Visiting the Future

Over the last three decades, the prevailing view of information technology strategy has been that it is a functional-level strategy that must be aligned with the firm's chosen business strategy. Even within this so-called alignment view, business strategy directed IT strategy. During the last decade, the business infrastructure has become digital with increased interconnections among products, processes, and services. Across many firms spanning different industries and sectors, digital technologies (viewed as combinations of information, computing, communication, and connectivity technologies) are fundamentally transforming business strategies, business processes, firm capabilities, products and services, and key interfirm relationships in extended business networks. Accordingly, we argue that the time is right to rethink the role of IT strategy, from that of a functional-level strategy--aligned but essentially always subordinate to business strategy--to one that reflects a fusion between IT strategy and business strategy. This fusion is herein termed digital business strategy.

We identify four key themes to guide our thinking on digital business strategy and help provide a framework to define the next generation of insights. The four themes are (1) the scope of digital business strategy, (2) the scale of digital business strategy, (3) the speed of digital business strategy, and (4) the sources of business value creation and capture in digital business strategy. After elaborating on each of these four themes, we discuss the success metrics and potential performance implications from pursuing a digital business strategy. We also show how the papers in the special issue shed light on digital strategies and offer directions to advance insights and shape future research.

https://misq.org/misq/downloads/download/editorial/581/

Digital business strategy: toward a next generation of insights

At the beginning of the artificial intelligence (AI)/machine learning (ML) era, the expectations are high, and experts foresee that AI/ML shows potential for diagnosing, managing and treating a wide variety of medical conditions. However, the obstacles for implementation of AI/ML in daily clinical practice are numerous, especially regarding the regulation of these technologies. Therefore, we provide an insight into the currently available AI/ML-based medical devices and algorithms that have been approved by the US Food & Drugs Administration (FDA). We aimed to raise awareness of the importance of regulatory bodies, clearly stating whether a medical device is AI/ML based or not. Cross-checking and validating all approvals, we identified 64 AI/ML based, FDA approved medical devices and algorithms. Out of those, only 29 (45%) mentioned any AI/ML-related expressions in the official FDA announcement. The majority (85.9%) was approved by the FDA with a 510(k) clearance, while 8 (12.5%) received de novo pathway clearance and one (1.6%) premarket approval (PMA) clearance. Most of these technologies, notably 30 (46.9%), 16 (25.0%), and 10 (15.6%) were developed for the fields of Radiology, Cardiology and Internal Medicine/General Practice respectively. We have launched the first comprehensive and open access database of strictly AI/ML-based medical technologies that have been approved by the FDA. The database will be constantly updated.

/pdf/the-state-of-artificial-intelligence-based-fda-approved-3wybhhjw9d.pdf

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

Brain-machine interfaces hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical brain-machine interfaces have not yet been widely adopted, in part, because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth brain-machine interface system. We have built arrays of small and flexible electrode “threads,” with as many as 3072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: The package for 3072 channels occupies less than 23×18.5×2 mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to brain-machine interface has unprecedented packaging density and scalability in a clinically relevant package.

/pdf/an-integrated-brain-machine-interface-platform-with-n7fyapdhlq.pdf

An Integrated Brain-Machine Interface Platform With Thousands of Channels

Neurological disorders such as Alzheimer's disease, stroke, and brain cancers are difficult to treat with current drugs as their delivery efficacy to the brain is severely hampered by the presence of the blood-brain barrier (BBB). Drug delivery systems have been extensively explored in recent decades aiming to circumvent this barrier. In particular, polymeric nanoparticles have shown enormous potentials owing to their unique properties, such as high tunability, ease of synthesis, and control over drug release profile. However, careful analysis of their performance in effective drug transport across the BBB should be performed using clinically relevant testing models. In this review, polymeric nanoparticle systems for drug delivery to the central nervous system are discussed with an emphasis on the effects of particle size, shape, and surface modifications on BBB penetration. Moreover, the authors critically analyze the current in vitro and in vivo models used to evaluate BBB penetration efficacy, including the latest developments in the BBB-on-a-chip models. Finally, the challenges and future perspectives for the development of polymeric nanoparticles to combat neurological disorders are discussed.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202003937

Development of Polymeric Nanoparticles for Blood-Brain Barrier Transfer-Strategies and Challenges.

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Visiting the Future

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References

Digital business strategy: toward a next generation of insights

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

An Integrated Brain-Machine Interface Platform With Thousands of Channels

Development of Polymeric Nanoparticles for Blood-Brain Barrier Transfer-Strategies and Challenges.

Bioprinting for the Biologist.