Transforming Healthcare with Artificial Intelligence

By Al Naqvi
Executive Director
Society of Artificial Intelligence
for Medicine and Healthcare
President
American Institute of Artificial Intelligence




They were tiny, inconsequential, and dwarfed by the enormous giants that walked the earth during the Jurassic era. Waiting for their time to come, mammals fought hard and won the battle of survival, and then emerged to dominate the world for the next 65 million years. Like mammals, the artificial intelligence community worked diligently and determinedly through the ups and downs of the artificial intelligence field. Committed to doing something spectacular – and ignoring the financially rewarding rise of the unintelligent technologies –  they patiently persevered in their labs and research centers. And now their patience is paying off as their time has come. Welcome to the dawn of artificial intelligence! The coming decades will belong to this technology as it transforms our world and the greatest impact it will make is in the healthcare industry.

The Two Goals

Simplifying and capturing the formidable complexities of healthcare and zooming in on what can dramatically improve and revolutionize it, we should focus on two fundamental goals: 1) Finding new cures (therapeutic and/or diagnostic), and 2) Applying known cures effectively, efficiently, and for all those who can benefit from them. And artificial intelligence is having an impact on both.

Finding New Cures

One of the most silent and often ignored problems of our times is our stagnation in finding new cures. Unlike climate change or jobs, this issue somehow doesn’t climb to the political consciousness, yet it is one of the most consequential problems of our times. The new drug pipeline appears to be as ailing as the diseases it is trying to heal. Despite a 10-fold increase in investment, the results are miserable (Coller and Califf, 2009). There are staggering failure rates of 97%, even before projects reach the preclinical stage (Sams-Dodd, 2013) and 90% after Phase I, are the industry standards (Biotechnology Innovation Organization (BIO) et al., 2016). The proverbial “Valley of Death” concept captures the disconnect between the upstream and downstream drug discovery process and the “valley” requires complex navigation (Rai et al., 2008). Whether failure is due to toxicity, or efficacy (Sams-Dodd, 2013), or due to cost as a function of time and risk (DiMasi et al., 2009), or other reasons like managerial or organizational issues (Buonansegna et al., 2014), the overriding concern is that the human civilization stands naked and hopeless without the prospect of new cures.

With the advent of artificial intelligence, we can expect to close the gap. Specifically, the solutions are coming in the following areas:

1. More efficient and smarter basic science and preclinical models
2. Smarter devices for preclinical (pattern recognition etc.) 
3. Genomics and molecular medicine
4. Forensic analysis of clinical trials data (what failed, why)
5. Sharing of clinical information to help develop new therapeutic options
6. Finding new patterns in existing clinical data 
7. Enhanced predicative ability to determine toxicity, efficacy etc. at early stages of development
8. Integrating various aspects of new drug development such as identified by Mullane et al. (Mullane et al., 2014)

Even cancer, which is not a single disease but potentially hundreds or even thousands of diseases, can be considered as a computational problem that can be solved by artificial intelligence (Tenenbaum and Shrager, 2011).

Making Existing Cures More Efficient and Effective, For All

Now enter the clinical side, where artificial intelligence is improving the current standards of care. Just because we have a cure doesn’t mean it is being applied efficiently and effectively for all those who need it. Artificial Intelligence is now transforming clinical healthcare by:

1. Improving the diagnostic speed and accuracy by analyzing data and observing never-before-seen patterns. This includes not only enhancing the ability to save lives by improving the speed and accuracy of diagnostics (for example Sepsis, a major killer), but also by artificial intelligence systems learning the ability to read scans.
2. Artificial Intelligence systems are being developed and tested for population health management, patient tracking, condition management, hospital workflow management, advanced analytics, and the list goes on and on.
3. Social robots, care bots, and healthcare management bots are being developed to help in providing care, patient monitoring, and doing patient or hospital chores.
4. The efficiency of hospitals is being increased by using artificial intelligence for claims management, coding and reimbursement.
5. In the future, we can expect healthcare kiosks and freestanding autonomous clinics providing primary care.
6. On the behavioral health side, we are observing a tsunami of new solutions providing various behavioral therapies and interventions. This area will greatly improve access and diagnostic consistency across behavioral health.

And this is only the beginning. As a civilization, we must challenge ourselves to conquer disease and suffering. Anyone who is, or has a family member, suffering from a disease like cancer knows that the speed and accuracy of finding cures and timely and effective interventions matter. With artificial intelligence, our hopes stand renewed.

The author will be presenting about the above developments at the 22nd Annual Medical Technologies: A Frost & Sullivan Executive MindXchange.

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About AL NAQVI

Al Naqvi is the Executive Director of  The Society of Artificial Intelligence in Medicine and Healthcare and the Chief Executive Officer of the American Institute of Artificial Intelligence. He is also Editor-in-Chief of the Artificial Intelligence AI post www.aipost.com. 

Formerly, he was the Chief Financial Officer of a major healthcare/hospital system and prior to that a consultant in the drug development industry with a special focus on molecular medicine and nuclear medicine. Prior to that, he was Vice President of a Fortune 500 company and a technology entrepreneur. His doctorate thesis is on Artificial Intelligence Governance and his Machine Learning training is from Stanford University. ________________________________________________________________

References

Biotechnology Innovation Organization (BIO) et al. (2016) Clinical Development Success Rates 2006-2015. (June), . [online]. Available from: https://www.bio.org/sites/default/files/Clinical Development Success Rates 2006-2015 - BIO, Biomedtracker, Amplion 2016.pdf.
 
Buonansegna, E. et al. (2014) Pharmaceutical new product development: why do clinical trials fail? R&D Management. [Online] 44 (2), 189–202. [online]. Available from: http://doi.wiley.com/10.1111/radm.12053.
 
Coller, B. S. & Califf, R. M. (2009) Traversing the valley of death: a guide to assessing prospects for translational success. Science translational medicine. [Online] 1 (10), 10cm9. [online]. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2879158&tool=pmcentrez&rendertype=abstract.
 
DiMasi, J. A. et al. (2009) Trends in Risks Associated With New Drug Development: Success Rates for Investigational Drugs. Clinical Pharmacology & Therapeutics. [Online] 87 (3), 272–277. [online]. Available from: http://dx.doi.org/10.1038/clpt.2009.295\npapers3://publication/doi/10.1038/clpt.2009.295.
 
Mullane, K. et al. (2014) Translational paradigms in pharmacology and drug discovery. Biochemical Pharmacology. [Online] 87 (1), 189–210. [online]. Available from: http://dx.doi.org/10.1016/j.bcp.2013.10.019.
 
Rai, A. K. et al. (2008) Pathways Across the Valley of Death: Novel Intellectual Property Strategies for Accelerated Drug Discovery. Yale Journal of Health Policy, Law, and Ethics. 81. [online]. Available from: http://www.worldcat.org/oclc/809548427.
 
Sams-Dodd, F. (2013) Is poor research the cause of the declining productivity of the pharmaceutical industry? An industry in need of a paradigm shift. Drug Discovery Today. [Online] 18 (5–6), 211–217. [online]. Available from: http://dx.doi.org/10.1016/j.drudis.2012.10.010.
 
Tenenbaum, J. M. & Shrager, J. (2011) Cancer: A Computational Disease that AI Can Cure. AI Magazine. [Online] 32 (2), 14–26. [online]. Available from: http://www.aaai.org/ojs/index.php/aimagazine/article/view/2345.

9 Healthcare Predictions For 2017

By Reenita Das
Partner and Senior Vice President
Transformational Health
Frost & Sullivan






Every year at Frost & Sullivan, the Transformational Health team brainstorms top predictions for the year ahead. 2017 will definitely continue to be a year of tumultuous uncertainty and turbulence. But amidst this uncertainty, we know for a fact that technology will continue to flourish and will have an unprecedented impact on healthcare in terms of building some of the foundation blocks towards a connected home and healthcare ecosystem.

The following are our nine top predictions for healthcare for 2017:

Strong Push Toward Price Control And Transparency Measures Around Drugs

Public and political pressure on the control of surging drug prices, globally, will compel health authorities to bring transparency measures around drugs pricing, especially for some of the diabetes and cholesterol medicines where more low-cost generic competition is gaining market acceptance.

Blockchain Becomes One Of The Most Important Technologies In The Healthcare Industry

With the potential to change how healthcare information is stored, shared, secured and paid for, blockchain technologies have immense potential to tackle some of the biggest challenges in healthcare information management. Companies like Gem Health are among the few companies currently advocating the use and benefits of such a platform.

Artificial Intelligence (AI) Transforms Medical Imaging Informatics

As more and more experts and healthcare professionals find the usability of these AI systems as decision support tools and not decision makers, uptake of AI-enabled clinical decision support tools is expected to increase in the coming years. More particularly during 2017, AI will play a big role in diagnostic imaging by complementing radiologists with advanced interpretation and imaging informatics supports.

Deployment Of More Sophisticated Outcomes-Based Compensation Care Models

To date, the majority of outcome-based compensation models are, in reality, performance modifiers built on top of legacy fee-for-service reimbursement schemes. In 2017, we will begin to see more fully formed schemes that focus on patient support across the care continuum. As such, healthcare providers are in dire need of the right technologies and tools to help them effectively deploy and coordinate patients, personnel and infrastructure.

Apple To Enter Clinical Healthcare

Healthcare has been a big focus for Apple in the past two years, and the company is committed to creating more clinical actionable products and services. Last August, Apple acquired medical records startup Gliimpse in order to broaden its presence in the personal healthcare information management market and complement existing solutions; these include HealthKit, CareKit and ResearchKit. This marks a tangible shift for Apple toward more clinically oriented solutions.

Venture Capital (VC) Healthcare Investment Will Have A Record Year

An ideal confluence of events is poised to make 2017 a banner year for VC investment in healthcare. Strains on healthcare spending, the global recession, tightening regulatory oversight and other factors have put a stranglehold VC dollar flow over the past five years, particularly for very early-stage companies in the healthcare industry. However, with the maturation of certain emerging technologies, policy changes to the FDA and access to cash, it is expected there will be a resurgence in funding for new healthcare technologies.

The Digital Health Toolkit Comes To Behavioral Health

Digital health coaching platforms and wellness programs with proven behavioral therapies will find their way as an efficient alternative to post-care settings and rehabilitation centers. Innovative online patient engagement platforms are capable of capturing tailored information on lifestyle and behavioral health. This is based on health risks data that have a white space opportunity to provide patient risk classification solutions to make precision medicine a holistic approach.

With a view to avoid future excessive treatment costs, payers will encourage healthier lifestyles among members; they are likely to provide them with wearables and incentives for attaining specific health goals as motivation. In the New Year, wellbeing programs will become a central, critical business imperative, necessary for optimizing not just the productivity and performance of employees, but also for managing the bottom line.

Point-Of-Care Diagnostic Devices Push Telehealth Beyond Video Conferencing

Consumers will play a greater role in driving the uptake of point of care testing. In vitro diagnostic device (IVD) manufacturers will invest in digital strategy. This is in order to make their business models patient-centric with consumer-friendly devices, embed remote connectivity features for real-time access to data, and simplifying sample collection process.

Consumer Will Be The New King in Healthcare Decision Making

The concept of consumerism has been making inroads into the healthcare industry and is advancing proportionally with the shifting industry focus from volume to value-based care delivery models. With this thriving consumer engagement movement, consumers are more receptive to information and as they want to actively participate in their healthcare treatment during, pre- and post-care. Technology is also playing a pivotal role in this paradigm shift with connected health products such as wearables, telehealth, artificial intelligence
and others.

This article was written with contributions from the Visionary Healthcare Program team and Venkat Rajan, Global Director for Frost & Sullivan’s Transformational Health Practice.

Time to Get Real: Quantifying Health Outcomes With Real Life Data

                       

By Deborah Kilpatrick, Ph.D.             Murali Doraiswamy, M.D.
Chief Executive Officer                    Professor of Psychiatry and Medicine
Evidation Health                             Duke University Health System

Given the widespread adoption of mobile technologies and digital health apps by patients, we now have a view into the continuous patient journey like never before. We can now “quantify real life” of patients and measure health outcomes beyond traditional clinical trials, at scale. And in this digital era of medicine, we have more robust analytical tools that can sift through massive, complex datasets faster and more reliably. Whether it is in Type 2 diabetes or multiple sclerosis or heart failure, the ability to quantify outcomes from real life patient data is going to change the way we think about the volume-to-value transformation.

Therapeutics industry leaders can now address some direct drivers of the historical gap between trial efficacy and post-launch effectiveness with solutions that enable:

1. Access to broader connected populations
2. Collection of novel real life data from patients
3. Quantification of real life outcomes

1. Access to Connected Populations
 
Clinical development strategies for drugs and devices include fundamentals ranging from recruiting eligible patients to capturing data at various points in time according to a pre-specified protocol. None of these steps go away in the digital era, but the tactics for getting them done are undergoing truly revolutionary change.[1],[2]

Digital technologies provide new channels for accessing target patient populations. In connecting with patients outside of traditional clinical settings, we are able to recruit patients for studies much faster, discover patterns across segments, and support patients in their everyday lives.[3]

Equally important, the benefits are not limited to the number of patients recruited or the improved efficiencies of the process. Digital technologies fundamentally expand the datasets we can use to quantify outcomes in the real world. That means we can more accurately correlate outcomes with patients’ daily lives and behaviors.

2. Collection of Novel Real Life Data

The most important expansion of our clinical development data universe is arguably our new ability to continuously and passively measure patient behaviors upon informed consent. For example, tracking sleep, physical activity, social media activity, and wireless sensor data all enhance the context available for analysis.[4]

In the near term, this new information can shed light on the efficacy-effectiveness gap between phase III trial results and what happens in post-launch settings. When combined with medical information including EHRs, claims data, and genomics, this new understanding of how patient behaviors drive health outcomes creates a direct path to precision medicine solutions.

3. Quantification of Real Life Outcomes

Gathering novel data from more people, more efficiently, is only helpful if it leads to scientifically valid conclusions that prove outcomes. We have always known that patient behaviors directly influence symptomology and disease progression/regression in many therapeutic areas, but quantifying the impact has traditionally been an elusive goal. That has changed.[5]

Therapeutic areas that are benefiting most from this new approach are those where patient behaviors outside the clinic walls disproportionately impact health outcomes. In our experience to date, the use cases for quantifying how real life patient behaviors drive health outcomes are now quite broad and accessible. For example:

• Segmenting populations by behaviors: identifying super-responders and non-responders to a medication adherence mobile app in cardiometabolic disease
• Evaluating "Services around the Pill": optimizing digital health interventions to impact vaccination patterns and reduce infection rates during flu season
• Characterizing real life quality of life improvement: measuring data reflecting productivity and daily symptom improvement in depression and anxiety
• Identifying new digital biomarkers for disease status based on quantified behaviors: establishing links between daily activity patterns and flares in multiple sclerosis

Pharma Company Puts It All Together to Quantify Impact

Connecting with patient populations, collecting continuous behavioral data, and quantifying health outcomes on large behavior datasets all benefit from digital tools -- but the greatest benefit is realized when the three tactics are combined.

For example, a top global pharma company worked with Evidation Health with the goal of improving patient adherence to medication and lifestyle modification in the diabetes market. The project started by connecting with 300,000 patients and segmenting that population into clusters. The platform collected real life behavioral data across well over 6 months of observation and linked relevant behavioral activity (diet, sleep, etc.) to medical adherence.

Ultimately, this enabled a top global pharma company to quantify health outcomes and leverage behavior-driven insights for dynamic intervention targeting.

We might not have imagined a decade ago that we’d be here so quickly. But suddenly we find ourselves able to quantify health outcomes like never before, in settings we never imagined, in populations we might not have ever reached—in their real lives. This is indeed an idea whose time has come.

To learn more about how healthcare companies are using Evidation Health’s Real Life Study Solution to quantify health outcomes in the digital era of medicine, follow @evidation.

PMD is a scientific advisor to Evidation Health and has served as an advisor to leading businesses, advocacy groups and government agencies.  

[1] Rosa C, Campbell AN, Miele GM, Brunner M, Winstanley EL. Using e-technologies in clinical trials. Contemp Clin Trials. 2015;45(Pt A):41-54.

[2] Juusola JL, Quisel TR, Foschini L, Ladapo JA. The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis. J Med Internet Res. 2016;18(6):e127.

[3] Kumar S, Oley L, Juusola JL. Efficiency of Virtual Recruitment Methods for Broad and Specific Study Populations. 38th Annual North American Meeting of the Society for Medical Decision Making, October 23 - 26, 2016.

[4] Pourzanjani A, Quisel TR, Foschini L. Adherent Use of Digital Health Trackers Is Associated with Weight Loss. PLoS ONE 11(4): e0152504.

[5] Rock Health. The Emerging Influence of Digital Biomarkers. 2016. Available at https://rockhealth.com/reports/the-emerging-influence-of-digital-biomarkers-on-healthcare/.
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Deborah Kilpatrick is the Chief Executive Officer of Evidation Health. Prior to this role, she served as the Chief Commercial Officer of genomic diagnostics company CardioDx. Earlier in her career, Deborah held multiple leadership roles at Guidant Corporation, including Research Fellow, Director of R&D, and Director of New Ventures in the Vascular Intervention Division. She serves on the Georgia Tech Advisory Board and is a Fellow of the American Institute of Medical and Biological Engineering. Deborah is a co-founder of the MedtechVision Conference, now held annually in Silicon Valley and has received many awards including 100 Women of Influence in Silicon Valley. She holds BS, MS and PhD degrees in mechanical engineering with a bioengineering focus from Georgia Tech.

Murali Doraiswamy is a scientific advisor to Evidation Health and has served as an advisor to leading businesses, advocacy groups and government agencies.  Doraiswamy is a leading physician scientist in the areas of brain health and personalized medicine at Duke Medicine where he is a Professor in the Division of Translational Neuroscience and Director of the Neurocognitive Disorders Program in Psychiatry. He also serves as a member of the Duke Institute for Brain Sciences and the Duke Center for Personalized Medicine. Doraiswamy has served as an advisor to leading government agencies, advocacy groups and businesses, and received many awards including a special Congressional recognition.  He is the coauthor of a popular book, The Alzheimer's Action Plan.
 

Does Healthcare Understand the ‘On Demand’ Consumer?

By Pieter Nota
Executive Vice President,
CEO Personal Health Businesses
Royal Philips





The age of the ‘on demand’ consumer has inspired a lot of discussion in recent years. Industries such as retail, hospitality, media, government and education have all undergone a sharp and drastic period of change led by digital innovations. 

Obviously, they are not the only ones. In healthcare, the world is changing too: the appetite for digital services is growing and so is the need for reliable information. 

“Is bronchitis contagious?” and “How many calories should I eat” were both top Google health searches between January and November last year. Last year around 1 in 20 Google searches were health-related. In 2015, more than 3 billion downloads of mHealth apps have been estimated for the main app stores, allowing people to self-monitor disease conditions and adjust their lifestyles. Gradually, we are becoming empowered to know more about our own health – and act on it.

Understanding the challenges
Does healthcare understand this shift? Communication with friends and family is fast and frictionless today; people can do business, shop and put themselves through a university degree course online. They can now manage their finances seamlessly via phone apps; using virtual reality they can visit and examine the world’s most famous artworks.

Soon, they will ask why healthcare isn’t being delivered the same way.

From one perspective, the challenges embedded in the industry are broad and deep, and the limitations revolve around access to and free movement of data. Medical information is sensitive and often struggles to flow around the complicated and tangled bureaucracies constructed around healthcare services in many countries.

This lack of access to data and poor care co-ordination has worked to the detriment of patients and has inhibited health outcomes. For example, despite steady progress towards universal medical records, a vast majority of patients still have to repeat the same basic information to multiple healthcare professionals, according to the Future Health Index1, a survey of 25,000 patients which was commissioned by Philips. Most say they have also experienced repeatedly taking the same tests, delaying treatments and burning up valuable time. 

These are big challenges for an industry negotiating digital change and it is not a unique problem.

Beyond traditional models 
Healthcare delivery has reached the same juncture as taxis, broadcasting and hospitality did with the arrivals of Uber, Netflix and Airbnb. Broadcasters used to decide what people watched and when; now streaming services like Netflix allow viewers to choose and enjoy their favorite movies and TV series in one sitting. As a result, streaming services are now a vital part of all traditional broadcasters’ online offerings. Whole industries have been transformed by the ‘on demand’ consumer and quickly overtaken by innovations.

People can now rent out their own homes to visitors as opposed to taking the traditional route and booking a hotel or a bed and breakfast. Airbnb tapped into consumer appetite for different experiences and more personalized accommodation anywhere in the world and as a result disrupted the hospitality industry.

I am not suggesting that healthcare is standing still. Research suggests consumers want more connected healthcare. Over half (57%) of patients surveyed for the Future Health Index (aged 18-34) said they owned or used at least one health monitoring device, with 71% saying they would be interested in scheduling appointments online and 66% interested in receiving medical test results online.

Where will healthcare go next?
The research also highlighted some fault lines: around 74% of patients actively managed their own health but 75% of doctors thought patients needed to take a more active role. There’s obviously a disconnect between what people think they are doing and what doctors are observing.

At Philips we want to narrow that gap by empowering people to take better care of themselves, using digital technologies and connectivity. At IFA 2016, we are introducing a wide range of connected personal health innovations that empower consumers to stay healthy, live well and enjoy life.

Empowering consumers to engage in their health and take control of their lifestyle choices is precisely what Philips’ connected personal health programs do. Data from our connected health devices – such as Philips’ health watch, digital blood pressure monitors and body analysis scale – supports the small lifestyle changes that make a big difference.

Data accrued from connected devices which monitor patients, sensors in hospital rooms, wearables and lab equipment will ultimately transform healthcare in a huge way and usher in a new era of care delivery, reducing costs and saving time. 

Soon consumers will want to access their lab results via their smart phones within minutes of leaving a medical center; they will want their data to be accessed on multiple devices and freely exchangeable, and they will want healthcare delivered from the comfort of their own homes.

And as care delivery moves that way, consumers will finally be able to add real-time, connected healthcare to the other digital services they now take for granted and use every day.

[1] More than 2,600 healthcare professionals and 25,000 patients were questioned in Australia, Brazil, China, France, Germany, Japan, The Netherlands, Singapore, South Africa, Sweden, UAE, UK and US. 

Pieter joined Philips in 2010 as CEO of Philips Consumer Lifestyle. Prior to that he was on the Board of Management as Chief Marketing & Innovation Officer at Beiersdorf AG (a.o. Nivea), based in Hamburg, Germany. He started his career at Unilever in the Netherlands as a Brand manager in 1990, rising to Marketing Director and Member of the Executive Board of Unilever Poland and Germany, where he worked until 2005.

Pieter was born in the Netherlands in 1964. He is married with two children and holds a degree in Business Administration from Erasmus University in Rotterdam, the Netherlands. Follow Pieter on: LinkedIn

The Face of Health Care

By Ingrid Blair 
Vice President, Business and Marketing 
3M Drug Delivery Systems Division





We’re constantly told that the face of health care is changing, but what exactly does that changing face look like and what does it mean for the future? As the population ages, that face probably has a few more lines and wrinkles, but it’s also a wiser and more inquisitive face when it comes to health matters. ‘Take two aspirin and call me in the morning’ isn’t going to cut it for this face. And when we are talking about serious diseases, such as Chronic Obstructive Pulmonary Disease (COPD), the faces of patients and their caregivers want to be as informed as possible. 

Of course, it’s one thing to have the information; it’s an entirely different matter to put that information into action to achieve optimal results. That’s where health care providers and industry can come together – uniting technological advancement with improved communications to overcome obstacles to effective treatment.  

At 3M, we apply science in collaborative ways to overcome such obstacles – developing new solutions that create healthier populations. One recent project we’ve been working on is treating the unmet needs in the respiratory drug delivery market to improve quality of life for those affected with COPD. 

For the 65 million people worldwide¹ who are affected by this disease, it is absolutely imperative to consistently receive the right amount of medication into the correct location of a patient’s respiratory system, which could allow them to live full and productive lives. 

However, recent studies have shown that traditional devices have failed to improve patient competence and adherence, leading to an increase in complications. One study has shown that approximately 76% of pressurized Metered Dose Inhaler users make at least one mistake each time they use their device.² These mistakes range from angling the mouthpieces the wrong way, to inhaling too much of the product, to not holding their breath long enough. Similarly, approximately 94% of Dry Powder Inhaler users make critical usage errors.³ Another study has shown that around 60% of COPD patients do not adhere to their prescribed therapy.⁴ Additionally, only 25% of patients use their medications every day as prescribed.⁵

This research has made it clear that patients are struggling with current options in COPD treatment. Thankfully, through the application of innovative technologies to inhalation devices, developers have been able to engineer “intelligent” inhalers to improve patient competence and adherence. For example, 3M’s new Intelligent Control Inhaler helps improve competence by controlling the inspiratory flow rate, so that variations in breath inhalation strength do not affect dosages; additionally, it incorporates step by step on-screen instructions, to help patients use the inhaler more effectively.

As for adherence, the device will ‘connect’ with a mobile app providing real-time data for patients and doctors about device usage as well as long-term trends in inhalation breath profiles. Patients will know when they took a dose and they’ll know if they took the correct amount. No more situations where a patient gets distracted and then forgets if they were just about to take a dose or if they just got done taking one! 

From the perspective of the health care provider, communications are greatly improved as they don’t need to rely on the patient’s memory or inexact descriptions to explain how their treatment has been going. Reception of real-time data will allow for treatment plan modifications that lead to healthier outcomes. 

While millions of patients continue to struggle with diseases such as COPD, there is hope that new “intelligent” devices will improve patient competence and adherence through technological advancements, while real-time data sharing builds more trusted relationships between patients and their healthcare providers. The face of health care might be continually changing, but with innovative solutions in drug delivery on the horizon, that face is beginning to show a bit of a smile. 

Ingrid Blair is the Vice President for Business & Marketing of 3M’s Drug Delivery Systems Division, a recognized world leader in business and innovation.  In this role, Ingrid has global responsibility for leading business strategy, marketing, and operations for the development and supply of complex drug delivery systems solutions for global pharmaceutical customers.  Related products are developed to meet a variety of patient needs within inhalation, transdermal, microneedle and digital health segments.   

Ingrid has spent 29 years at 3M in positions of increasing responsibility in technology development, laboratory management, and global business leadership.  She is a Certified Design for Six Sigma Master Black.  She is currently a member of the Inclusion Steering Committee at 3M.  An engineer by training, Ingrid has a bachelor’s degree in Chemical Engineering from the University of Minnesota.  

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1. http://www.who.int/respiratory/copd/burden/en/
2. http://www.sciencedirect.com/science/article/pii/S0954611107004477
3. http://www.sciencedirect.com/science/article/pii/S0954611107004477
4. https://www.ncbi.nlm.nih.gov/pubmed/18990964
5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2629978

Surgical Robots – Current Status and Next Generation Solutions

By Alind Sahay
Vice President
Noxilizer, Incorporated







Today, robots are present in a variety of application areas in the healthcare space – in surgery, pharmacy, rehabilitation, hospital services and many new application areas.  With orders of magnitude improvements in processing power and maturing of sensor technologies, there is a global and societal trend toward increased use of robotics. Global spending in robotics, and correspondingly, in the surgical robotics areas is expected to more than double in the next 5 years. 

The surgical robotics field is over three decades old – the first robot-assisted surgical procedure occurred in 1985 when a neurological biopsy was carried out using a PUMA 560 robotic arm.  In this article we will take a look at areas where there has been significant adoption – laparoscopic and general surgery, orthopedic surgery, spine and neurology – and explore next generation solutions that are expected to drive further growth.

In the laparoscopic surgery area, in 2016, we expect more than 700,000 robotic procedures worldwide. Clinical adoption, to date has been driven by benefits from the reduction in hand tremors, the minimally-invasive nature of the system and improved visualization.  Along the way, there have been innovations such as improved image resolution, shortened set-up time and, recently, improved visualization to identify vasculature beneath the tissue surface.   A number of studies have shown that robotic assisted surgery leads to shorter hospital stays and faster recovery times.  However, there continues to be a debate regarding the clinical benefits of robot assisted surgery.

While more recent clinical data may demonstrate clinical benefits, next generation solutions have the potential to provide step-function improvements. These solutions include Laparo-Endoscopic Single Site Surgery (LESS), Natural Orifice Transluminal Endoscopic Surgery (NOTES) and further improvements in surgical field information that could be presented through a merged visualization display.   Surgical field information will include further improvements in 3D vision, in vasculature information, improved haptic feedback, as well as cellular level information. These next generation systems have the potential to further reduce overall cost as well as improve final outcomes.  One robotic system that provides NOTES capability recently became commercially available and we expect that more Single-Site Surgery systems will become commercially available over the next 2-3 years.

In the orthopedic space, adoption has been slower – in 2016 we expect approximately 100,000 worldwide robot-assisted procedures.   In this space, there are two types of available robots – active robotic systems where the bone machining is autonomous, and passive robotic system where the robot constraints the surgeon but the machine is under the surgeon’s guidance.  Recent clinical publications from all these systems have demonstrated that component positioning and alignment, using robot assisted surgery, is statistically superior to manual surgeries.  And in a recent 2-year follow-up study using an active robotic system, there is evidence that for robotic surgeries, there is less bone loss when compared to manual surgeries. 

A significant challenge faced by orthopedic robotic systems is that the robot is only responsible for bone machining, which is one half of the surgery – the other half is the design of the orthopedic prosthesis itself.  Therefore, by integrating the development of the robotic systems and prosthesis, there may be synergistic opportunities related to system design, clinical workflow and business processes.  For example, by using a robot, it is possible for orthopedic implant companies to eliminate a significant portion of the bone preparation hardware, thereby significantly reducing cost.  Synergistic possibilities in improving the design include further reduction in invasiveness and potentially reducing overall operating time through workflow improvements.   As more long-term data is available with more recent improved systems, orthopedic robots will also demonstrate an improved quality of surgery.  In the spine space, recent retrospective and prospective clinical studies have shown a significant reduction in complications and revisions for robot assisted surgeries.

Recent clinical data, from robot assisted surgical procedures, provides strong evidence of improved alignment and reduced bone loss (orthopedic robots), reduced recovery times (laparoscopic and general surgery robots) and reduced complications (spine robots).  Next generation solutions described earlier have the potential to significantly decrease invasiveness and improve clinical outcomes.  Because robot systems are computer controlled and have the capability to store surgical case data records, these systems will eventually incorporate Artificial Intelligence to augment the surgeon’s decision making process.   For these same reasons, these systems will be used more routinely for quality control purposes within a hospital system.  With further increases in procedure volumes and increased competition, we can reasonably expect that the cost of robotic surgeries will come down, while outcomes are being improved. 

Alind Sahay is a research and development business leader and innovator with over 20 years experience developing and launching innovative medical devices for global markets, which includes over 12 years leading product development for image based robotics at Integrated Surgical Systems and navigation systems at GE Healthcare. His business development experience encompasses defining and executing on technology-based opportunities, including licensing and collaborations. 

Currently, he is Vice President, Research and Development at Noxilizer. Previous positions include Program Director, Endo Health Solutions, where he was responsible for the complete research and development portfolio for the Healthronics product line and Director, Product Development at Terumo Cardiovascular Systems, where he managed new product development and line-extensions for cardiac pumping systems and associated disposables.

Healthcare 2025: Ten Top Technologies That Will Transform the Industry

By Reenita Das
Partner and Senior Vice President
Transformational Health
Frost & Sullivan


 
As healthcare moves to a model of “any time”, “any place,” “continuous” and “personalized” care, it is important to identify the key technologies that will enable this transition and work toward their implementation into different care settings.  Frost & Sullivan’s Visionary Healthcare research has identified several technologies that are most likely to impact healthcare paradigms by 2025.

Figure 1: Healthcare World in 2025
 
It is interesting to note that technological advances in the fields of computing, machine learning, nanotechnology and electronics are all playing a role in helping reshape the industry.  The figure below provides an overview of the top technologies that will change this industry dramatically, and an analysis of the timeframe for their commercialization and maturation.

Figure 2: Timeframe for Commercialization and Maturation of Top 2025 Technologies
 
Quantum Computing

We are now beginning to see larger datasets in healthcare research and delivery to analyze and make sense of entire genome sequences, impact of environmental, behavioral and hereditary factors on health, population health data, patient generated health data, etc. The amount of such data becoming available is only set to increase exponentially by 2025. The available computing prowess, even those of supercomputers, will not be adequate to generate quick and actionable insights from such large data sets. But quantum computing, that has a far greater calculation capacity than traditional computers, could help solve some of the highly complex healthcare problems. One noteworthy company in this field is Canadian D-Wave Systems, which boasts of clients like NASA and Google. However, the possibility of widespread quantum computing is prevented by the problem of quantum incoherence, which, it is hoped, will be solved sometime soon.

Artificial Intelligence

While the human capacity to analyze and make deductions is superior to any other species on the planet, it is still limited in terms of the volume of information that can be processed quickly. Artificial intelligence makes this process faster by several degrees and far more efficient than humanly possible. IBM’s Watson, for example, can read 40 million documents in 15 seconds. With machine learning capabilities, the technology’s healthcare applications are boundless. Some of the applications currently being developed are assisting physicians and radiologists to make accurate diagnoses (IBM Watson Health), predicting which potential therapeutic candidates are most likely to work as efficient drugs (Atomwise) and mining medical records data to improve healthcare service delivery (Google DeepMind Health).
 
Robotic Care

Robots have been in healthcare for a long time now – the Da Vinci surgical robot is a case in point. But several other robotic applications are emerging and we should expect a lot more robots operating in the healthcare space by 2025. Consider the simplistic telepresence robots like those offered by InTouch Health, allowing the doctor to ‘move around’ and examine patients, while being seated at his or her computer at a distant location. Or Aethon’s TUG robots that help hospitals internally transport their pharmacy supplies, lab samples, patient food, clean or soiled linen or even trash, all by itself. Then there are the patient and elderly care robots that help in lifting patients from beds to wheelchairs and back, like the Robear robot or the Riba robot in Japan. Finally, robots can also play a role in pediatric therapy for autism disorders, phobias and as distractions; several examples exist - Phobot, PARO, NAO and Milo.
 
Nanorobots

At the nanoscale, robots can play entirely different roles, this time inside the human body, traveling through bloodstreams. Ongoing research is exploring the potential nanorobots can have in vitals monitoring, performing body functions (e.g. carrying oxygen, destroying infectious agents like bacteria), targeted drug delivery (e.g. cancer therapy, blood clotting) or even to perform nanoscale, in situ surgeries. The actual list of applications of nanomedicine, the umbrella term for nanotechnology applications in healthcare, is even larger and fascinating. It includes assisting biological research (cell simulations), being intracellular sensors for diagnostics and playing a role in molecular medicine (genetic therapy). At the very least, we should see the beginning of testing of such applications by 2025.

Cyborgization

The year 2025 should bring not just the introduction of robots inside our bodies, but also the transformation of the human body itself into partial robotic beings. This can manifest in several forms, some of which are visible even today – limb replacements, organ replacements, internal electronics, and capabilities, limbs or senses that are enhanced in function than their normal counterparts. Apart from the ‘bionic’ prosthetics movement, an estimated 30,000 – 50,000 people already have an implanted RFID chip inside their bodies. In the future, we are likely to see enhanced capabilities in terms of vision, hearing or with limbs, especially in defense application areas. Artificial pancreas is a subject of intense research, and it is likely that more sophisticated versions of these devices may even be implanted in the human body in the future – to supplement or even completely replace normal pancreas.
 
Brain-Computer Interfaces

Another form of cyborgization is the use of brain-computer interfaces to connect a wired brain directly with an external device. Apart from the research and brain-mapping applications currently in use, the technology is being developed for ‘neural bypass’ applications - helping paralyzed patients regain control of their limbs via ‘external’ connections to the limbs. Similar applications are being developed wherein the body’s neural framework is tapped using electric stimulation to modify certain functions. Existing examples include cochlear implants and pacemakers, while applications being developed include retinal implants (to restore sight) and spinal cord stimulators (for pain relief).

Medical Tricorder (Diagnostic Device)

Taking cue from the device popularized by the Star Wars franchise, efforts are aimed at developing a hand-held portable diagnostic device that can scan the human body and diagnose their ailments within seconds. While the fantasy version of the device could do this, current efforts are more realistic in their approach. The $10 million Qualcomm Tricorder X Prize competition launched in 2012, for example, aims at diagnosing 13 medical conditions (10 required, 3 elective) including strep throat, sleep apnea and atrial fibrillation, with a consumer-friendly interface device weighing no more than 5 pounds. With the winners of this competition set to be announced in 2017, we could expect such devices to be commercially available by 2025.

Digital Avatars

After self-diagnosing using a tricorder, patients in 2025 will want to get in touch with a doctor. Of course, telehealth will be an option, but there might be another option available for satisfying queries or getting more information on the diagnosis – just like the generic voice assistants available today. While Siri or Cortana are voice-only assistants, the Dr. WebMD of 2025 can be a digital avatar that can appear in holographic projections to assist patients and caregivers with their healthcare queries. The holographic projection of a human doctor, backed by artificial intelligence technologies, will allow for it to handle several queries simultaneously. Beyond answering queries, it could schedule appointments for a physical checkup with a doctor in your network, and share notes of your conversation with a doctor, in a digital-physical care coordination model. 

Augmented / Virtual Reality

The applications of the two related technologies are manifold and relevant to both sides of the care delivery equation – providers as well as patients. Providers can benefit from using enabled glasses for medical education - to study the human anatomy, for example, and for observing and studying surgeries as they were performed. Augmented reality could also be used during live surgeries to ‘see through’ anatomical structures to know the location of organs and blood vessels. On the patient side, one of the most advanced applications that are already in use is the treatment of various phobias and other mental health disorders. As the technology advances, we can expect more advanced applications to emerge by 2025, especially for healthcare providers.
 
3D Printing

3D printing is a well-known technology with several existing applications in healthcare, including orthopedic devices and several implants. Another application that is being considered is of 3D printed medicines, which can allow alteration of daily dosage and enable personalized medicine by customizing formulations of the drugs. Another niche that is now opening up is that of 3D Bioprinting – the possibility of ‘printing’ tissues or even organs. Applications range from skin tissue for burn victims to organ replacements for patients. Tissues thus printed can also be used in drug development, a service currently being offered by Organovo.

Companies within the healthcare industry must examine and study the impact of these technologies on their business, as well as investing into utilizing these in the future if they are to continue to sustain themselves profitably in the new environment.

This article was written with contributions from Siddharth Shah, Research Analyst and Venkat Rajan, Global Director, both from the Visionary Health program of Frost & Sullivan’s Transformation Health practice.