Famed founder Daphne Koller tells it straight: “With most drugs, we do not understand why they work”

Daphne Koller doesn’t mind hard work. She joined Stanford University’s computer science department in 1995, spending the next 18 years there in a full-time capacity before cofounding the online education giant Coursera, where she spent the following four years and remained co-chairman until last month. Koller then spent a little less than two years at Alphabet’s longevity lab, Calico, as its first chief computing officer.

It was there that Koller was reminded of her passion for applying machine learning to improve human health. She was also reminded of what she doesn’t like, which is wasted effort, something that the drug development industry — slow to understand the power of computational methods for analyzing biological data sets — as been plagued by for years.

In fairness, those computational methods have also gotten a whole lot better more recently. Little wonder that last year, Koller spied the opportunity to start another company, a drug development company called Insitro that has since raised $100 million in Series A funding, including from GV, Andreessen Horowitz and Bezos Expeditions, among others. As notably, the company recently partnered with Gilead Sciences to find medicines to treat a liver disease called nonalcoholic steatohepatitis (NASH) because of all the human data on the disease that Gilead has amassed over the years.

Later, Insitro may target even bigger epidemics, including perhaps Alzheimer’s disease or Type 2 diabetes. Certainly, it has reason to feel optimistic about what it can accomplish. As Koller told a group of rapt attendees at an event hosted by this editor a few days ago, “We’re now at a moment in history where a confluence of technologies emerged all at around the same time allow really large and interesting and disease-relevant data sets to be produced in biology. In parallel, we see  . . . machine learning technologies that are able to make sense of that data and come up with novel insights that can hopefully cure disease.”

It all sounds like talk we’ve heard before in recent years, but coming from Koller, one gets the sense that we’re finally getting close. Below are some excerpts from Koller’s interview with journalist Sarah McBride of Bloomberg. You can also watch their conversation below.

On why Insitro struck a partnership with Gilead (beyond that it could prove lucrative, with up to $1 billion in milestones attached to successfully developing targets for NASH):

There are fairly broad categories that our technology is well-suited for. We’re really interested in creating what you might call disease-in-a-dish models — places where diseases are complex, where we really haven’t had a good model system, where typical animal models that have been used [for years, including testing on mice] just aren’t very effective — and creating those ‘in vitro’ models to generate very large amounts of data that can be interpreted using machine learning.

There’s a whole slew of diseases that lend themselves to this type of approach. NASH was one of them, so partly it was the suitability of our technology to this disease, and partly it was that Gilead was just a really good partner for it because they have a whole bunch of human data from some of the clinical trials that have been running [which give us] access to two complementary data sources. One is what happens to the disease in large human cohorts, and one is what happens when you look at what the disease does in vitro, in the dish, then see if we can use what we see in the dish using machine learning to predict what we see in the human.

On how Insitro views data differently than big pharma companies:

Pharma companies say, ‘We have lots of data.’ And you say, ‘What kinds of data do you have?’ And it turns out they have dribs and drab of data, each stored on a separate spreadsheet in someone else’s laptop. There’s metadata that isn’t even recorded. For them, it’s like, ‘Yeah, I did the experiment and obviously I recorded what I had to because it doesn’t make sense to throw it away,’ but they don’t think of it as something you build a company on top of.

We come at it a completely different way. We say, ‘This is the problem that you’d like to solve. If only we had a model that could tell us the result of this experiment without having to do the experiment, because it’s costly or complicated or even impossible [because it would involve perturbing a living human’s gene].’  Well, machine learning has gotten really good at building predictive models if you give it the right data to train the model. So we’re in the business of actually building data for the sole purpose of training machine learning models. We think of [these models] like little crystal balls that would allow you to avoid doing [these more expensive or complicated] experiments.

On the impact of the National Institutes of Health’s “All of Us” research program, which is an effort to gather data from one million or more people living in the U.S. to accelerate research and improve health in part by logging individual differences in lifestyle, environment, and biology:

I would say if anything that the U.S. is a little late to the game on this one. There have been a number of national cohorts have already been generated in different countries; the two that are currently best developed are in Iceland and in the U.K, but there’s also one in Finland and one in Ireland and even in Estonia, where they’ve taken a large population from within that country and measured their genetics, but also measured a whole lot of properties about those people, including blood biomarkers and urine biomarkers and behavioral aspects and physical aspects and imaging. And so what you have now (in these countries) is a dataset that tells you, ‘Nature perturbed this gene,’ and, ‘We see this effect on the human.’

[In the UK, specifically, where they started their program five years ago and recruited 500,000 volunteers who agreed to physical and cognitive and blood pressure testing and images of the brain and the abdomen, among other things] it’s an incredibly rich data set [from which] discoveries are coming along on pretty much a weekly basis.

… This is valuable not just primarily for gene therapies but just as a way of identifying targets that actually make a difference, because most drugs that go into clinical trials fail. And by most, I mean 95 percent. And most drugs fail because they are targeting the wrong things. They are targeting proteins or genes that do not affect the disease they are supposed to affect. The recent, very visible failures of Alzheimer’s drug trials — actually several of them in a row — were almost certainly because the protein they were targeting, called amyloid beta, is just not the right causal factor in the disease.

On what researchers can do now with stem cells that would have been impossible even a few years ago:

[There are now] tools that have enabled the creation of not only large amounts of data but large amounts of biologically relevant data. So we used to do experiments on cancer cell lines . . . but it’s not a very disease relevant model. Today, we can take a small sample of skin cells and use what’s called the Yamanaka factor, to reprogram those cells to stem cell status, which are the cells that exist effectively in the womb. And those cells are capable of differentiating themselves into neural cells or liver cells or cardiac cells, and those are very disease relevant because they represent human biology; you can take those cells now from patients and from healthy people and see if there are differences in how they appear.

Readers, we could feature more of the transcript here, but we highly suggest watching the conversation with Koller. If you use this text as a leaping off point, you’ll want to start listening at around the 13-minute mark. It’s definitely worth the time to listen to what she has to say, including about cystic fibrosis, spinal muscular dystrophy in babies, and why the “mouse models” we’ve long relied on for a wide number of seemingly ubiquitous diseases “range from bad to really, really bad.” Hope you enjoy it.

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The best 2-in-1 laptop 2019: find the best convertible laptop for your needs

Over the last decade, we have fundamentally changed the way we use our laptops – thanks in large part to hybrid laptops. The best 2-in-1 laptops come in various shapes and sizes, and there’s nothing like flipping your laptop into tent mode to watch a show or movie on Netflix after a long study session.

Some of the top 2-in-1 laptops, like the Dell XPS 15 2-in-1, will come fitted with the best processors, and will be among the best laptops on the market right now. We can’t wait to see what the future holds for this versatile form factor.

The best 2-in-1 laptops will more often than not be convertible, which means the keyboard flips around the back, transforming the device into a tablet. Other devices, like the Surface Book 2, approach it differently. Microsoft’s convertible has a detachable screen, and its high-resolution PixelSense display is held up by sheer magnetic force when in laptop mode.

No matter how they execute the 2-in-1 functionality, these flexible laptops will usually have stylus compatibility – even if it’s becoming rarer to find a stylus included in the box. So, to help you find the most ideal 2-in-1 laptop for your needs, we’ve put together a list of the best convertible notebooks we’ve reviewed recently, with all their pros and cons taken into account.

best 2-in-1 laptops

For years, HP’s Spectre line of Ultrabooks and 2-in-1 laptops has been all about combining elegance and performance, and the 2019 HP Spectre x360 15 is no different. Packed with an 8th-generation Intel Core i7 CPU, Nvidia GeForce GTX 1050 Ti graphics and 8GB of RAM in its base configuration, you’re going to be able to do anything your work day throws at you – plus a bit of light gaming. However, the Spectre x360 is a bit heavy for a 2-in-1, so you likely won’t be using it in tablet mode that often. Put it in tent mode instead and watch some movies on its stunning 4K display.

Read the full review: HP Spectre x360 15T (2019)

best 2-in-1 laptop 2019

It might strike you as odd that a Chromebook is on a list of the best 2-in-1 laptops, and rated so high at that. However, the Google Pixelbook merges the two so flawlessly. It’s an impressive device that takes the Chrome OS platform and elevates it to levels never seen before, or even since. The Google Pixelbook is fitted with powerful internals as well as supports full Android apps, tearing down the walls that prevented Mac and Windows devotees from embracing the best Chromebooks

Read the full review: Google Pixelbook

best 2-in-1 laptops

We get it, the Pixelbook is enticing, but it’s also out of many consumers’ price range. In that case, the Asus Chromebook Flip C302 is a worthy alternative. Having introduced a touchscreen and hybrid design to Google’s cloud-based Chrome OS, the Asus Chromebook Flip is made better by its compatibility with Android apps. That’s right, just like the Pixelbook, you can use the Asus Chromebook Flip for Google Play apps, albeit after installing an out-of-the-box update.

Read the full review: Asus Chromebook Flip

best 2-in-1 laptops

The HP Spectre x360 isn’t just one of the top convertible laptops on the market; it’s one of the best laptops, period. There are few devices out there that amalgamate formidable components with elegant design quite as well as HP does here. The gem cut chassis will draw plenty of admiring looks in the coffee shop, while the powerful hardware will breeze through all of your productivity tasks. And, when you’ve had enough drawing in those looks of envy, you can flip it around into tablet mode to squeeze some late-night Netflix in.

Read the full review: HP Spectre x360

best 2-in-1 laptop 2019

If you’ve been looking for one of the best 2-in-1 laptops, but also kind of wanted something with some serious horsepower, you’re in luck. The Dell XPS 15, already one of the best Ultrabooks you can buy today, has been elevated to one of the most coveted 2-in-1 laptops – with discrete class Radeon RX Vega graphics to boot. What this means is that you can get a stunning 2-in-1, without sacrificing sheer power. And, while it is a bit expensive on the high end – it’s completely worth the price.

Read the full review: Dell XPS 15 2-in-1 

best 2-in-1 laptops

We’re not going to lie: we loved the original Surface Book already, so when we first heard that there was going to be a 15-inch Surface Book 2, we got excited. In the end, the Microsoft Surface Pro 2 isn’t the dreamiest 2-in-1 laptop out there. However, it’s still an impressive machine, only held back by a handful of necessary concessions. This 2-in-1 laptop features cutting-edge 8th-generation processors and Nvidia 10-series graphics for gamers and creatives alike. Couple that with its unique convertible solution, and the Surface Book 2 is a winner.

Read the full review: Microsoft Surface Book 2 (13-inch)

best 2-in-1 laptops

Sleek, slim and with strong specs to boot, the new Lenovo Yoga C930 is definitely well-deserving of a spot in the best hybrid laptops list. That’s without mentioning the fact that it now touts a 4K display model, so that high-end viewing experience and decent gaming may be had once users have gotten their productivity tasks out of the way. This 2-in-1 is a solid contender for the budget-minded, but if you do decide to go for gold, you might have to break the bank.

Read the full review: Lenovo Yoga C930

best 2-in-1 laptop 2019

It’s no secret that we’re fans of the Microsoft Surface Book 2 13-inch, seeing as how we only gushed about it earlier in this list, but what do we think of its 15-inch counterpart? With its long battery life, envy-worthy specs that will get you through most productivity demands and a lot of entertainment, and of course, its unique design features, we’re inclined to feel the same about it. Though this model isn’t for the budget shoppers: its base model with 256GB storage, you need to shell out $2,499 (oof!).

Read the full review: Microsoft Surface Book 2 (15-inch)

If you’re in the market for an excellent 2-in-1 laptop, but want to save a few bucks, look no further than the Lenovo Flex 6 14. For less than $1,000, you’re getting specs that will be able to handle most common workloads life throws at it – in a chassis that doesn’t just look good, but is rigid and even supports the Lenovo Active Pen. The only real downside here are the tinny speakers and the lack of Thunderbolt 3, but those are hardly enough to hold it back especially at that bargain price.

Read the full review: Lenovo Flex 6 14 

  • This product is only available in the US and AU at the time of this writing. UK readers: check out a fine alternative in the HP Spectre x360

best 2-in-1 laptops

Acer has a knack for designing affordable laptops that are reliable enough for typical productivity tasks and some viewing pleasures. They’re proving that with their cut-rate contender, the Acer Chromebook Spin 11, touted by many as one of the best Chromebooks that hit the shelves so far. Some concessions are made, understandably with its price tag of $330, including below average battery life. But for users on a budget who are unlikely to tackle processor-hungry work, this one’s a win.

Read the full review: Acer Chromebook Spin 11

  • Images Credit: TechRadar
  • Want more choices? Check out our list of the best laptop 2019

Gabe Carey and Bill Thomas have also contributed to this article

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