An Introduction to Emerging and Evolving World of Digital Medicine
Technology as we all know is rapidly changing the world. While other industries have embraced technology at a rapid pace, healthcare lags due to multiple reasons. One key reason being regulatory environment that tends to slow progress as health authorities are striving to minimize any risks of adverse outcomes. Digital medicine holds great promise in terms of improvement of medical measurement, diagnosis and treatment. Developing digital medicine tools is a challenging and intensive process as it involves expertise from multiple disciplines viz. engineering, technology, ethics, health care providers and payers.
The process gets compounded as they speak different languages, follow different standards, have different expectations and experiences. The COVID-19 pandemic has accelerated digital medicine.
While the topic itself is very extensive and information is rapidly changing, the attempt of the author will be to provide an overview and some examples and it’s in no way comprehensive or all inclusive.
What is Digital medicine?
Digital medicine describes a field, concerned with use of technologies as tools for measurement, and intervention in the service of human health. Such technologies/ products are driven by high-quality software and hardware that support health research and practice of medicine. The use of such technologies could be in many facets including diagnosis, treatment, recovery, prevention of diseases and health promotion across the population. Digital medicine products can be used independently or in combination with pharmaceuticals, biologics, medical devices or other products for optimal care and outcomes. One of the key impacts of such products or tools is improved patient centricity. The providers on the other hand get access to intelligent and accessible tools that can address a wide range of conditions through high-quality, safe, effective measurements, and data-driven interventions. Such tools have application both in health research and in clinical care.
Digital intervention products can be broadly categorized into three types – i. measurement products;ii. Intervention products; and iii. Combination products that both measure and intervene. Digital measurement products could include digital biomarkers, electronic clinical outcome assessments and tools that measure adherence to therapy and safety. Digital health products are excluded from Digital medicine.
Digital measures in clinical care – there are many examples of such measures for recovery (post-surgery recovery and rehabilitation), performance, and treatment selection, for safety monitoring (e.g. digital fall detection systems for elderly and frail patients), treatment adherence (e.g. ingestible sensor embedded in a medication that, when it interacts with stomach acid, transmits to a patch sensor worn overthe abdomen, monitoring when a pill was taken – used under limited circumstance and the only approved drug combined with a digital ingestion tracking system, Ability MyCitein the US) and multimodal data integration (combining data from different sources to improve clinical decision-making and support data-driven medicine).
Intervention products include digital therapeutics and connected implantable (e.g. an insulin pump used to manage Diabetes). Digital therapeutics deliver well studied therapeutic interventions to patients that are driven by high-quality software to prevent, manage or treat a medical condition or disease. They can be used independently or along with a medication, device or other therapies.
"Artificial intelligence (AI) has recently surpassed human performance in several domains, and there is great hope that in healthcare,AI may allow for better prevention, detection, diagnosis, and treatment of disease.
An interesting example of a combination product is using continuous glucose monitors (CGM as it is commonly referred to) for patients that can share data with the health care provider using a companion app. Interestingly the level of human involvement may vary in the cycle between measurement and intervention. At one end of the spectrum, there is human involvement e.g. a doctor makes a diagnosis based on a ECG reading off a smartphone. At the other is a more closed-loop system – an example is the recently developed “artificial pancreas” that combines CGM with a insulin pump and a computer-controlled algorithm that allows the system to automatically adjust the delivery of the right dose of insulin to reduce high blood sugar levels and minimize risk of low blood sugar levels.
Across therapeutic areas and technologies, digital medicine solutions can address weaknesses of existing solutions, and can bring more patient-friendly packages.Digital measures are also used in clinical research to better monitor patients and more efficiently assess safety and efficacy of interventions studied.
Digital medicine vs. Digital wellness or Digital health
In the same way as wellness products differ from those used in medicine, digital medicine differs from digital wellness. Digital wellness is used to describe products that consumers use to measure physical activity or sleep quality as they can influence their personal well-being. This could include apps or wearable sensors (e.g. Fitbit). These are typically consumer-facing and not used in clinical care of patients as they may not be well-studied/tested, validated or fully verified. At times, however,when appropriate such tools can be utilized in clinical research, after appropriate validation and verification.
Artificial Intelligence and Machine learning- Oh My!
Artificial intelligence (AI) has recently surpassed human performance in several domains, and there is great hope that in healthcare,AI may allow for better prevention, detection, diagnosis, and treatment of disease. Hence AI and Machine learning and their application in medicine is another hot topic in recent years. AI has played a significant role in enabling digital medicine products. While traditional health measures represent a snapshot in time (e.g. a laboratory value, an image from a diagnostic test, a blood pressure reading etc.), connected technologies can offer a longitudinal and highly personalized window into human health. The FDA is currently considering several products that use AI in healthcare.
Conclusion
Technology is transforming many industries, though Healthcare industry lags due to many reasons, is catching up especially as a consequence of the COVID-19 pandemic. Despite many challenges including the fact that its development is a complex and intensive process, requiring collaboration of many domains / experts, Digital Medicine can transform healthcare, supporting better disease prevention, diagnosis and treatment of medical conditions or disorders. It could not only transform healthcare delivery but also the experience of the stakeholders especially patients. There are many examples of Digital medicine tools that are useful for measurement and intervention or a combination of purposes that have been either developed or introduced into clinical care or health research. Many more promising tools are under development including those that leverage AI or Machine learning.
Disclaimer: The views and opinions expressed in this article are those of the author in his personal capacity based on experience and research and do not represent in any way the views or opinions of his current or past employers. This article is for basic educational purposes only.
The process gets compounded as they speak different languages, follow different standards, have different expectations and experiences. The COVID-19 pandemic has accelerated digital medicine.
While the topic itself is very extensive and information is rapidly changing, the attempt of the author will be to provide an overview and some examples and it’s in no way comprehensive or all inclusive.
What is Digital medicine?
Digital medicine describes a field, concerned with use of technologies as tools for measurement, and intervention in the service of human health. Such technologies/ products are driven by high-quality software and hardware that support health research and practice of medicine. The use of such technologies could be in many facets including diagnosis, treatment, recovery, prevention of diseases and health promotion across the population. Digital medicine products can be used independently or in combination with pharmaceuticals, biologics, medical devices or other products for optimal care and outcomes. One of the key impacts of such products or tools is improved patient centricity. The providers on the other hand get access to intelligent and accessible tools that can address a wide range of conditions through high-quality, safe, effective measurements, and data-driven interventions. Such tools have application both in health research and in clinical care.
Digital medicine products can be used independently or in combination with pharmaceuticals, biologics, medical devices or other products for optimal care and outcomes. One of the key impacts of such products or tools is improved patient centricity.
Digital intervention products can be broadly categorized into three types – i. measurement products;ii. Intervention products; and iii. Combination products that both measure and intervene. Digital measurement products could include digital biomarkers, electronic clinical outcome assessments and tools that measure adherence to therapy and safety. Digital health products are excluded from Digital medicine.
Digital measures in clinical care – there are many examples of such measures for recovery (post-surgery recovery and rehabilitation), performance, and treatment selection, for safety monitoring (e.g. digital fall detection systems for elderly and frail patients), treatment adherence (e.g. ingestible sensor embedded in a medication that, when it interacts with stomach acid, transmits to a patch sensor worn overthe abdomen, monitoring when a pill was taken – used under limited circumstance and the only approved drug combined with a digital ingestion tracking system, Ability MyCitein the US) and multimodal data integration (combining data from different sources to improve clinical decision-making and support data-driven medicine).
Intervention products include digital therapeutics and connected implantable (e.g. an insulin pump used to manage Diabetes). Digital therapeutics deliver well studied therapeutic interventions to patients that are driven by high-quality software to prevent, manage or treat a medical condition or disease. They can be used independently or along with a medication, device or other therapies.
"Artificial intelligence (AI) has recently surpassed human performance in several domains, and there is great hope that in healthcare,AI may allow for better prevention, detection, diagnosis, and treatment of disease.
An interesting example of a combination product is using continuous glucose monitors (CGM as it is commonly referred to) for patients that can share data with the health care provider using a companion app. Interestingly the level of human involvement may vary in the cycle between measurement and intervention. At one end of the spectrum, there is human involvement e.g. a doctor makes a diagnosis based on a ECG reading off a smartphone. At the other is a more closed-loop system – an example is the recently developed “artificial pancreas” that combines CGM with a insulin pump and a computer-controlled algorithm that allows the system to automatically adjust the delivery of the right dose of insulin to reduce high blood sugar levels and minimize risk of low blood sugar levels.
Across therapeutic areas and technologies, digital medicine solutions can address weaknesses of existing solutions, and can bring more patient-friendly packages.Digital measures are also used in clinical research to better monitor patients and more efficiently assess safety and efficacy of interventions studied.
Digital medicine vs. Digital wellness or Digital health
In the same way as wellness products differ from those used in medicine, digital medicine differs from digital wellness. Digital wellness is used to describe products that consumers use to measure physical activity or sleep quality as they can influence their personal well-being. This could include apps or wearable sensors (e.g. Fitbit). These are typically consumer-facing and not used in clinical care of patients as they may not be well-studied/tested, validated or fully verified. At times, however,when appropriate such tools can be utilized in clinical research, after appropriate validation and verification.
Artificial Intelligence and Machine learning- Oh My!
Artificial intelligence (AI) has recently surpassed human performance in several domains, and there is great hope that in healthcare,AI may allow for better prevention, detection, diagnosis, and treatment of disease. Hence AI and Machine learning and their application in medicine is another hot topic in recent years. AI has played a significant role in enabling digital medicine products. While traditional health measures represent a snapshot in time (e.g. a laboratory value, an image from a diagnostic test, a blood pressure reading etc.), connected technologies can offer a longitudinal and highly personalized window into human health. The FDA is currently considering several products that use AI in healthcare.
Conclusion
Technology is transforming many industries, though Healthcare industry lags due to many reasons, is catching up especially as a consequence of the COVID-19 pandemic. Despite many challenges including the fact that its development is a complex and intensive process, requiring collaboration of many domains / experts, Digital Medicine can transform healthcare, supporting better disease prevention, diagnosis and treatment of medical conditions or disorders. It could not only transform healthcare delivery but also the experience of the stakeholders especially patients. There are many examples of Digital medicine tools that are useful for measurement and intervention or a combination of purposes that have been either developed or introduced into clinical care or health research. Many more promising tools are under development including those that leverage AI or Machine learning.
Disclaimer: The views and opinions expressed in this article are those of the author in his personal capacity based on experience and research and do not represent in any way the views or opinions of his current or past employers. This article is for basic educational purposes only.
