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Software Start-Ups Aim to Automate Bio Labs

Earlier this month, major tech consulting company Cambridge Consultants announced a partnership with Synthace, a small, UK-based software start-up. According to the press release, the collaboration is designed to “unlock the full potential of biology” by increasing adoption of Synthace’s operating system and programming language for biological experiments.

The idea of automating wet lab work—such as pipetting microliters of liquid, pouring gels, or mixing reagents—is not new to biology. Yet adoption of expensive robotic systems has been largely limited to pharma companies that have pockets deep enough to afford them. Thus, the manual, painstaking work of most wet labs continues.

In sharp contrast to the complexity of even a simple biological cell, “Biotechnologists engage with a handheld pipette, an Excel spreadsheet, and a pen and paper,” says Tim Fell, CEO of Synthace. And because of that tradition, experimental methods are recorded in text files and results are stored in datasets whose formats vary from lab to lab, making them hard to combine.

Several young companies are now working to bring biology-specific software and programming languages to the lab in order to automate such tasks. They hope to not only speed up experiments, but to improve their reproducibility and standardize data gathering so data can be analyzed using machine learning techniques. “Biology is so complex, our brains just can’t see all the interactions, so we’re going to need machine learning,” says Fell.

“The future is really about generating larger datasets and having access to more powerful computational tools,” adds Max Hodak, founder and chief technical officer of robotic cloud lab start-up Transcriptic. “I’m not sure the way most academic research labs [currently operate] can lead to that improvement.”

Synthace, a 28-person company established in 2011, created a platform called Antha, an operating system and programming language designed to allow scientists to engage with biology in a completely new way, says Fell. The software is device-agnostic, so researchers can use their own favorite mass spectrometers and centrifuges in combination with the software. Using Antha to code an experiment, one can look at dozens to hundreds of variables at a time (instead of one), and there is no need to manually track all the experimental details. Instead, the software automatically records everything including reagents, temperature, and timing, and saves the data and methods in a standardized way. 

Transcriptic, a 40-person start-up founded in California in 2012, provides a robotic cloud lab service that allows researchers to log into the company’s automated labs on demand. Each robotic workcell in the facility (soon to be sold commercially to large companies) is powered by custom, open-source software. Users interact with the platform via a Web interface linked to custom databases. “It fulfills the traditional role of lab [software] and the lab notebook,” says Hodak, who was recently announced as a co-founder of Elon Musks’s new venture, Neuralink.

Behind Transcriptic’s Web interface is custom software called Transcriptic Common Lab Environment, or TCLE, which operates the infrastructure. This set of APIs interacts with the lab, checking inventory, executing protocols, even autoformatting data. TCLE is powered by Autoprotocol, a data standard developed by the company and subsequently released as open source.

The robotic lab itself is made up of approximately 20 devices including pipetting systems and plate readers that can be combined to perform a huge range of experiments, says Hodak. “The platform is extremely open-ended.”

And here’s why these types of start-ups matter: Just as most of us don’t care how a printer works, a scientist using these platforms doesn’t have to track (or care about) every detail of an experiment. The software does it for her, and saves it in a way that can be stored and shared with others.

“Say I want to assemble 40 genes into an organism. Then all of the complex details [involved], be it liquid handling or using the equipment, just disappear from view,” says Fell.

Synthace offers both an open-source version of its language, and a commercial version including the OS and support. Most of Synthace and Transcriptic’s clients are currently Big Pharma companies, but both claim they are working their way down to smaller users. Fell hopes that as the costs of robotics systems for biology decrease, more academic centers will use the platform.

Photo: Shanghai Key Laboratory of Regulatory Biology

Smartphone-Controlled Cells Keep Diabetes In Check

Smartphones can already control homes and cars, and diagnose diseases. Chinese and Swiss researchers now show that a smartphone can command engineered cells implanted in diabetic mice to produce insulin.

The researchers demonstrated a clever closed-loop system in which a digital glucometer transmits data on the rodents’ blood glucose levels to a smartphone, which processes the data and then signals the implanted cells to deliver insulin. This is a step towards “a new era of personalized, digitalized precision medicine,” says Haifeng Ye of East China Normal University, who led the work reported in Science.

Cell-based therapies are a radical new medical treatment option being investigated by researchers. The idea is to turn cells into disease-fighting weapons by engineering them to produce therapeutic chemicals and proteins that they would churn out once implanted in the body. Living white blood cells, for instance, have been designed to fight cancer, HIV, and other diseases. Hundreds of cell therapies are undergoing clinical trials. But none can be controlled from outside the body.

Ye and his colleagues have come up with an innovative way to add smarts to cell-based therapy. They chose diabetes as the target disease.

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US Department of Defense announces program to fund research that aims to improve learning peripheral nerve stimulation

DARPA to Use Electrical Stimulation to Enhance Military Training

It takes years to learn some of the most important national security skills, such as speaking foreign languages, analyzing surveillance images, and marksmanship. The U.S. Department of Defense (DoD) wants to speed up that training process using electrical stimulation to enhance the brain’s ability to learn. The Defense Department’s research arm, the Defense Advanced Research Projects Agency (DARPA), today announced it had awarded multimillion-dollar contracts to eight university groups that will study and develop such technologies. 

DARPA wants to see a 30 percent improvement in learning rates by the end of the four-year program. Studies will be conducted on human volunteers and animals. DARPA did not disclose the total value of the research contracts. 

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A woman stands on stage at Facebook's developer conference. Behind her a giant screen displays the text: "So what if you could type directly from your brain?"

Facebook Announces "Typing-by-Brain" Project

First it was Elon Musk, now Facebook. Suddenly, all the big Silicon Valley players want to get into brain tech. 

Yesterday Facebook announced that it’s working on a “typing by brain” project. At its developer conference, Facebook executive Regina Dugan promised that this brain-computer interface will decode signals from the brain’s speech center at the remarkable rate of 100 words per minute.

Dugan, who runs the Facebook moonshot lab known as Building 8, said the technology for decoding brain signals will be non-invasive. That sets Facebook’s efforts apart from Elon Musk’s mysterious new Neuralace company, which is working on tiny implants called neural dust that would likely be embedded in the blood vessels of the brain. Dugan said that Facebook has no plans for an invasive implant, saying, “Implanted electrodes simply won’t scale.”

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Sparking Memories With Electrical Stimulation

For years, brain researchers have experimented with electrical stimulation as a way to improve memory, but with mixed results. The problem with these approaches may have been a matter of timing, according to a report published today in the journal Current Biology. Electrical stimulation should be delivered to the brain precisely when memory is predicted to fail—and not when a memory network is operating efficiently, say the authors of the report.

The proof-of-concept study offers the first clear indication for when to stimulate the brain in a way that affects memory. The study also marks the first major milestone of the U.S. military’s $77 million program to develop an implantable device that improves memory for people with traumatic brain injury (TBI). 

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Illustration shows a man's transparent torso with a battery implanted in his shoulder and wires leading to a chip implanted in his brain.

Treating Depression With Deep Brain Stimulation Works—Most of the Time

Here are three things we know about deep brain stimulation (DBS) as a treatment for severe depression: 

1. When the pacemaker-like brain implants do help depressed people, they get dramatically better. “I have patients who got their implants 10 years ago now,” says Helen Mayberg, a professor of psychiatry and neurology at Emory University and a leading researcher on DBS for depression. “These people get well and they stay well,” she says. 

2. Unfortunately, they don’t help everybody. Experimental trials by Mayberg and others have consistently had a subset of people who simply don’t respond to the treatment. And two big industry-sponsored trials were counted as failures by the companies, squashing hopes that the treatment would soon be available for mainstream clinical use.

3. Researchers must figure out why some depressed patients respond to DBS while others don’t; otherwise their experiments will never lead to a truly practical treatment that can gain regulators’ approval. And two new studies with good response rates show that researchers are making progress toward that understanding.

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Algorithm Aims to Predict Bickering Among Couples

Smartphone apps could eventually predict arguments among couples and help nip them in the bud before they blow up. For the first time outside the lab, artificial intelligence has helped researchers begin looking for patterns in couples’ language and physiological signs that could help predict conflicts in relationships.

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Winners of Qualcomm Tricorder XPRIZE hold check

Brothers Win XPrize for “Star Trek”-Inspired Tricorder

The results are in! Wait, first we should double-check that we’re reading from the right cue card

The winner of the long-awaited Qualcomm Tricorder XPRIZE is Pennsylvania-based Final Frontier Medical Devices. Final Frontier developed a mobile device able to diagnose 13 health conditions while continuously monitoring five vital signs. The award was announced yesterday at a ceremony in Los Angeles. 

“We could not be more pleased with the quality of innovation and performance of the teams who competed,” said Marcus Shingles, CEO of the XPRIZE Foundation, in a statement.

In 2012, the nonprofit company XPRIZE and U.S. chipmaker Qualcomm launched the competition to incentivize companies to build a medical tricorder–a portable device to rapidly diagnose medical conditions—right out of the scenes of “Star Trek.” The original field, comprising 312 applicants, was narrowed to 10 finalists in August 2014.

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Illustration shows the human brain depicted in glowing blue circuits.

5 Neuroscience Experts Weigh in on Elon Musk's Mysterious "Neural Lace" Company

Elon Musk has a reputation as the world’s greatest doer. He can propose crazy ambitious technological projects—like reusable rockets for Mars exploration and hyperloop tunnels for transcontinental rapid transit—and people just assume he’ll pull it off. 

So his latest venture, a new company called Neuralink that will reportedly build brain implants both for medical use and to give healthy people superpowers, has gotten the public excited about a coming era of consumer-friendly neurotech.

Even neuroscientists who work in the field, who know full well how difficult it is to build working brain gear that passes muster with medical regulators, feel a sense of potential. “Elon Musk is a person who’s going to take risks and inject a lot of money, so it will be exciting to see what he gets up to,” says Thomas Oxley, a neural engineer who has been developing a medical brain implant since 2010 (he hopes to start its first clinical trial in 2018). 

Neuralink is still mysterious. An article in The Wall Street Journal announced the company’s formation and first hires, while also spouting vague verbiage about “cranial computers” that would serve as “a layer of artificial intelligence inside the brain.”

So IEEE Spectrum asked the experts about what’s feasible in this field, and what Musk might be planning. First, though, a little background.

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Round up of several computer models aimed at improving medical decision making

IBM, Intel, Stanford Bet on AI to Speed Up Disease Diagnosis and Drug Discovery

Big players in software are putting their weight behind artificial intelligence as a way to improve health care decision making. New computer models stretch the limits on how early doctors can spot disease, or how quickly molecular compounds can be screened for use as new drugs.

In the past week, news of several such models crossed IEEE Spectrum’s desk, which we’ve rounded up for you here. IBM announced a computational model that predicts heart failure, Stanford University reported a deep learning algorithm that predicts the safety of drug compounds, and Intel announced a competition to find an algorithm for early detection of lung cancer. 

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The Human OS

IEEE Spectrum’s biomedical engineering blog, featuring the wearable sensors, big data analytics, and implanted devices that enable new ventures in personalized medicine.

 
Editor
Eliza Strickland
New York City
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Emily Waltz
Nashville
 
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Megan Scudellari
Boston
 

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