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Femtech startup Inne takes the wraps off a hormone tracker and $8.8M in funding – TechCrunch

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Berlin-based femtech startup Inne is coming out of stealth to announce an €8 million (~$8.8M) Series A and give the first glimpse of a hormone-tracking subscription product for fertility-tracking and natural contraception that’s slated for launch in Q1 next year.

The Series A is led by led by Blossom Capital, with early Inne backer Monkfish Equity also participating, along with a number of angel investors — including Taavet Hinrikus, co-founder of TransferWise; Tom Stafford, managing partner at DST; and Trivago co-founder Rolf Schromgens.

Women’s health apps have been having a tech-fuelled moment in recent years, with the rise of a femtech category. There are now all sorts of apps for tracking periods and the menstrual cycle, such as Clue and Flo.

Some also try to predict which days a women is fertile and which they’re not — offering digital tools to help women track bodily signals if they’re following a natural family planning method of contraception, or indeed trying to conceive a baby.

Others — such as Natural Cycles — have gone further down that path, branding their approach “digital contraception” and claiming greater sophistication vs traditional natural family planning by applying learning algorithms to cycle data augmented with additional information (typically a daily body temperature measurement). Although there has also been some controversy around aggressive and even misleading marketing tactics targeting young women.

A multi-month investigation by the medical device regulator in Natural Cycles’ home market, instigated after a number of women fell pregnant while using its method, found rates of failure were in line with its small-print promises but concluded with the company agreeing to clarify the risk of the product failing.

At issue is that the notion of “digital contraception” may present as simple and effortless — arriving in handy app form, often boosted by a flotilla of seductive social media lifestyle ads. Yet the reality for the user is the opposite of effortless. Because in fact they are personally taking on all of the risk.

For these products to work the user needs a high level of dedication to stick at it, be consistent and pay close attention to key details in order to achieve the promised rate of protection.

Natural contraception is also what Inne is touting, dangling another enticing promise of hormone-free contraception — its website calls the product “a tool of radical self-knowledge” and claims it “protect[s]… from invasive contraceptive methods”. It’s twist is it’s not using temperature to track fertility; its focus is on hormone-tracking as a fertility measure.

Inne says it’s developed a saliva-based test to measure hormone levels, along with an in vitro diagnostic device (pictured above) that allows data to be extracted from the disposable tests at home and wirelessly logged in the companion app.

Founder Eirini Rapti describes the product as a “mini lab” — saying it’s small and portable enough to fit in a pocket. Her team has been doing the R&D on it since 2017, preferring, she says, to focus on getting the biochemistry right rather than shouting about launching the startup. (It took in seed funding prior to this round but isn’t disclosing how much.)

At this stage Inne has applied for and gained European certification as a medical device. Though it’s not yet been formally announced.

The first product, a natural contraception for adult women — billed as best suited for women aged 28-40, i.e. at a steady relationship time-of-life — will be launching in select European markets (starting in Scandinavia) next year, though initially as a closed beta style launch as they work on iterating the product based on user feedback.

“It basically has three parts,” Rapti says of the proposition. “It has a small reader… It has what we call a little mouth opening in the front. It always gives you a smile. That’s the hardware part of it, so it recognizes the intensity of your hormones. And then there’s a disposable saliva test. You basically collect your saliva by putting it in your mouth for 30 seconds. And then you insert it in the reader and then you go about your day.

“The reader is connected to your phone, either via BlueTooth or wifi, depending on where you are taking the test daily… It takes the reading and it sends it over to your phone. In your phone you can do a couple of things. First of all you look at your hormonal data and you look at how those change throughout the menstrual cycle. So you can see how they grow, how they fall. What that means about your ovulation or your overall female health — like we measure progesterone; that tells you a lot about your lining etc. And then you can also track your fluids… We teach you how to track them, how to understand what they mean.”

As well as a contraception use-case, the fertility tracking element naturally means it could also be used by women wanting to get pregnant.

“This product is not a tracker. We’re not looking to gather your data and then tell you next month what you should be feeling — at all,” she adds. “It’s more designed to track your hormones and tell you look this is the most basic change that happens in your body and because of those changes you will feel certain things. So do you feel them or not — and if you don’t, what does it mean? Or if you do what does it mean?

“It builds your own hormonal baseline — so you start measuring your hormones and we go okay so this is your baseline and now let’s look at things that go out of your baseline. And what do they mean?”

Of course the key question is how accurate is a saliva-based test for hormones as a method for predicting fertility? On this Rapti says Inne isn’t ready to share data about the product’s efficacy — but claims it will be publishing details of the various studies it conducted as part of the CE marking process in the next few weeks.

“A couple more weeks and all the hardcore numbers will be out there,” she says.

In terms of how it works in general the hormone measurement is “a combination of a biochemical reaction and the read out of it”, as she puts it — with the test itself being pure chemistry but algorithms then being applied to interpret the hormonal reading, looping in other signals such as the user’s cycle length, age and the time of day of the test.

She claims the biochemical hormone test the product relies on as its baseline for predicting fertility is based on similar principles to standard pregnancy tests — such as those that involve peeing on a stick to get a binary ‘pregnant’ or ‘not pregnant’ result. “We are focused on specifically fertility hormones,” she says.

“Our device is a medical device. It’s CE-certified in Europe and to do that you have to do all kinds of verification and performance evaluation studies. They will be published pretty soon. I cannot tell you too much in detail but to develop something like that we had to do verification studies, performance evaluation studies, so all of that is done.”

While it developed and “validated” the approach in-house, Rapti notes that it also worked with a number of external diagnostic companies to “optimize” the test.

“The science behind it is pretty straightforward,” she adds. “Your hormones behave in a specific way — they go from a low to a high to a low again, and what you’re looking for is building that trend… What we are building is an individual curve per user. The starting and the ending point in terms of values can be different but it is the same across the cycle for one user.”

“When you enter a field like biochemistry as an outsider a lot of the academics will tell you about the incredible things you could do in the future. And there are plenty,” she adds. “But I think what has made a difference to us is we always had this manufacturability in mind. So if you ask me there’s plenty of ways you can detect hormones that are spectacular but need about ten years of development let alone being able to manufacture it at scale. So it was important to me to find a technology that would allow us to do it effectively, repeatedly but also manufacture it at a low cost — so not reinventing the whole wheel.”

Rapti says Inne is controlling for variability in the testing process by controlling when users take the measurement (although that’s clearly not directly within its control, even if it can send an in-app reminder); controlling how much saliva is extracted per test; and controlling how much of the sample is tested — saying “that’s all done mechanically; you don’t do that”.

“The beauty about hormones is they do not get influenced by lack of sleep, they do not get influenced by getting out of your bed — and this is the reason why I wanted to opt to actually measure them,” she adds, saying she came up with the idea for the product as a user of natural contraception searching for a better experience. (Rapti is not herself trained in medical or life sciences.)

“When I started the company I was using the temperature method [of natural contraception] and I thought it cannot be that I have to take this measurement from my bed otherwise my measurement’s invalid,” she adds.

However there are other types of usage restrictions Inne users will need to observe in order to avoid negatively affecting the hormonal measurements.

Firstly they must take the test in the same time window each time — either in the morning or the evening but sticking to one of those choices for good.

They also need to stick to daily testing for at least a full menstrual cycle. Plus there are certain days in the month when testing will always be essential, per Rapti, even as she suggests a “learning element” might allow for the odd missed test day later on, i.e. once enough data has been inputted.

Users also have to avoid drinking and eating for 30 minutes before taking the test. She further specifies this half hour pre-test restriction includes not having oral sex — “because that also affects the measurements”.

“There’s a few indications around it,” she concedes, adding: “The product is super easy to use but it is not for women who want to not think ever about contraception or their bodies. I believe that for these women the IUD would be the perfect solution because they never have to think about it. This product is for women who consciously do not want to take hormones and don’t want invasive devices — either because they’ve been in pain or they’re interested in being natural and not taking hormones.”

At this stage Inne hasn’t performed any comparative studies vs established contraception methods such as the pill. So unless or until it does users won’t be able to assess the relative risk of falling pregnant while using it against more tried and tested contraception methods.

Rapti says the plan is to run more clinical studies in the coming year, helped by the new funding. But these will be more focused on what additional insights can be extracted from the test to feed the product proposition — rather than on further efficacy (or any comparative) tests.

They’ve also started the process of applying for FDA certification to be able to enter the US market in future.

Beyond natural contraception and fertility tracking, Inne is thinking about wider applications for its approach to hormone tracking — such as providing women with information about the menopause, based on longer term tracking of their hormone levels. Or to help manage conditions such as endometriosis, which is one of the areas where it wants to do further research.

The intent is to be the opposite of binary, she suggests, by providing adult women with a versatile tool to help them get closer to and understand changes in their bodies for a range of individual needs and purposes.

“I want to shift the way people perceive our female bodies to be binary,” she adds. “Our bodies are not binary, they change around the month. So maybe this month you want to avoid getting pregnant and maybe next month you actually want to get pregnant. It’s the same body that you need to understand to help you do that.”

Commenting on the Series A in a supporting statement, Louise Samet, partner at Blossom Capital, said: “Inne has a winning combination of scientific validity plus usability that can enable women to better understand their bodies at all stages in their lives. What really impressed us is the team’s meticulous focus on design and easy-of-use together with the scientific validity and clear ambition to impact women all over the world.”



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Apple and Google’s AI wizardry promises privacy—at a cost

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Since the dawn of the iPhone, many of the smarts in smartphones have come from elsewhere: the corporate computers known as the cloud. Mobile apps sent user data cloudward for useful tasks like transcribing speech or suggesting message replies. Now Apple and Google say smartphones are smart enough to do some crucial and sensitive machine learning tasks like those on their own.

At Apple’s WWDC event this month, the company said its virtual assistant Siri will transcribe speech without tapping the cloud in some languages on recent and future iPhones and iPads. During its own I/O developer event last month, Google said the latest version of its Android operating system has a feature dedicated to secure, on-device processing of sensitive data, called the Private Compute Core. Its initial uses include powering the version of the company’s Smart Reply feature built into its mobile keyboard that can suggest responses to incoming messages.

Apple and Google both say on-device machine learning offers more privacy and snappier apps. Not transmitting personal data cuts the risk of exposure and saves time spent waiting for data to traverse the internet. At the same time, keeping data on devices aligns with the tech giants’ long-term interest in keeping consumers bound into their ecosystems. People that hear their data can be processed more privately might become more willing to agree to share more data.

The companies’ recent promotion of on-device machine learning comes after years of work on technology to constrain the data their clouds can “see.”

In 2014, Google started gathering some data on Chrome browser usage through a technique called differential privacy, which adds noise to harvested data in ways that restrict what those samples reveal about individuals. Apple has used the technique on data gathered from phones to inform emoji and typing predictions and for web browsing data.

More recently, both companies have adopted a technology called federated learning. It allows a cloud-based machine learning system to be updated without scooping in raw data; instead, individual devices process data locally and share only digested updates. As with differential privacy, the companies have discussed using federated learning only in limited cases. Google has used the technique to keep its mobile typing predictions up to date with language trends; Apple has published research on using it to update speech recognition models.

Rachel Cummings, an assistant professor at Columbia who has previously consulted on privacy for Apple, says the rapid shift to do some machine learning on phones has been striking. “It’s incredibly rare to see something going from the first conception to being deployed at scale in so few years,” she says.

That progress has required not just advances in computer science but for companies to take on the practical challenges of processing data on devices owned by consumers. Google has said that its federated learning system only taps users’ devices when they are plugged in, idle, and on a free internet connection. The technique was enabled in part by improvements in the power of mobile processors.

Beefier mobile hardware also contributed to Google’s 2019 announcement that voice recognition for its virtual assistant on Pixel devices would be wholly on-device, free from the crutch of the cloud. Apple’s new on-device voice recognition for Siri, announced at WWDC this month, will use the “neural engine” the company added to its mobile processorsto power up machine learning algorithms.

The technical feats are impressive. It’s debatable how much they will meaningfully change users’ relationship with tech giants.

Presenters at Apple’s WWDC said Siri’s new design was a “major update to privacy” that addressed the risk associated with accidentally transmitting audio to the cloud, saying that was users’ largest privacy concern about voice assistants. Some Siri commands—such as setting timers—can be recognized wholly locally, making for a speedy response. Yet in many cases transcribed commands to Siri—presumably including from accidental recordings—will be sent to Apple servers for software to decode and respond. Siri voice transcription will still be cloud-based for HomePod smart speakers commonly installed in bedrooms and kitchens, where accidental recording can be more concerning.

Google also promotes on-device data processing as a privacy win and has signaled it will expand the practice. The company expects partners such as Samsung that use its Android operating system to adopt the new Privacy Compute Core and use it for features that rely on sensitive data.

Google has also made local analysis of browsing data a feature of its proposal for reinventing online ad targeting, dubbed FLoC and claimed to be more private. Academics and some rival tech companies have said the design is likely to help Google consolidate its dominance of online ads by making targeting more difficult for other companies.

Michael Veale, a lecturer in digital rights at University College London, says on-device data processing can be a good thing but adds that the way tech companies promote it shows they are primarily motivated by a desire to keep people tied into lucrative digital ecosystems.

“Privacy gets confused with keeping data confidential, but it’s also about limiting power,” says Veale. “If you’re a big tech company and manage to reframe privacy as only confidentiality of data, that allows you to continue business as normal and gives you license to operate.”

A Google spokesperson said the company “builds for privacy everywhere computing happens” and that data sent to the Private Compute Core for processing “needs to be tied to user value.” Apple did not respond to a request for comment.

Cummings of Columbia says new privacy techniques and the way companies market them add complexity to the trade-offs of digital life. Over recent years, as machine learning has become more widely deployed, tech companies have steadily expanded the range of data they collect and analyze. There is evidence some consumers misunderstand the privacy protections trumpeted by tech giants.

A forthcoming survey study from Cummings and collaborators at Boston University and the Max Planck Institute showed descriptions of differential privacy drawn from tech companies, media, and academics to 675 Americans. Hearing about the technique made people about twice as likely to report they would be willing to share data. But there was evidence that descriptions of differential privacy’s benefits also encouraged unrealistic expectations. One-fifth of respondents expected their data to be protected against law enforcement searches, something differential privacy does not do. Apple’s and Google’s latest proclamations about on-device data processing may bring new opportunities for misunderstandings.

This story originally appeared on wired.com.

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Amazon joins Apple, Google by reducing its app store cut

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Enlarge / The Amazon Fire HD 8 tablet, which runs Amazon’s Fire OS.

Apparently following the lead of Apple and Google, Amazon has announced that it will take a smaller revenue cut from apps developed by teams earning less than $1 million annually from their apps on the Amazon Appstore. The same applies to developers who are brand-new to the marketplace.

The new program from Amazon, called the Amazon Appstore Small Business Accelerator Program, launches in Q4 of this year, and it will reduce the cut Amazon takes from app revenue, which was previously 30 percent. (Developers making over $1 million annually will continue to pay the original rate.) For some, it’s a slightly worse deal than Apple’s or Google’s, and for others, it’s better.

Amazon’s new indie-friendly rate is 20 percent, in contrast to Apple’s and Google’s 15 percent. Amazon seeks to offset this difference by granting developers 10 percent of their Appstore revenue in the form of a credit for AWS. For certain developers who use AWS, it could mean that Amazon’s effective cut is actually 10 percent, not 15 or 20 percent.

But for some, it amounts to something more like giving the developer a coupon on a purchase of services from Amazon than actually putting more cash in their pockets. It leaves small developers who aren’t spending a bunch of money on Amazon’s services with a worse deal than they’d get on Apple’s or Google’s marketplaces.

As with Apple’s program—but not Google’s—the lower rate applies to developers only if they made $1 million or less in total (in this case, the numbers assessed are those from the previous year). Crossing that threshold will lead developers to pay the older, higher rate on all of their earnings. In contrast, Google always takes a smaller cut of the first million in a given year and then applies the bigger cut to revenues after $1 million without changing the amount it took from the first million.

The Amazon Appstore primarily exists as the app store for Amazon’s Android-based Fire OS software that runs on tablets. It’s also offered as an alternative App Store for users of other Android-based operating systems.

All three companies are facing various forms of regulatory scrutiny, and that scrutiny was likely a factor in Apple’s decision to cut the fees it applies to apps released by small developers on the Apple App Store. Google followed shortly afterward for its Google Play marketplace.

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Microsoft’s Linux repositories were down for 18+ hours

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Enlarge / In 2017, Tux was sad that he had a Microsoft logo on his chest. In 2021, he’s mostly sad that Microsoft’s repositories were down for most of a day.

Jim Salter

Yesterday, packages.microsoft.com—the repository from which Microsoft serves software installers for Linux distributions including CentOS, Debian, Fedora, OpenSUSE, and more—went down hard, and it stayed down for around 18 hours. The outage impacted users trying to install .NET Core, Microsoft Teams, Microsoft SQL Server for Linux (yes, that’s a thing) and more—as well as Azure’s own devops pipelines.

We first became aware of the problem Wednesday evening when we saw 404 errors in the output of apt update on an Ubuntu workstation with Microsoft Teams installed. The outage is somewhat better documented at this .NET Core-issue report on Github, with many users from all around the world sharing their experiences and theories.

The short version is, the entire repository cluster which serves all Linux packages for Microsoft was completely down—issuing a range of HTTP 404 (content not found) and 500 (Internal Server Error) messages for any URL—for roughly 18 hours. Microsoft engineer Rahul Bhandari confirmed the outage roughly five hours after it was initially reported, with a cryptic comment about the infrastructure team “running into some space issues.”

Eighteen hours after the issue was reported, Bhandari reported that the mirrors were once again available—although with temporarily degraded performance, likely due to cold caches. In this update, Bhandari said that the original cause of the outage was “a regression in [apt repositories] during some feature migration work that resulted in those packages becoming unavailable on the mirrors.”

We’re still waiting for a comprehensive incident report, since Bhandari’s status updates provide clues but no real explanations. The good news is, we can confirm that packages.microsoft.com is indeed up once again, and it is serving packages as it should.

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