Bigfoot co-founder and former Medtronic Diabetes Chief Engineer; Nudge BG aims to create simple, easier-to-use AID algorithm; extensive Q&A with Lane Desborough
- Q&A with Lane Desborough
- Q: What is Nudge BG?
- Q: What separates Nudge BG from other “algorithm” groups, such as CamAPS, Tidepool, or Diabeloop?
- Q: Where do you hope to be in the next year with Nudge BG? In the next 2-3 years? 5-7 years?
- Q: In your expert opinion, what sorts of outcomes can be achieved with a simple system? Is there an upper limit to the outcomes that can be achieved without more input from the user and their clinician?
- Q: What are the biggest challenges facing Nudge BG over the next year? In the next 2-3 years? 5-7 years?
- Q: How can the Nudge system support healthcare providers (especially primary care) and make diabetes care easier for providers, rather than more difficult as more data comes in?
- Q: Is there a plan for commercializing Nudge BG?
- Q: Is there space in the marketplace for algorithm-only groups, or will they ultimately have to partner with CGM/pump companies?
- Q: It's an incredibly exciting task on which you have embarked – we could not be happier that you have taken on this mission.
Impressive, lengthy history in diabetes technology includes legions of entrepreneurial, corporate, research, and policy leaders, plus hundreds of families and patients
We recently had a chance to catch up with automated insulin delivery trailblazer Mr. Lane Desborough and learn about his new automated insulin delivery (AID) algorithm company, Nudge BG. Mr. Desborough was, of course, formerly the Chief Engineer at Medtronic Diabetes (2010-2014) before co-founding Bigfoot with Bryan Mazlish and Jeffrey Brewer in 2014. Mr. Desborough’s work in AID is personal, as his son was diagnosed with type 1 diabetes in 2009. He has also been instrumental in the DIY movement, co-creating Nightscout (with John Costik) in 2013 and being the first to say, that year at the annual DData/DiabetesMine meeting “We are not waiting,” which then quickly became a mantra for the T1D community (many were involved in this moment, such as Amy Tenderich hosting the meeting with her incredible DiabetesMine team, countless people with diabetes, and parents such as Howard Look who quickly created the hashtag #WeAreNotWaiting, among many others.) In his work in co-founding Bigfoot in particular, Mr. Desborough hastened work in the entire field on AID, working alongside Brewer and Mazlish.
What’s happened more recently? As Bigfoot became bigger and more well-funded, Mr. Desborough got the entrepreneurial bug again, resigned from Bigfoot in the fall of 2019 and began quietly working on Nudge BG, going back to his roots, focusing again nearly completely on algorithms. The company is designing algorithms for a broader group (see Intel Inside references below, which we look forward to writing more about in the future). Now that his influence on Bigfoot and AID has been cemented, we understand his work on algorithms broadening to work with specific, larger populations; while Bigfoot is working on the entire “vertical” system, Desborough’s focus is horizontal, at the top of the ecosystem, on algorithms in particular, as well as better understanding of how all components will work together, on interoperability and other approaches, etc.
Desborough’s influence on the field is prodigious and his eagerness to share experiences and offer advice is widely renowned, whether that be with both entrepreneurial, corporate, research, or regulatory leaders, with people with diabetes and their families, with endocrinologists, nurses, behavioral specialists, and others – specifically, he’s very well known for moving forward the entire diabetes field, rather than just specific organizations or even his own company.
Aims to create the "Intel Inside" of AID algorithms with a vision of simpler=better
According to California business records, Nudge BG was registered in January of 2020 and we expect Desborough to continue to help the field, even now that he’s CEO himself of his own company. Close Concerns has followed Desborough for over a decade, and is delighted to be the source for his first public discussion about his work at Nudge BG. Mr. Desborough set the stage for Nudge BG by describing for us more about his 21-year old son, Hayden, who is also quite well-known in the field over the years, largely through stories he has allowed (and encouraged) his father to share, to help people understand more about diabetes.
As background, for a long time, Hayden had chosen not to use a traditional or DIY AID system, Mr. Desborough said, because such systems from his perspective still required too much user input and mental energy.
With Nudge, Mr. Desborough is aiming for an AID system open to a group of people much broader than those only on pumps, and his work will be primarily on developing the best and easiest algorithms to achieve this while also continuing to work with multiple others in the field trying to do the same thing. Akin to Abbott’s FreeStyle Libre, Nudge BG is focusing on two principles: “simpler is better” and allowing users to choose their own levels of engagement. Ultimately, Nudge BG’s goal is to create a system requiring less effort than existing SAP and hybrid closed loop systems, and with better outcomes than MDI or open-loop pump therapy. To this end, Nudge BG will be a fully closed loop algorithm (aiming for class II, interoperable “iController” clearance) that does not require meal or exercise inputs. On the name, Nudge BG, Mr. Desborough explained that the system is designed to “nudge” basal insulin in response to CGM.
To date, Nudge BG has been tested on “hundreds of thousands of patient-days” in-silico with promising results. The in-silico data suggests, like “other systems,” that very engaged users can reduce their A1cs from 7% to 6%, but, perhaps more importantly, also help less engaged users with A1cs >8% get “into the 7%-range.” Nudge BG is already “working with half a dozen companies in the AID space,” aiming to be the “Intel Inside” algorithm for CGM and pump companies looking to get into AID. Wow!
Q&A with Lane Desborough
Q: What is Nudge BG?
LD: I founded Nudge BG in January, after leaving Bigfoot last fall. I wish Bigfoot well and think they have a real winner with Bigfoot Unity, which is currently being reviewed by the FDA. But for my son Hayden, who’s 21 and prefers to dose insulin using a pump and not a pen, there’s no AID system in existence or on the horizon (no pun intended) that lets him safely put diabetes in the background and get on with his life. In the absence of such a solution he, like millions of other people living with diabetes, is choosing - at great peril - to put diabetes in the background by simply ignoring it. Diabetes management has been unrelenting for our son and for our whole family; eleven years after his diagnosis we’re all mentally and emotionally exhausted by the prospect of thinking about diabetes hundreds of times per day.
Taking a lesson from Jared Watkin and his team at Abbott Diabetes Care, we recognized there’s a large cohort of people with diabetes - like my son - who wish to engage with diabetes on their own terms:
The Abbott FreeStyle Libre’s outstanding success in the market is a great example of “simpler is better” for the majority of people.
With FreeStyle Libre, instead of “being chased by the number” - constantly reminded by alarms that they are “failing” - users choose their level of engagement, which is refreshing and empowering.
Nudge BG is delivering a simple AID system comprised of software and algorithms that reduces the burden for those living with insulin-requiring diabetes: less effort than Sensor Augmented Pump (SAP) and Hybrid Closed Loop (HCL) therapies and with better outcomes than Multiple Daily Injection (MDI) and Continuous Subcutaneous Insulin Infusion (CSII) therapies. We’ve developed a Full Closed Loop (FCL) AID, inspired by FDA’s Interoperable Automated Glycemic Controller (iAGC) 510(k) pathway. Our FCL algorithm sits between a CGM and an insulin pump, “nudging” basal insulin in response to CGM glucose values.
Here’s a simple way of thinking about how our system works: imagine if a user ran a correction bolus calculation every five minutes, based on CGM data, and made small adjustments to insulin delivery (including reducing basal to reduce exposure to hypoglycemia).
The way we’ve designed and developed our system, it could be deployed as a mobile app running on a smartphone, or, just as easily, be directly implemented in the firmware of an interoperable CGM (iCGM) or Alternate Controller Enabled (ACE) pump.
Q: What separates Nudge BG from other “algorithm” groups, such as CamAPS, Tidepool, or Diabeloop?
LD: Those are Hybrid Closed Loop (HCL) systems, rich with features and configuration options to support engaged users. They are out of the reach of most people - including my son - due to their complexity and need for a steady stream of user inputs and settings information. Nudge BG’s system has been designed from the start to be Full Closed Loop (FCL), with no bolusing or CGM alarms required. We’re going after a much larger cohort, with a much greater need.
Hundreds of thousands of patient-days of in silico evidence suggest that with our system working in the background, people can choose their level of engagement while achieving their desired glycemic outcomes. Bolusing and CGM notifications can still be accessed from the pump or CGM respectively through the devices’ standard user interfaces, but it's up to the user how they use these features.
Other systems help very engaged folks reduce HbA1c from 7s to 6s. We see this in the clinical study data for most of these systems, which typically recruit subjects who are already generally highly engaged. In Silico data suggests Nudge BG’s system can achieve these results as well, although we think the bigger opportunity is to help those with HbA1cs north of 8 (half of all people with insulin-requiring diabetes!) get into the 7s, while simultaneously reducing exposure to severe hypoglycemia and diabetic ketoacidosis, with a system they will want to use - and keep using - because it reduces their cognitive and emotional burden.
As an adjuvant to SAP therapy, our system improves outcomes at night by safely bringing glucose into range by morning as the user sleeps. During the day, it reduces exposure to hypo- and hyperglycemia for those who struggle to bolus accurately and consistently, or for those who just want to get on with life.
Q: Where do you hope to be in the next year with Nudge BG? In the next 2-3 years? 5-7 years?
LD: Ultimately, we want Nudge BG's life-altering technology to be available to everybody living with insulin-requiring diabetes. To that end, we are working with half a dozen companies in the AID space to provide a truly enhanced, integrated solution that will deliver a fantastic experience and great glycemic outcomes to the largest possible cohort of people.
Nudge BG’s algorithm, data science, and systems engineering skills, experience, and intellectual property serve to complement CGM and pump companies’ core competencies (which we’d define as hardware development and manufacturing, marketing, sales, reimbursement relationships, customer support, and supply chain).
We intend to be the “Intel Inside” of iCGM or ACE pumps, especially for those companies who have not made a strategic investment in industrial grade automation algorithms. We know that every device manufacturer is struggling to achieve a simpler interface where their algorithms are concerned. With “Nudge BG Inside”, these companies differentiate themselves and provide a solution for a segment of the market for whom feature-rich HCL algorithms are simply beyond reach; a large cohort who want good outcomes with less therapy burden.
Q: In your expert opinion, what sorts of outcomes can be achieved with a simple system? Is there an upper limit to the outcomes that can be achieved without more input from the user and their clinician?
LD: I’m flattered by the “expert” compliment, but recognize that I’m standing on the shoulders of giants. My perspective has been informed by more than a decade working with some of the best and brightest minds in the space and the mountain of data and research they have created.
Nudge BG's unique benefit is that it enables the user to tailor their level of engagement to the point, should they wish, of eliminating much of the daily micro-management of diabetes therapy - beyond making sure the pump and CGM are functioning - while at the same time dramatically improving glycemic outcomes.
For the majority of people living with insulin-requiring diabetes, evidence suggests that with almost no cognitive or emotional burden, glycemic outcomes (TIR, HbA1c) with Nudge BG’s system are expected to be comparable to standard of care MDI / SAP. For very engaged users - with Nudge BG, engagement is a choice, not an obligation - outcomes may be better than HCL.
Bolusing really scares me because of the potential for use error and the wide discrepancies in how people calculate boluses, which is why Nudge BG’s system is designed so that the user would never need to issue a bolus dose. Winston Churchill said “democracy is the worst form of Government except for all those other forms that have been tried from time to time”. Subcutaneous bolusing of rapid acting insulin is the worst form of insulin delivery except for all those other forms that have been tried from time to time. Bolusing is difficult, burdensome, embarrassing, inconvenient, dangerous (hypo risk), technically challenging, and only partially effective. A typical meal bolus has a glucose lowering effect of 180 mg/dl or 10 mmol/L: three times a day, people eat themselves out of a significant glucose deficit. With the arrival of ultrarapid insulins, insulin coformulations, hepatic-directed prandial insulin (Diasome HDV), and inhalable insulin (Mannkind Afrezza), subcutaneous insulin bolusing is becoming less necessary.
Living with insulin-requiring diabetes means living in a constant stream of blood glucose variation, coming from dozens of unmeasured sources (42 sources according to Adam Brown!). The profusion of settings and features with contemporary HCL AID systems (which have hundreds of settings) represent additional sources of variation. I think it’s important to recognize that input to an AID system provided by humans (users and their HCPs) is a source of both good and bad variation. With great power comes great responsibility. Input from the user (meal and / or exercise announcement) or input from their HCP (basal insulin profile adjustments), when done consistently and accurately, will produce great outcomes. Done poorly, they will do more harm than good.
Take for example “exercise mode.” What does exercise mean to the user? How do they interpret this? What is the intent of this mode? I’m an ultramarathon runner, a skier, and a sailboat racer. If I had diabetes, those activities would have completely different effects on my blood glucose. Does the user understand how to safely use a feature like “exercise mode”?
Nudge BG is intent on improving safety and efficacy – Time in Range - for people who want to be less engaged with managing their diabetes; people who may be unwilling or unable to safely use the many features of contemporary HCL AID systems.
Q: What are the biggest challenges facing Nudge BG over the next year? In the next 2-3 years? 5-7 years?
LD: The first challenge facing any company in the AID space is correctly identifying and serving the needs of those with insulin-requiring diabetes who will benefit the most.
It's easy to find highly engaged users. It's easy to engage early technology adopters, in fact they will find you. It's also easy to over-engineer and create complex, burdensome products that fail to achieve broader market adoption because you were focused on that highly engaged and vocal minority.
Unfortunately, highly engaged users and early technology adopters make up the lion's share of those recruited and studied in AID trials. Population data from NHANES, CDC, CMS, T1PCO, and private insurers paints a very different picture of the state of type 1 diabetes in the United States from the data we’re seeing from AID trials. It’s clear that the population HbA1c is higher, the prevalence of severe hypoglycemia and DKA are higher, and Time in Range is lower than the cohort being so carefully recruited and studied in AID trials.
This tells me that less engaged folks - who represent the majority - are being left behind by the complexity of other AID systems.
The second challenge is interoperability. AID interoperability is here; Pandora’s Box has been opened. Today, what we call interoperability is really just compatibility, a set of development or commercial agreements between pairs of CGM, pump, and algorithm companies.
The interoperability trend will play out over the next 2-7 years in much the same way I saw it play out in industrial automation two decades ago. Profound changes in the landscape are coming, which will ultimately be of benefit to people with diabetes. But in the meantime, companies and regulators are in for a tumultuous ride.
Q: How can the Nudge system support healthcare providers (especially primary care) and make diabetes care easier for providers, rather than more difficult as more data comes in?
LD: Nudge BG’s algorithms are intended to take on more of the work from the healthcare providers than any other solution and deliver consistent, repeatable, high quality outcomes.
Nudge inherits settings from the pump, at least as an initial starting point, then adapts them over time. For instance, if someone has been using 12U of long acting insulin per day and then starts using a pump, the pump's initial basal rate may be 0.5U/hr. Nudge would start from that baseline.
Our system is intended to be as easy to prescribe and support as an SGLT-2 inhibitor or a GLP-1 agonist. It has no settings, no configuration, and hardly any user interface at all. Adjusting physiology parameters (basal rates, insulin-to-carb ratios, insulin sensitivity factors) is a difficult task for PCPs, NPs, and endocrinologists. Nudge BG’s algorithms, which constantly adjust settings based on data, reduce this burden on healthcare providers.
Q: Is there a plan for commercializing Nudge BG?
LD: Yes! The path to regulatory approval and commercial success has never been more dynamic and exciting. Rapidly changing environmental factors favor those who are most agile. More details to follow.
Q: Is there space in the marketplace for algorithm-only groups, or will they ultimately have to partner with CGM/pump companies?
LD: We'll know the answer to that question in a year or so. If the economics aren’t there, it will be a real tragedy for the interoperability regulatory pathway which Dr. Courtney Lias and her team at FDA have worked so hard to develop, because there will be less innovation and fewer choices for people with diabetes.
Q: It's an incredibly exciting task on which you have embarked – we could not be happier that you have taken on this mission.
--by Albert Cai and Kelly Close