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GE Healthcare CDO Outlines Vision of Precision Health Using AI

Posted By Jon Lavietes, Wednesday, September 16, 2020

In the third and final session of the second day of the 2020 ASAP BioPharma Conference, medtech took center stage. Derek Danois, chief data officer at GE Healthcare, outlined his company’s nascent efforts to transform basic healthcare delivery models in his presentation “Artificial Intelligence in Clinical Care Delivery and the Opportunities to Accelerate Your Development and Commercial Strategy.”

Artificial Intelligence (AI) is one of the principal tools at the heart of a larger movement in the healthcare industry around “precision health.” The concept is simple: Rather than prescribing medications based on a set of generic symptoms, doctors will integrate lots of relevant data, such as genetic profile, family history, and environmental factors, in designing a custom treatment plan. Precision health will be built on precision diagnostics, therapeutics, and monitoring (e.g., wearables).

Data: the Source Code for AI and the Key to Early Detection

With the overarching mission of precision health explained, Danois showed the audience a video that told a story set in the future where a woman detects a lump on her breast, sends the self-exam directly to her doctor right from her bathroom, gets scheduled for a consult immediately, and is put through a battery of tests at the healthcare facility while doctors and technicians analyze the resultant data. The verdict: they caught a malignancy early enough to expect a full recovery. 

The video is meant to inspire, said Danois, but it also conveys GE Healthcare’s vision for the future.

“What can we do to intervene now in helping to spot the early signs of diseases? How can we intervene in a little bit more of an effective manner? How do we help patients feel less fearful and engage more with their clinicians?” he said. “We’ve got to start thinking even earlier. We have to start thinking about the data that is being collected around the world that allows us to think about this journey. Data truly is the source code for AI.”

AI, Danois explained, has to be educated, taught, and trained over a long period of time in order to be effective. For example, an AI program must be exposed to a trusted radiologist’s annotation of a tumor on an x-ray over and over again before it can learn to recognize a similar tumor on its own and become a “true companion source” and a reliable second opinion for doctors. 

Leaping Regulatory and Economic Hurdles to Make Leaps in Precision Health

The technological piece is one challenge. There are also regulatory, economic, and administrative obstacles to contend with. Healthcare providers are generating loads of valuable data, but this information is fragmented around the world, making it difficult to get the right data in the hands of clinicians at the right time. Moreover, hospitals still aren’t convinced that the cost-benefit ratio is in their favor yet. They still haven’t seen enough evidence of positive long-term outcomes, plus there’s a question as to whether health insurance plans will reimburse for AI-based treatments. Even if a health provider is sold on a new concept, it is difficult to deploy it in a highly regulated industry like healthcare.

Still, despite the hurdles that still need to be cleared, nobody disputes that the payoff is going to be transformative, to say the least, down the road in terms of fluid and effective healthcare delivery. Danois likened where we are today in digital health to the first iPhone more than a decade ago. Back then, there were only a few apps, but everyone saw tremendous possibilities. Now, we perform many of our day-to-day functions on our phones. Healthcare can get to the same place, in Danois’s view.

“It starts with understanding and thinking about the various data content that exists in these organizations. How can those be made available for, not just research but practical product development, AI development, collaboration with industry partners,” he said. “Thinking about how those can be turned into AI applications that can be deployed in the right workflows, what challenges exist from a security and privacy perspective? And then thinking about how those get injected into intelligent applications that can be deployed either on the devices in hospitals right now, or they can be deployed in a hybrid model using cloud infrastructure.”

Ultimately, said Danois, we need to get to a point where doctors don’t even think about the technology behind AI-powered apps and devices, where all it takes is a simple Internet connection in order to take advantage of them.

Alliances, of course, are a must if we are going to get there. GE Healthcare realized early that it couldn’t do it alone, despite the great investment it made into AI technology, software engineering, and data science. (For more details about GE Healthcare’s Edison AI platform, see “It’s the Data—and a Lot More,” Strategic Alliance Quarterly, Q1 2020.)

“We needed to open our technology. We needed to create an ecosystem. We needed to create the landing platforms for other partners to work with us. We’ve been encouraging others to think about doing similar things,” he said. “When you can have ethically compliant ecosystems, when you can think about what each party brings to that challenge and help solve it, and that there’s a known entity at the end of that workflow stream, either in the provider or the patient, that will allow us to take advantage of these tools and technologies and leverage these delivery models, we know that we can achieve amazing precision outcomes.”

The FDA’s Position on AI in Healthcare Devices

With that, Danois fielded a few questions from the audience. The first dealt with privacy and security concerns that come with AI apps and devices. Danois explained that these apps are like any digital health technology in that they are designed “in a thoughtful way” to do a task.   

“These get deployed into an already-existing, highly regulated environment for medical devices, whether it is in the US, in Europe, or for most other countries around the world. There’s some regulatory process where these devices need to be approved from a technology point of view, both physical and digital hardware. Those AI applications will exist in those environments,” he said, before adding that the FDA’s position is that if you incorporate AI into an existing piece of hardware, you must treat the new product as an entirely new device. You can create a separate AI app instead, but whatever you produce must be delivered in a “in cybersecurity-hardened and technically thoughtful way.”

Danois was also asked if the partnering language and mindset is different in these partnerships, given the disparities between tech and pharma corporate and alliance cultures. He responded first by making an important distinction between pure technology ventures that are focused solely on creating AI apps and services and medtech initiatives which use diagnostic tools and technologies to deliver AI-powered services. The latter already undergo a rigorous three- to five-year approval process—Danois cited pet scanners as an example. His larger point was that many collaborations are already comfortable with the longer-term regulatory and alliance cycles.

Danois had plenty more to share during his presentation. ASAP BioPharma Conference registrants can review “Artificial Intelligence in Clinical Care Delivery and the Opportunities to Accelerate Your Development and Commercial Strategy” anytime this week and beyond to benefit from his knowledge and expertise. They can also enjoy a dozen other prerecorded on-demand presentations, as well as the rest of this week’s completed livestreamed sessions.

Keep checking this blog for updates from the conference throughout this week!

Tags:  AI  AI-based treatments  alliance culture  Artificial Intelligence  Clinical Care Delivery  Derek Danois  diagnostics  FDA  GE Healthcare  health  partnering  partnerships  pharma  strategy  tech  therapeutics 

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AI Is Simple—Until It’s Not

Posted By Jon Lavietes, Thursday, March 26, 2020

ASAP members, the Q1 2020 edition of Strategic Alliance Quarterly is now in your hands, and we hope you enjoy our feature that examines some of the early tenets emerging around still-nascent artificial intelligence (AI) alliances that now dot all walks of business. Per usual, this blog serves as a vehicle to share some of the thoughtful commentary that didn’t make it into the print feature. The following insights come to you via Bruce Anderson, electronics industry global managing director at IBM. 

We touched briefly in the piece on how vertical-industry expertise is a must for creating some of the more advanced AI applications in the market today. This isn’t true of all AI-enabled products and services—Anderson cited smart speakers, which evolve their communication based on the data they collect throughout their interactions with end users, as an example of an application that doesn’t require much more than the optimization of a set of programming APIs to bring to market.

Those Who Have External Data Use It—Those Who Don’t, Buy It

However, to develop a program for optimizing manufacturing schedules, development teams need more than just base APIs. Anderson noted that an AI algorithm of this nature would in all likelihood need to digest various sets of internal end-user data, plus some external data sources, such as weather (to account for factors like humidity and temperature). In this case, the coding skill and IT knowledge of software developers can only take you so far. They need to collaborate with manufacturing veterans to figure out how to integrate domain expertise that is specific to that manufacturing environment. In many cases, companies may conclude that there isn’t “a [single] package with all of the data I might want. There’s engineering, and perhaps data acquisition, that has to be done,” according to Anderson.

Alliance managers charged with bringing AI innovations to market must get creative and figure out which companies might possess the data sets needed to create a new AI application. Then they must use their deal-making skills to put together win-win agreements that incentivize those data proprietors to share their data sets. (We discuss this new “offering manager” role in depth in the quarterly feature.)

Anderson also spoke about the difference between early back-end technology AI alliances and partnerships designed to bring an AI solution to market—more specifically, how the former is often much simpler than the latter. Bringing together servers, development platforms, sensors, traditional enterprise applications, and data management services that will ultimately power your AI APIs could be just as simple as integrating technology pieces.

“One of the companies involved may not know what you’re using [its product] for. You just know you’re using a lot of it,” said Anderson.

Happy Selling? Easier Said Than Done

But once an ecosystem of partners starts to jointly comarket and/or cosell a product offering, another layer of complexity is added.

“The more people that you get involved, there’s a lot of people who want a slice of the pie—in other words, the revenue—so you start to get complex marketing and selling arrangements,” said Anderson. “You could have a single offering that is jointly developed with somebody else. It could be sold by either of the parties. It could be delivered by either of the parties. There could be a third company in there, as well, if they’re involved in the overall stack.”

The challenge can be summed up in one question: “How do you keep it so that all of the alliance partners are happy?” asked Anderson.

Again, in the quarterly feature we delve into some of the specific issues partners need to sort out in these situations in order to bring orderly, concise, and impactful sales presentations to prospective buyers. Check-out the print issue you received earlier this month! 

Tags:  AI  API  Artificial Intelligence  Bruce Anderson  comarket  cosell  data management services  external data  IBM  innovations  integration  Strategic Alliance Quarterly 

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Alignment, Agility, and ‘Leadership IQ’ | Alliance leaders always have driven alignment. But what do we do differently, as disruption accelerates?

Posted By Michael Leonetti, CSAP, Wednesday, November 27, 2019

As an alliance leader, I used to spend 70 percent of my time not working with partners, but working on aligning internally. The concept of creating value through partnering was brand new for our leaders. We’d never walk into a meeting without a pre-meeting. Building alignment stole time away from creating new value with partners—yet it was critically important to delivering the value intended when the alliance was created.

Much has changed in alliance management—but driving alignment remains a central task of alliance leaders.

Indeed, research indicates the highest performing alliance leaders are “ambassadors” who bridge boundaries both internally as well as externally. They focus “on dialoguing with superiors and other stakeholders, proactively putting themselves on the agenda of their leaders, and managing behaviors,” according to Dave Luvison, CSAP, PhD, professor at Loyola University Maryland.

That makes sense—but what about time for externally facing alliance management?

Applying agile principles to partnering reflects a broad understanding in our profession that alliance management cannot afford to accrete more bureaucracy and process. Instead, how can we simplify the activities and processes of driving alignment so that partnering can become more agile? That seems essential to proceed effectively in the ecosystem—where it’s just not possible for there to be 100 percent alignment.

Complex models once helped us describe, in comprehensive detail, the complicated work and rich value created in the alliance management function. Alliance leaders have always looked for simplified means to explain the complexity of partner value creation. Back in the day, we used our STAR model to define Situations, Tasks, Actions, and Results—simplifying our alignment discussions as much as possible.

Today, partnering leaders look to jettison complexity wherever they can, seeking shortcuts in the traditional alliance lifecycle and technologies to further streamline alliance activities. It is the embodiment of Albert Einstein’s famous admonishment: “We cannot solve our problems with the same level of thinking that created them.” At its roots, then, agility is about changing how we think.

“Growth is a thinking game,” said Salesforce evangelist Tiffani Bova, author of Growth IQ. I would add that alliance management is a thinker’s profession. As our profession both expands and evolves in direct response to pervasive disruption, our most critical and differentiating skill remains our “leadership IQ.” It defines how we understand the transformation of business and its implications for partnering practice.

“In the advancing era of artificial intelligence, companies need to create all the pieces—and alliances—necessary to make it easy to adapt for the advancement of products,” said Bruce Anderson, IBM’s general manager, high tech/electronics industry. “You need to ask how your company should be thinking about alliances in this accelerating business approach,” he emphasized. “Alliances have become fundamental to the idea of strategy.”

Anderson’s and Bova’s points reinforced each other in a powerful way, I thought. How we think, the choices (and sequence of choices) we make, and how quickly and efficiently we can make decisions all matter. Alliance managers must improve their “leadership IQ” to better understand the big picture of disruption, how it will create value or threaten loss of market share—and how, “in this accelerating business approach,” they will drive alignment accordingly.

Tags:  accelerating  agile  aligning creating value  alliance leader  alliance management  alliances  artificial intelligence  Bruce Anderson  Dave Luvison  drive alignment  Growth IQ  IBM  leadership IQ  Loyola University Maryland  partnering alliance  partners  strategy  Tiffani Bova 

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Covey Got It Just Right: ‘Sharpen Your Saw’ in 2019—Because the Faster Partnering Moves, the More Learning and Professional Development Matters

Posted By Michael Leonetti, CSAP, Saturday, March 9, 2019

We recently did some research into ASAP’s Certified Strategic Alliance Professionals. Going back to 2010, we found that fully 90 percent of CSAPs—nine out of every 10 recipients—remain active members in the association. That tells me that that CSAPs are leaders who think seriously about our profession, who want to ensure this is an enduring profession, and who can do the hard, heavy lifting it takes to be at the top of their game.

In other words, our CSAPs are still reinvesting, following the late Stephen Covey’s advice: “We must never be too busy to take time to ‘Sharpen the Saw.’”

Covey’s seventh habit of highly effective people borrows from ancient wisdom traditions as well as modern insight into the importance of renewal. It reminds us to take regular breaks in our personal lives, and to periodically re-sharpen the skills and knowledge that keep us on the forefront of our profession. This essential saw-sharpening only happens when we engage deeply in the alliance management community and participate in its events.

Just how sharp does the learning get? Check out our Strategic Alliance publications’ coverage of the November 8-9, 2018 ASAP European Alliance Summit in Amsterdam—and join me in Fort Lauderdale, Florida, for the March 11-13, 2019 ASAP Global Alliance Summit, “Agile Partnering in Today’s Collaborative Ecosystems.”

Both of these international events exemplify how our community collectively sharpens the saw—how we continually reflect, reexamine, and renew the content of our learning. ASAP events are an eye-popping confluence of brilliant and diverse people—typically a 50/50 mix of ASAP veterans and newcomers. Our content gets richer and more nuanced with every conference as it updates tried-and-true alliance management fundamentals with the bleeding edge of practice.

The alliance lifecycle—as presented in the ASAP Handbook of Alliance Management: A Practitioner’s Guideremains very relevant “blocking and tackling.” But—as we push across industry boundaries and into ecosystem partnering, agile practices, organizational collaborative capability, and even partnering process automation—it’s obvious that so many things around the alliance lifecycle must be agile. One partnership may skip lifecycle steps two, three, and four; another alliance might start at one, continue through three, and then go to market.

We’ve talked for years about partnering going beyond alliance management. Now we’re in the “perfect storm” as the partnering everywhere model comes to life. Ecosystem partnering is everywhere—in technology, in life sciences, even in jewelry, where open innovation networks fuel innovation for Swarovski, as I learned last fall in Amsterdam. Classic channel partnerships are in decline, cloud partnerships are accelerating, and the whole field of partnering is getting much larger, much more complex.

Look at digital therapeutics—I’ve been predicting at ASAP conferences that IT companies would be the healthcare partners of the future. Now we have life science member companies partnering with big data and analytics and launching therapies approved by the US Food and Drug Administration that are primarily software based, while tech companies’ business models evolve to be able to deliver safe, reliable healthcare-related services. In telecom, 5G speeds will create new networks and mobile capabilities that we’ve never seen before—requiring partners we’ve never seen before. And artificial intelligence—what organizations and processes will become our partners in the future because of the advances of AI, and how will that again change the complexity of our alliances? 

Amidst this perfect storm, ASAP is a perfect conduit for everyone who leads collaborations to learn how to do it better and evolve “the how” every day in practice. So sharpen your saw. Invest in your community through ASAP, and invest in yourself through ASAP’s professional development events and publications.

Stephen Covey got it just right: “‘Sharpen the Saw’ means preserving and enhancing the greatest asset you have—you.”

Visit http://asapsummit.org for the most up-to-date agenda for March 11-13, 2019 ASAP Global Alliance Summit, and register for the event, at. See the ASAP Media team’s comprehensive before, during, and after coverage of the 2019 Summit in Strategic Alliance publications and on the ASAP blog. 

Michael Leonetti, CSAP, is president and CEO of ASAP and executive publisher of ASAP Media and Strategic Alliance publications. A previous version of this article appeared in Q1 2019 Strategic Alliance Quarterly

Tags:  5G  agile practices  alliance lifecycle  alliance management  artificial intelligence  ecosystem partnering  healthcare-related services  mobile  organizational collaborative  Partnering  Professional Development  telecom 

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