Parsons Life Science Design Lab

Bridging the gap between scientists and the rest of society. Attempting to make genetic data visualization simple enough so that any person can understand it.

Transcript

1. life sciences let’s talk about life sciences from a design-thinking perspective.
2. life sciences biotechnology neuroscience molecular biology bioinformatics microbiology genomics First of all, it’s Life ScienceS! There are many, these are just a few, and they look at different problems as well as different parts of the same problem. It’s like having a microscope that you can set to many different zoom levels.
3. juan enriquez a great moment that helped me understand why Life Sciences is going to be a HUGE deal in the future, was when I met Juan Enriquez at the Harvard Club of Manhattan. Juan is the founding director of the Life Sciences Project at the Harvard Business School. He also teaches, invests in biotech and writes books about life sciences.
4. What Juan told me when we met, and what I’ll never forget, is that a USB drive is the same as an apple (yes, the fruit). And they are the same in that both contain information we can manipulate. But more on that later.
5. Harvard Business School’s Life Sciences Project Juan Enriquez wrote an excellent book that explains in the simplest terms what Life Sciences are, and how they will change everything we know. There’s a more recent book that takes these ideas further, but “As The Future Catches You” is the best one in my opinion. There’s also amazing Ted Talks that Juan has given, where he uses humor and other analogies to break down his ideas in simple terms.
6. DB1KTT But don’t worry, I’m not going to torture you with the latest epidemic, what I call “DB1KTT”…
7. DB1KTT death by a thousand ted talks or “death by a thousand ted talks”. So you can check out Juan Enriquez’ talks at TED on your own time.
8. PCs DNA Binary code: 1s and 0s Genetic code: A, C, T, G information stored on drives (Kb, Mb..) information stored on living cells (Kbp, Mbp...) execution can lead to insights execution can lead to anything! But the most important take-away message here is that these two worlds, of PCs and DNA, don’t compete with each other. They are similar, yet different. But if anything, they complement each other.
9. And that’s what I had in mind when I took a job in a company from the sector. I wanted to be closer to that intersection of binary code and genetic code. So I joined that company, and right away…
10. I had what I call “the titanic moment”, which is the moment when one feels like on top of the world, and all one can see is opportunity. Unfortunately, this moment is plagued by optimism and a little bit of ignorance of potential threats.
11. So shortly thereafter, I was like this. Covered in paperwork, developing 10 to 15-year business plans that will probably never happen, working under an awful organizational culture with no transparency, questionable ethics, no accountability and no clear oversight on goals.
12. It was a very upsetting a depressing time in my life. This was the overall attitude around me, and it didn't make me happy.
13. I quit! So I decided to quit. I had my “Jerry Maguire” moment, which is covered in more optimism (a renewed, more sophisticated kind?) but this time with a great element of awareness of external barriers to success. ! This one creates risk but gives great empowerment to redefine things, and to make sure this time around, you will succeed and stay away from toxic individuals. It can get lonely unless you try to go and build a network of people who share the same vision and ideas.
14. I started my own company, and our first product called Taskflight, is a software as a service for teams that need efficient collaboration. ! I took all of what frustrated me in that awful job and made a software that can help people deal with a toxic company culture. ! So for instance, everyone in your team can see what and how much you bring to the table, and you can assign tasks and upload files to advance work from wherever you may be.
15. And when someone closes a task, you will immediately see a calculation in percentages, which indicates how closer you are to achieving your objective. ! That was something we did to get started, something that can now help me with the work of my next teams and projects. Now back to Life Sciences…
16. work on stuff that matters truly There’s a trend going around VCs, pundits and entrepreneurs, saying that you should work on stuff that matters. And so we have lots of companies coming up with supposedly “ground-breaking” things. But to work on stuff that TRULY matters, we have to ask ourselves the question: “Will it still matter 30 years from now? 50 years from now?”.
17. making things! Well, it turns out, the only way to approach that big challenge is to make things. To collaborate with others in not just combining things that exist, but to create new stuff.
18. I think the buzz and excitement around 3D printing is great, I love what it is doing for people, and the fact that we have these at Parsons. But 3D printing is still in its infancy, and it’s still a very limited space for people to make things. Engagement is limited to tweaking designs and executing a “make” function.
19. linearity design make It’s this linearity that we are confined to. I agree it is nonetheless impressive, but also very similar to just telling our computers and printers to churn out a paper for class.
20. linearity design make we are always dependent of what the printer, the medium, can do for us.
21. building inanimate objects and we are always dealing with inanimate objects.
22. life sciences: hack life! whereas in life sciences, the premise is that we can hack life! Just like we program computer software, we can now program genetic code to execute other functions.
23. linearity design make It’s not like this linearity where the function is always the same.. which is to “make” whatever is designed.
24. networked plasticity gather data visualize, analyze design, create make, re-make ACTG ACTG ACTG The model with Life Sciences is one where you take things that exist, you understand them, then modify them.. and since they are living things, they can create stuff for us. ! We can make anything with them! The medium (or the printer if you will) is DNA code (or molecular structures), so the limit is set by the capacities of life itself. ! *note: this “doodle” is an oversimplification of a plethora of sciences and their process. It would never stand a review from the scientific community, but it’s just a visual approximation for a non-scientific crowd to grasp the nature of working with DNA.
25. It’s just like having a set of Play-Doh. Remember play-doh?
26. We used to make these balls and then turn them into shapes.
27. and we’d play with the dough and we could create any kind of object we wanted. As far as our imagination would allow.
28. But then we could always round them up into spheres again. And we could start over the process if we wanted to.
29. A C T G Well, imagine that DNA is like a set of 4 Play-Doh colors, and that each color is a letter. So we have four elements, A, C, T, G. And we can turn those 4 ingredients into anything we want.
30. So when we were babies, there’s a combination of these 4 elements of DNA that said…
31. ACTGCGATCATGATACA “grow baby teeth” That is, they were lined up together to execute a function to “grow baby teeth”.
32. ACTGCGATCATGTATGAT “grow adult teeth” And then there is another line of code in our DNA, that combines these letters in another way, which tells our cells and our tissues to “grow adult teeth” and replace those baby teeth.
33. once you grow adult teeth... but of course, as we know… once you grow those adult teeth…
34. you are stuck with them for life! You can’t re-grow them.
35. In other words, with DNA once we make shapes….
36. we cannot roll those shapes back into spheres and start over. Otherwise we’d all be growing 6 or 7 sets of teeth over our lifetime.
37. how do we tell our bodies to do stuff? So how do we tell our bodies to execute those functions again? Remember, this code is already in us. It’s like having software that you can only run once. I.e: once “Baby teeth” is executed.. or “adult teeth” is executed, that’s it. Same for limbs, organs, etc.
38. codifying knowledge The answer is: by doing something we’ve always done, which is to make meaning of things.
39. conversion that helps us make meaning of stuff tacit explicit converting tacit knowledge into explicit is what enabled us humans to develop the wheel or light a fire. You achieve something, you replicate it, you understand how it was achieved and you give instructions so that other people can do it. You make it explicit! But first you need to know what’s going on in your observation. That’s the tricky part.
40. gather tacit data So you start by gathering “the unknowns”. Gather the data that you can’t make meaning of, and that you want to analyze.
41. In life sciences this happens with many different kinds of machines, but a simple one is PCR (Polymerase chain reaction), which is a process where we can basically take a very small look at a piece of life code. It’s like a DNA photocopier, in that it takes a sample of a living thing, and it copies its DNA in sequence to determine how that code (those letters) are combined. So we could, for instance, “photocopy life” and run it against a database of species to determine what kind of living thing we have a sample of.
42. A great use case of this, called DNA Barcoding, has been to go out and sample sushi to see if the description of the fish actually matched what was being sold. Turns out, most of the time, when restaurants claimed to sell White Tuna, they were actually delivering a much cheaper substitute, like the Mozambique Tilapia. ! In this case, it’s called Barcoding because you take a very small piece of the genome (the whole DNA with all of its genes), to identify the species. It’s like having a set of numbers like we do with barcodes to identify items in a store.
43. Fortunately, the cost of sequencing a human genome (and also other life forms as a consequence) has been dropping so fast, actually faster than Moore’s Law! ! Remember Moore’s Law, where the number of transistors was meant to double every year? That has been used in the PC age to reflect the doubling of capacity and the doubling of price drops every year. ! If the cost of a genome had followed Moore’s Law, it would cost over a million dollars today, but its cost is at almost $10,000.
44. So how does this relate to Parsons? And what are we trying to do with a design lab for life sciences?
45. the biggest bottleneck in life sciences data collection data analysis Well, it turns out that one of the biggest productivity issues that scientists are facing is actually in making sense of all that data that companies spend so much money to obtain. It is in that white arrow where the problem lies.
46. ! ! networked plasticity gather data visualize, analyze design, create make, re-make ACTG ACTG ACTG Visualize! The methods by which to visualize the data gathered are so hard to use, so technical, that they require someone who is well versed in very opposed worlds: the bioinformatic world (mostly programming) and the specific life sciences need (molecular biology, genomics, microbiology, whatever we are working with). ! Usually a bioinformatic does not have the scientific knowledge to help accelerate discoveries, and a scientist does not have the programming knowledge to improve the extracting of the insight they need from their data sets! It’s a problem most companies get stuck with, and real life solutions suffer as a consequence.
47. Look at a section of my genotype (a small portion of my full genome) as provided by 23andme.com ! This is an old-fashioned table list. 23andme is a consumer service and they actually do a great job and visualizing things for people to understand. But most companies that are doing serious genomic research obtain a simple data list in columns and rows like these. They have to find highly educated people to turn this into something useful. Big data? not as common in labs as you might think!
48. The standard is actually this! Something that NCBI (National Center for Biotechnology Information: http://www.ncbi.nlm.nih.gov) has made available online for free. ! A lot of companies build tools around this to boost its capabilities, but it only feeds the gap between raw data and insight. ! Try showing this to a shareholder if you work for a biotech company. Try showing it to your lab trainees, or your bioinformatics that need to understand what you’re looking for with your next analysis tool you want to build. What about your customers?
49. Perhaps the most sophisticated version of a visualization tool for genomes is this. The framework is called “Circos” (http://circos.ca) and it requires a software engineer, systems analyst or bioinformatic person to install a distribution package and run scripts to make this happen. ! This is so-called “Bleeding edge” but very outdated already. If we are to become a life code literate society, we need to do better than this.
50. This is a data visualization from 23andme, which matches my genes to their database that has geographical information on where my gene variations (my SNPs, pronounced “Snips”) have been in the past thousands of years. ! This is something we can all make meaning of, mostly because it uses something we all know about, which is geography. So we need to find something like this for complex things like DNA markers.
51. how do we build a design framework for scientists to use?
52. -access NCBI and download genetic data to graph ! -raise $600 and build a “DNA photocopier” We can get started TODAY. There’s a plethora of data waiting to be tinkered with. Or if we want to get people involved and engaged in something really cool, we can build our own PCR machine, with just $600, and go out and start sequencing things!
53. Beats a 3D printer any time! This thing can read genetic code and send it to our laptops. We are designers and design-thinkers, it is OUR job to make meaning of this.
54. -make data repositories with what we collect. ! -visualize them, make tools for scientists to use. ! -have companies test them. So we could build repositories that people can access, like the NCBI does. Then we could visualize them in many different ways, see what sticks and what doesn’t. And we could have a network of companies testing them to validate the scientific usefulness.
55. Of course, I’d make available free Taskflight accounts for the design lab, so we get organized and track progress of what we decide to do along the way.
56. let’s hack life code. Let’s do it! Let’s participate, organize trips to the Brooklyn Biohackers meetup and get ourselves in the game! ! They often organize an “open DNA Barcoding night”: http://www.meetup.com/Brooklyn-Biohackers/
57. thank you. @mmalisani mariano.malisani@vantagon.com We can create something that has the potential to become a standard in the scientific community. To have Parsons gain influence in a field where design has taken a very small role, and to enable discoveries that can change lives globally.