Notable Labs is working on changing the way cancer is treated by putting patients first. Notable screens thousands of combinations of FDA-approved drugs against a patient's own cancer cells and helps identify drug combinations for each individual patient that can be prescribed by their oncologist. By repositioning treatment as a patient-centered service, Notable labs is working on bringing together modern data science and laboratory automation to achieve the promise of combination therapy and personalized medicine. I spoke with Transon Nguyen to learn more about what goes on behind the scenes.
Q: What do you do at Notable Labs?
Transon: I’m the lead hardware/automation engineer at Notable, so I get to play with all the cool robots that we use to automate our work. My goal is to make our lab one of the most technologically advanced high-throughput labs out there, so that we can identify better treatments for cancer patients faster. My day-to-day varies; I could be in the lab crawling under tables installing a new robot, or coding in the office, or helping run lab work every once in a while (so I can better understand it and eventually automate it). But there’s a general theme of “automate everything” in my work, which includes:
- Working with our scientists to translate the assays they’ve developed from a manual process to a fully-automated robotic process
- Evaluating new technology that we can bring in to improve our lab (including TetraScience!)
- Getting our current technology as user-friendly as possible so that anyone can feel free to walk up to our robots and run them
There’s another theme to these goals, and that’s making our scientists’ lives easier. We only have so much executive function in our brains to spend; if you tell me to manually pipette 55 μL of liquid from point A in one plate to point B in another plate 200 times, I’m guaranteed to mess it up at least once. We’ve got some brilliant scientists, and automating away some of these more mundane tasks will give them more time to analyze their data, synthesize conclusions, and come up with new experiments and assays to run.
Q: Notable Labs isn’t your typical cancer research lab. What do you think makes you different?
Our focus has been, and always will be, to put patients first. That’s one of our core values, and it drives a lot of the decisions that we make as a company. This may sound obvious to an outsider looking in at a cancer research company, but at times we find that patients are at a dead end with no one advocating for them, fighting for them to find something better. Notable was created to be that driving force, to provide the scientific rationale for a patient to be prescribed a potentially better treatment.
Another aspect that makes us different is our technology. We’re in San Francisco, the heart of tech startups; tech is in our DNA, from our cloud-based LIMS (laboratory information management system) to our dynamically scheduled robotic workcell. I can’t give enough praise for our scientists, who are very open-minded to bringing in new technologies that can drastically change the way they work. We are often at the frontiers of technology in the life sciences; a good example of this is our high-throughput flow cytometry assay, which we run across a spectrum of very heterogeneous patient samples. I’m not aware of many others that are attempting to do this, and we find ourselves running into a slew of new (and interesting!) problems that no one else has seen.
Q: How is cancer research (or biotech/pharma in general) changing, and why is that important?
One change that I’d like to highlight is the increased interest in functional testing and personalized medicine; there’s always been some progress on both fronts, but nowadays we’re seeing a faster rate of innovation coming out of both academia and industry. We’re starting to look beyond more traditional targeted therapies that are based largely on genotypic screens, and instead pursuing more realistic tests in the lab that can better predict how patients will react to a given treatment. This includes, but is not limited to, developing in vitro cultures that more closely mimic essential functions of an organ (this is the idea behind “organs-on-chips”, a fairly new and exciting field of research), or running high-throughput screens on ex vivo cultures straight from a cancer patient, which is what we do.
We even see the structure of clinical trials changing to accommodate these priorities. There’s the relatively new concept of an adaptive clinical trial, which is essentially a clinical trial designed to change over time based on how the trial’s participants respond to treatment. To me, this shows a shift in how we approach drug discovery; with this idea that it’s important for us to look for the right treatment for the right population of people, rather than trying to find a magical silver bullet that works for everyone.
Q: Notable is implementing cutting-edge technology to achieve your goals. Can you tell me about your “stack”? What combo of equipment and software does the lab use?
Our core languages include Ruby (specifically Ruby on Rails), Python, and C#. The short story is that we use Rails and Python for most of our backend, which includes the LIMS and data pipelines, and C# for the robotic workcell. We use a nifty piece of scheduling software to interface with our robots called Green Button Go, created by a company called Biosero. There’s a lot of tight communication between the robots and our LIMS which allows for flexible workflows.
TetraScience is another key part of our automated drug screening platform. Because TetraScience gives us complete visibility into the status and stability of instruments, we have the dashboard up on our lab's flat-screen TV around the clock.
As a hardware person I have to talk a little bit about our custom hardware--most of the time we’ll use well-established, commercially available lab instruments since the manufacturers have done all the work to validate their product. But there exist edge cases where the best solution is to make our own hardware. I think the Maker community has done a lot to make custom hardware more accessible to everyone, including us; it’s amazing how fast you can create something with a 3D printer, some t-slotted aluminum, and maybe a Raspberry Pi or Arduino.
My personal favorite is our automation-friendly fridge: we bought a mini-fridge, ripped the front door off, and mounted a custom sliding door in its place so that our robot arm can open the fridge, grab a plate full of cells from there, and then close the fridge door.
Q: Who are the other fast-moving, innovative biotechs doing inspiring work with new technology?
Transcriptic, Ginkgo Bioworks, Zymergen, Emerald Cloud Laboratory, Recursion Pharmaceuticals, and Synthego are a few that come to mind. Also, they’re not exactly biotech but I want to give a shout out to Hampton Creek; they’ve got some great tech that overlaps with the life sciences, and I feel like they’re pushing the boundaries in food research. These are all off the top of my head and I’m without a doubt missing many others--it’s a great time for innovation in biotech!
Q: You are having a strong 2017. You just received the PM360 Elite Tech-Know Geek award and one of your cofounders, Matthew De Silva, was named a Disruptor. Matthew was also recently named a Forbes 30 under 30. What else does 2017 have in store for Notable Labs?
This is our growth year. More patient samples in the door, more partnerships, more robots, more people on our team. We’ve been a little quiet over the past two years, and I’m thinking a lot more people will know about Notable Labs by the end of this year.
Q: Are you hiring? What types of folks are you looking to add to the team?
We’re hiring in almost all areas! Automation engineers, full-stack engineers, data scientists, clinical lab production scientists, research scientists, and more. You can see our job postings at http://notablelabs.com/careers, or feel free to reach out to our talent team at firstname.lastname@example.org.