]. Intensive care units (ICUs) monitor disease progression via continuous physiological measurements (eg, electrocardiograms) [7-10]. As a result, patient data in digital medicine are regularly of longitudinal form (ie, consisting of health events from multiple time points) and thus form patient trajectories. Analyzing patient trajectories provides opportunities for more effective care in digital medicine [2,7,11]. Patient trajectories encode rich information on the history of health states that are also predictive of the future course of a disease (eg, individualized differences in disease progression or responsiveness to medications) [9,10,12]. As such, it is possible to construct patient trajectories that capture the entire disease course and characterize the many possible disease progression patterns, such as recurrent, stable, or rapidly deteriorating disease states (Figure 1). Hence, modeling the patient trajectories allows one to build robust models of diseases that capture disease dynamics seen in patient trajectories. Here, we replace disease models with data from only a single or a small number of time points by disease models that account for the longitudinal nature of patient trajectories, thus offering vast potential for digital medicine. Several studies have previously introduced artificial intelligence (AI) in medicine for practitioners [13,14].

The doctor can therefore fall back on an intelligent and automated appointment management and concentrate on the personal exchange and service for the patients. In medical treatment, digital technology can be used in a wide variety of scenarios: Screening treatments can be used for the early detection of breast cancer which is a benefit from digital applications. Here, patient-specific data on the previous history and habits can be recorded. Enriched with scientific data, the application creates a risk profile and makes suggestions for routine control.

John Halamka, M.D., president, Mayo Clinic Platform, and Paul Cerrato, senior research analyst and communications specialist, Mayo Clinic Platform, wrote this article. The FDA's approach to software as a medical device (SaMD) has been evolving. In 2018, IDx-DR, a software system used to improve screening for retinopathy, a common complication of diabetes that affects the eye, became the first AI-based medical device to receive US Food and Drug Administration clearance to "detect greater than a mild level of … diabetic retinopathy in adults who have diabetes." To arrive at that decision, the agency not only reviewed data to establish its safety, it also took into account prospective studies, an essential form of evidence that clinicians look for when trying to decide if a device or product is worth using. The software was the first medical device approved by the FDA that does not require the services of a specialist to interpret the results, making it a useful tool for health care providers who may not normally be involved in eye care. The FDA clearance emphasized the fact that IDx-DR is a screening tool not a diagnostic tool, stating that patients with positive results should be referred to an eye care professional.

Scientists are tasking a language-processing Artificial Intelligence (AI) with detecting and diagnosing the early signs of language-associated cognitive impairments in people with failing livers. In their findings, the researchers report finding evidence that this cognitive function is likely to be restored following a liver transplant. In their paper, published in the journal npj Digital Medicine (formerly Nature Digital Medicine), the researchers explained how they used natural language processing (NPL) to evaluate electronic message samples from patients with chronic liver failure. This disease is associated with transient cognitive abnormalities. These include diminished attention spans, loss of memory, and a reduced ability for an individual to detect and respond to their surroundings.

Technology is changing how we practice medicine. Sensors and wearables are getting smaller and cheaper, and algorithms are becoming powerful enough to predict medical outcomes. Yet despite rapid advances, healthcare lags behind other industries in truly putting these technologies to use. A major barrier to entry is the cross-disciplinary approach required to create such tools, requiring knowledge from many people across many fields. We aim to drive the field forward by unpacking that barrier, providing a brief introduction to core concepts and terms that define digital medicine. Specifically, we contrast "clinical research" versus routine "clinical care," outlining the security, ethical, regulatory, and legal issues developers must consider as digital medicine products go to market. We classify types of digital measurements and how to use and validate these measures in different settings. To make this resource engaging and accessible, we have included illustrations and figures ...

Monday, December 3, Rockville, MD - Insilico Medicine, one of the leaders in artificial intelligence for drug discovery, biomarker development, digital medicine, and aging research announced today the publication of its recent paper titled "Artificial Intelligence for Aging and Longevity Research: Recent Advances and Perspectives" in Ageing Research Reviews, one of the highest-impact journals in the field. The paper introduces recent advances in deep learning for aging research and provides fair insight into the field. The emergence of the longevity biotechnology industry has brought many biotech and pharma companies and academic research institutions to the longevity landscape, and now one of the key trends accelerating the field is recent advances in artificial intelligence. "Insilico Medicine is dedicated to extending human longevity. We came up with several very important realizations. First, age is one of the most abundant biological features, and when your data looks like Swiss cheese, age is present. Second, Deep Learning (DL) age predictors are a great way to integrate previously incompatible data types, such as videos and blood test results. Third, the generation of new biological data using Generative Adversarial Networks (GANs), with age as a generation condition, is a great way to produce high-quality synthetic data. Also, it is possible to view aging as a staged disease to get a holistic view of the biological process on both tissue-specific and systemic levels, which makes the Deep Neural Networks (DNNs) more interpretable, builds causal graphs, and identifies biological targets. Moreover, it is possible to train the DNNs on age and retrain the model on specific diseases. Also, it is possible to use biological aging clocks to personalize immunotherapies and vaccinations and to identify new ways to improve response rates. The paper outlines these realizations and presents a way to accelerate aging research using AI technologies", said Alex Zhavoronkov, Ph.D., founder and CEO of Insilico Medicine, who led the study.

Amid the country's growing substance abuse crisis, last year the FDA cleared reSET, a mobile app that tracks substance use, cravings, and social triggers to treat dependency on alcohol, cocaine, and cannabis. The FDA's clearance makes reSET one of the first prescription "digital therapeutics"--an emerging class of evidence-based interventions that are predominantly driven by software rather than drugs. Andy Coravos is is the CEO of Elektra Labs and a member of the Harvard-MIT Center for Regulatory Science. Earlier this year, digital medicine company Akili Interactive announced that its video game for children with ADHD demonstrated a statistically significant improvement in a randomized, controlled clinical trial. That milestone paves the way for what could be the first prescription video game.