David Jennions, a reformed physicist, shares his career shift and current role as the head of Systems Engineering for a leading biotech company, Synthego. Synthego is a corporation dedicated to making digital biology a reality by doing what he calls, “Building the factory behind the product.” In this episode, we will get into mind-blowing modern technology such as CRISPR, a tool used for gene editing. To understand more about what this means, tune into this episode as we discuss behind the scenes of how the health industry has the potential to move away from general healthcare solutions, and move into more personalized treatment.
1. Digital biology
3. Gene editing
4. Black Holes
5. Modern medicine
6. Personalized medicine
1. Synthego Corporation
5. Society for Laboratory Automation and Screening (SLAS)
6. Integrated Vehicle Health Management (IVHM)
7. Black Holes and Time Warps by Kip S. Thorne
8. Kardashev Scale
Carlos: David, thank you so much for joining me today. It's a pleasure to have you on the show.
David: Great to talk to you, Carlos.
Carlos: David, you and I have been talking for couple of weeks and has some back and forth and I said earlier I'm really grateful because you stuck it out with me to record this. And as I was preparing for this episode there's been a lot of research and a lot of understanding that I had to do in order to be able to ask you questions that at a level that is intellectually at your level. It's been impactful to me just because I had to go a little bit deeper than I usually go, so anyways thank you. And then just a way to get started, I think before we start talking about our main subject today which is going to be around processes and systems behind delivering hardware and software products within the industry that you're working, in which as an industry is very interesting to me and also for Gistia as a company, and we want to really learn more about it. So anyway, I am personally very interested in this conversation so without further ado why don't you tell me a little bit about yourself and your background. How did you get into tech?
David: Sure. It's a little bit of winding path. I typically introduce myself, reformed physicist. My undergraduate work was indeed theoretical physics. And I actually slowly became more interested nothing but solely about the fundamental science but how you look at it. How you created instruments and tools to look at the stars, look at molecules, look inside the human body. I'm slowly drifted into more the instrumentation of scientific measurement.
I moved to London after doing that at the University of Cambridge, to do a doctorate in medical imaging looking to create a novel imaging system for detecting breast cancer; so kind of combining a little bit of anatomy and a little bit of biology with the scientific measurements that I have before. Couple of years later I had a reason to go back to California and really by circumstance happen to fall into biotech with the moved out to California, and that was a laboratory automation architect for production facility making synthetic DNA. And this is where we start a story that I think we're going to come back a little bit which I making cross pollination of ideas between different industries. Especially within biotech bringing in ideas that are kinds of standard and mainframe for other industries, the automatable silicon for example that they mass manufacturing. And really where we're only just getting to inside the biotech industry for just doing a little bit more of what scientists do in needing to make that step change.
Carlos: Just to put things into perspective, astrophysicist, like damn. You know that's, I would put a pin on that for a second, and then put a pin on how you were interested in building the tools for the craft for the science. So I'm starting to see this, you are zooming in from, I'm visually thinking of it as a funnel, you're thinking of the big picture and then you're zooming in literally into the human body from the stars to the cells basically. But before we get into it just want to put a quick thought here is that, tell me some of the impact that you think is possible in our lifetime with the work that you're doing in the lab or that is as an industry is happening at the lab. You know, let's keep it like down to maybe let's say three items. What are some of the top three things the industry is able to do for humanity?
David: So let me take one step back because there is an adage that's kind of talked about sometimes about the 1800s were really about chemistry. The 1900s we seem to had large gains mostly in the realms of physics. The idea is now that 2000 is a biology, and the reason why kind of that series of events and mass iterations happened is because we've needed all the foundational technologies that we got from one of the sciences in order to make leaps and bounds in another. One of the examples in that specifically with inside biology is the amount of… space, the amount of different bits of information we have to collect and talk about when talking about the cells or even tissue interactions has only become possible with our level of computation that's happened in the recent decades.
So to get one of your examples, drug discovery is mainly a format of a little bit more gas and check we'd like it to be taking one cell type and applying a large library of chemistry to it and just seeing what happens. The difference being with large data sets and being able to do analytics on it properly, you can start drawing patterns and doing real deep understanding about what is going on in the system you are interrogating versus just, “Ok, we're happy with the answer we've got now. Let's move on.” So that's one side of it kind of as an example on drug discovery.
Another side of it is because we not used to doing mass manufacturing on larger scales and even down again to kind of again silicon wafer scales. The idea are of now playing with biochemistry as we can create molecules and even to the point of there's actually an eye gems computation each year of trying to do logic gates and things like what you'd normally think of in transistor logic but with bacteria such that we can control biological systems to do logic gates, to do problem solving, to control what's going on that level to try and solve problems for us. So those are the two big ones I see.
Carlos: So the impact of those could be humanity changing when they are out of the lab and say put into production if you would in the future because I think the forefront of that is still, right?
David: Yes, indeed. The impact of all of that is something that's generally referred to personalized medicine that rather than trying to create health programs, drug programs and even surgeries that are good for general population. Knowing and being able to measure specifically what your body is doing and deriving a diagnosis and prognosis and what we do to it for that system versus having to do it in kind of more holistic ways, which should improve just generally our reaction to disease in terms of awful loss of different kind of problems with the human body.
Carlos: So the reason I kind of wanted to kind of get to that is that the impact of this industry could change the fate of humanity. And I know that I'm sounding a little bit hyperbolic here or exaggerated but the reason I am saying all of this is because this is almost a calling, like I'm trying to call on engineers, on developers, on technologists to get interested in this. There is a world beyond just being an expert within a technology or a framework. But there is really impact as technologists and we can create as technologists as experts within our fields. We can help move the needle with this sort of progress for the future. I want to start off with that because you're somehow inspired to look up to the skies, to look up to the stars and because you were able to do that now, you are helping us figure out what the insides look like as humans. That to me is uniquely inspiriting like being able to derive that inspiration from again could be on and then turning that inside, introspect into ourselves on how we can be interested and excited about us. So anyways, I just wanted to start off with that.
David: Yes. And I absolutely I agree with that, not sort of I mean by kind of rebuilding our levels of scientific and engineering knowledge to the point of ok we can have this base of tools of different engineering disciplines but what we are driving towards and I feel very rapidly is actually serious impact on the biological condition on people's lives, on healthcare, and on all these things. But it requires people from all of these diversity from backgrounds to add their skills into it to actually make that work. Biologists sitting by themselves kind of on the sidelines for kind of a century or so need people to get involved and be excited about the difference that could be made very rapidly by bringing these different ideas, these different engineering skillset.
Carlos: And we're going to talk just about that. I think we're going to get into that right now. So before we get into some of the processes and systems I would like to get an idea of what Synthego as a company does. What do you do and tell me a little bit about what role you played within this? If we think of this ecosystem, right, what role do you play there?
David: Ok, so Synthego is dedicated to making digital biology a reality. One of the things I was talking about earlier was that drug discovery has generally been a brute force effort about taking some target cells, the cell you wanted to affect change in, putting a large chemistry set on top it and trying to draw conclusions. And moving through the last stage of drug discovery kind of classification doing some optimization making sure that it's safe and then all clinical trials. One of the biggest problems with doing that though is where is the chemistry set is fairly easy to create. We've been able to do that for large number of decades. Creating the cells that you want to test against, creating a model of what the problem is in the first place is really rather tricky. They are kind of hard to culture and thus typically taken on the scale of months to years in some cases to create the one that you could start this testing process with adopting a really quite wonderful defense mechanism in bacteria. CRISPR is a technology that now allows us to directly edit the genome dramatically shortening this period between here is a problem that we can see in nature, here is something where we can actually test against trying to do that translation.
Synthego is a combination of hardware, software, biologist, chemist kind of the four package. And what we've done is we're trying to take the synthesis, the creation of this molecule of RNA that CRISPR and scale it up such as to provide academics, to provide these searches, and to promote commerce. This tool kind of in larger quantity but the internal structure we have is trying to bring all of these different disciplines together to make the product useful. So we can synthesize it we have engineers building equipment, we have software engineers writing a software and we have the scientists trying to push the boundaries and understanding the end product forward. But what we have in the middle is something called systems engineering, and that's the grid that I had of trying to coordinate all the different pieces of engineering and science to make a manufacturing plant and to make mix commercial entity that really scales, works and understands what it does. So trying to make all these different bits talk together.
It's surprising how some of the different disciplines of engineering as they've gone through university and the early stages of careers how they learned talking almost completely different languages. And that's where I fit and that's where my team fits in the middle.
Carlos: So one thing that is more interesting to me is everything that happens at the forefront of this process and you know looking at the big picture I think we're talking a little bit about the end result here. But I'd like to get an idea of if you can walk us through it again, and I think I ask you for a favor of try to simplify for people that don't know much about this topic. Tell us about what is the usual process to develop a medicine right. We're just developing a thing, I told you earlier about a story and actually I think it might be a good way to explain my question. Last week we had a gentleman from ArcherDX, his name is Doug Wendel. And Doug and I we're talking about a very interesting story where they have found a patient that needed a special type of treatment that was not covered by insurance. They went out their way to help this patient, and they did a treatment for the patient. But he explained to me that basically it was a specialized sort of treatment because it wasn't something that regular cancer treatment would be able to solve. Anyways, she didn't get a coverage, they went in as company and they helped her. They covered the treatment. But treatment consisted of doing genetic testing on this patient and then identifying what was wrong and what was the cause of the cancer then they identified that, and maybe I'm going to be botch this again, but a certain strands of here DNA were making the body create extra specific protein that again resulted in her cancer. But they were able to identify exactly what protein, they were able to identify which part of her DNA was causing this and they were able to fix the problem by identifying a drug in the market that repressed the protein. By the way you're probably going to explain this to us even if it's not related to your day to day but I am curious because it might impact some of our own understanding overall. But how do we create drug that we know will suppress certain proteins. So how do we do that, how do we test over and over to see which one. It is a bit of a walkthrough for dummies if you would as to how that works, how the process even happens.
David: And so what you're describing is a very good example of what we discuss as being personalized medicine. You can take a person, a couple of cells from them, examine the DNA in that, see what the repercussions of that, see what the variants in it, see how the cell is either the healing or has some variants therein, compare that to a model that you already have and go, “Ok, we see that these variants are creating these proteins wrong.” And ok, that's the upfront measurement bit for the patient. Luckily, in the case that I think is what you're describing there was a drug already available decreasing that protein or that halfway. In a different way for a different case that given it solve the same problem was very useful to your patient. And again, matching those up is what we consider kind of personalized medicine.
In the case there wasn't a drug already available in the market. Well, you know what the variant is inside the cell that's causing this background thing. That now you want to test your wide world of chemistry that we don't fully understand about how it interacts with the cell so you want to test everything that you think is safe. You want to test across a broad range and for that you need a large amount of target cells. The quickest way to get there is simply to take the genome that you found in your target patient and create an entire number of cells with exactly the same genome. Unfortunately, that ends up being really tricky because the way cells grow. But what we can do is with CRISPR we can take a perfectly healthy primary cell and just put the editing that is the protein that we're interesting of finding out about. If we do that we can then make a large bulk of cells which we can test our chemistry set against and move that through our clinical pipeline. And that just simply looks like, we take ourselves, we take a specific molecule and chemistry that we entrust and thinking has therapeutic benefit combined it to but we do that across let's say hundreds of thousands to millions of molecules that might have therapeutic benefit. We narrow that field down to a couple of hundred that actually affect the protein we're looking for and we continue those on three clinical trials. The thing is that upfront process probably takes a year or so, on the downstream repercussions, the downstream clinical trials can take up to decades. But all of that only happens after you can contain your problem to a single cell and replicate in such that you can do the base biological test against it. This is gain where CRISPR comes. Once we can edit these cells in isolation and to a whole degree and accuracy, that then enables the rest of the pipeline to work much more smoothly than the cross pollinating and working with virus is in other ways of doing gene editing that the entire pharmaceutical industry has have to work with in previous decades.
Carlos: So moving on to try to bridge the gap as to how engineers or how this multiple disciplines can make an impact. Let's talk a little bit about your day to day. The science is the tip of the arrow now. We've got the science. Now, how does system engineers support the business in particular Synthego? I know that from a high level you guys as a group of engineering it's basically bringing different engineering roots in making a factory if you could think of it that way. That works, right, when you have software, electrical, mechanical engineers. But answer in your own words, how does engineering support the business and how do these teams come together.
David: So systems engineering is a term that's co-opted into a number of different areas and different disciplines, but I go back to what I consider old school definition which is literally it is a field of engineering that tries to bring other engineering disciplines together. So, ok we've been talking about the science and the end result of all of it but what my group is mainly focused at is building the factory to make this product, to make the molecules that we send out for the gene editing. And what that involves is bringing, again the kind of the hardware, the software and the science together to make sure that what you're building as a factory is well understood and well controlled such that again what you ship is accurate and precise for what it intended to send. My direct group contains scientists who understand the difference between doing something waltz on a bench and doing it in a factory which is again a kind of dedicated science in itself, that translation. Then engineers to make sure that we've qualified and tested all the hardware and software, process engineers that monitor kind of movement of material through the factory and make sure that standard manufacturing metrics like cost of goods or turnaround times, or past yields are all contained and controlled. And then, yes, project management as well looking at the pipeline of changes we want to make and updates we want to make such as that the different research and development, engineering groups, and scientists who work behind us all having a nice neat pipeline through such that we can continuously improve our factory.
Carlos: Do you think that there are ideas that could have been learned from the industry manufacturing design world and the software world in order to deliver products that, again a hardware and software product, in this industries not as easy as say. You are building a very advance, how would you take from those industries some lessons learned.
David: That's the interesting point I was making very early on our discussion about bringing in ideas from outside sciences and outside of engineering fields. Biotech is only a term that's existed really for about 30 years now as biotechnology. In terms of laboratory automation kind of a more of a factory sense. I would say it's more like 15-20 so as people to try automate factory and automate around biology and chemistry it's a really young industry. This means that they are learning everything from scratch again in the most parts unless you cross pollinate ideas in from other fields. Is there a kind of rocket surgery about making a production plant. We've been at the tip of industrialization and making factories for century or even longer bringing in ideas of things like from software and manufacturing plant. These are key ideas that if you're simply a scientist trying to scale up what you do from a bench with a couple of robots don't really occur to you. Making incremental improvements and doing Agile methodology, all of these ideas haven't really been cross pollinated into the biotech sphere up to this point but can have a huge impact in of themselves. So the more we can get those ideas in, the more we can cross pollinate everything that we have already discovered in the other industries. The quicker advances will be with inside the biotechnology area.
Carlos: And as you say that, I mean there are new techniques. You know, for example 3D printing, retaskable components. There are a lot of new things that are happening that could influence this world tremendously.
David: Yes, and I think this is kind of where we go with this conversation because the rapid iteration is something that again is kind of cross pollinating through the different engineering fields. Unfortunately, the more advance technologically you can be in the greater number of disciplines. The bigger the multiplier is to how fast you can move. And trying to keep these days actually with advances in software engineering, in manufacturing engineering, in hardware engineering is to how you prototype, how you run projects, how you launch things, is a significant challenge.
Carlos: Do you think that there is a, this question is hard to ask. By the way, I don't know if you've noticed but for everybody listening we do have some questions that we kind of plan ahead of time but this conversation has taken a bit of a turn in the sense that it's becoming more interesting to talk about the core of impact. And gain, talking about this mix of the multiple disciplines than to talk about specific; I was going to ask you about things like using emulators and so forth this was going to be to detailed into that, for example how does the software team deal with the fact that sometimes hardware doesn't exist yet. But that would be too trivial so I want to challenge ourselves to think of like, how can we bring more people from other fields to be interested in this if as you said earlier in the biologist can't do this by themselves. They need the rest of us with our ideas, with our knowledge with again cross pollination from other areas. How can we motivate them to see that this is one of the most groundbreaking industries in the world at this point in time? That not only are they going to be making an impact in today but a huge impact in tomorrow while at the same time becoming probably more experts than they are within their field. You're not going to lose any status of as an engineer or a software engineer. You are probably going to create new tools for this industry. How do we motivate them?
David: It's an interesting one. I think in engineering fields we are slightly blinking in our view as to what the applications of the engineering discipline are. So for example, certain types of coding solutions, certain types of algorithms only apply to certain types of problems. And that's something we need to breakout the mold of. The range of scientists, the range of industries that are now supported by significant amount of data analytics in terms of data structures, in terms of algorithms running them, in terms of AI. And also, ok that's the software world, of hardware world of things like rapid prototyping making sure that you can actually make all of your equipment modularized to support it better. These are ideas that are unique to any of these industries and so you have to have a little bit of education, starting with education of there is not one place to apply these solutions. You can go and find any problems interesting to you. But on the flip side as employers we have to advocate for just because you are a circuit board or an electronics engineer. You have to go down the road of doing the printed, doing the fabrication forms. We have other interesting problems over here and being vocal in recruiting in to say that we have the same sort of issues.
Carlos: And this has been a very interesting, not only eye opening experience for me of having you on the show. Everybody who listens to the shows knows we do a pre-interview and we prepare for these interviews because we want to get the most out of your time and we give the audience the most value. But I got to tell you I've got a ton of value for myself out of this because it has inspired me even to make company decisions that we're making today because of this sort of inspiration. So anyways, I have two more questions for you and have a kind of a party question be in. But, you know, what's the most fun part about your role? What's the most fun and also most fulfilling that you get out of your role?
David: Not to want to be repetitive but it's exactly what we've been talking about the whole time. I love the interdisciplinary part of my role specifically in seeing people who have very diverse and unique educational background and experiences come together and cross pollinate ideas such that, “Oh yeah, we solved that problem 10 years ago over here.” The solution applies to what we are doing today to a bunch of people who would never thought about the solution in that way. I talk amount of people who do laboratory automation never stop their university careers thinking that they are going to go into laboratorial automation. We all take right hand turns at some point. But it means it's a collective of people who've just followed what they are interested in doing and want to learn more about that diverse nature and diverse problem solving. Bringing that together to create something to this, again so impactful, it's just I find day to day incredibly enjoyably challenging.
Carlos: You know, when you started talking about your past in astrophysics and your interest in that world it really made me think of a path that I am personally following. I've been reading a lot about astrophysics myself from like. Astrophysics is weird, I'll put into that a second. I've been reading a bunch of books in astrophysics that are way beyond my understanding by the way. It takes me, like I have to read a page like 4 or 5 times to grasp what it's trying to say because I could barely understand half of it. These are not even books that are explained in the math because then that is another language. But I like to understand this concept of gravity and so forth but when you start talking about, so there is something to be said about curiosity like being curious in like. And I think that not only curiosity leads us to paths that we wouldn't otherwise have gone into but it leads us to, you know, hopefully to some level of success whether it's intellectual or not. But curiosity for me is like the most important thing that as a human, as a introspective type of person, that curiosity is kind of essential to me. Anyways, so hearing you talk about again that curiosity that you built up by looking at the stars and how that transformed into like looking inside the body, inside the cells. Like that's mind boggling. If I could words it into something like this it would be very romantic “from stars to cells”. Something crazy like that but it is and in the end it is one of those things that this is a sort of thing that motivates people to wake up in the morning versus “Oh, I just have to go do this repetitive thing.” There is this notion sometimes of fulfilling this intellectual thing that you have to find out and discover and kind of check.
David: If I could make one point, that is I would say to you and I and to everybody listening are kind of challenge and that is as scientists and engineers I think we have a lot of excitement about trying to solve problems, about tying to investigate things, about trying to create solutions. I'd say the challenge is to look at what the purpose of the solution is, what the end product is and see whether or not just the solution you're creating kind of solves that problem, but whether you think it adds total value and whether you're being challenged or whether you're learning from where the industry is going. Because I think both sides of that in both science and engineering are very important.
Carlos: Do you have any resources or any books that you would recommend?
David: Unfortunately, I work in such a manufacturing and engineering focused area that most of the textbooks I would discuss on process efficiency, on thinking, even about laboratory automation are a little bit close minded. I would say I would recommend wholeheartedly three academic groups. One which is The Society of Laboratory Automation and Screening (SLAS), the other is a group called IVHM which is Integrated Vehicle Health Management, which to bring in something from that field is how you monitor jet engine health on the aircraft. I'm sorry, I should leave it there at two. But to your point into your question, if you are interested in astrophysics and you almost like it's only backs the beginning, there is a book called Black Holes and Time Warps written by a physicist who did all of the background work for the film Interstellar. I got his name Kip Thorne.
Carlos: Alright, that my friend. That is an excellent resource, thank you so much. I haven't read that book by the way. Ok, this is the party trick question. Give me a nutshell about how gravity works within a black hole. I need to understand this because, what the hell, which way is down in a black hole?
David: The fundamental problem with that is that however we describe the universe of what we can see around us, gravity in of itself breaks all of those rules as soon as you get anywhere near the center of it. So describing what happens there and I will actually give you. I think Kip Thorne's foreword does a fairly good job of describing sorts of on behaviors that happen around black holes. Generally nothing special, it's just that pull of the universe gets too great for things just to exist as complex entity and because of the power of gravity because the strength of it everything gets broken down it just, simply it's base energy. So the center of a black hole is kind of at the same time nowhere end it just contains everything.
Carlos: So the question is, does time happen within a black hole? I am telling you, these things like drive me insane up a wall. Again, there is no commercial benefit or in benefit for me to know or even me interested about these things. But these are the things that my wife, she listens to me, either listening to YouTube videos telling about these things or reading this things and then I read it to her. And this is like 2:00 in the morning as I usually do. And she is like, “This guy is crazy.” Like she must think I'm out of my mind like thinking of this down way. Like thus the direction of down have a weight. I mean, these are just crazy thoughts that astrophysics puts in your brain or like the one we just had, does time happen? Does time pass? Does the notion of time break within a black hole? Right, because there is so much gravity that is time I think. So anyways, I just want to end it with that because I don't speak to many astrophysicists that have any much interest in this field so I'm sure my questions about astrophysics are probably didn't bad questions but I'd love to hear some of what you have to say, so thank you so much.
David: I would give you one parting thought there and that is if you're interested in all of this stuff I would look up something called the Kardashev scale and it's a way of describing civilizations and about where they power themselves from. Base level of civilization is typically gained by burning things. It's the easiest form of chemical energy. You then move on to on the scale of atomic energy, Kardashev scale one civilization. It's what we consider other kind of fusion and fission. But the higher levels actually start discussing how you extract energy and power out of the universe and it's a fascinating way of framing where humanity has got to, where we can continue to get to and what the universe around us looks like. And it's part of the excitement about biology and pushing that boundary forward that is in wanting to go and explore that. And the only way we can do it is by making ourselves better for us.
Carlos: Man, thank you so much. Let me ask one last thing to that. It would take thousands of years to get to the closest star. Biologically we are incapable of reaching that star so unless we fix ourselves to somehow we wouldn't be able to even get there as a race.
David: Yes, I am hoping that we can extend the life such that some of the shortcuts we know exist will start getting into play but certainly that is as a base level of biological kind of exploration. That is the next challenge we need to overcome.
Carlos: So David, as a parting question, how can people get in touch if they have any questions, they are interested in the work that you're doing at Synthego? And I'd like to get an idea of if you guys are hiring and if you are what are some of the traits that you are looking for and again how can they apply or get in touch if they have any questions?
David: I'm generally going to forward you to the Synthego website and you can find me on links. I think you are putting my contact details on there. The second point though with all of the different disciplines and all of the different engineering disciplines we just have been describing we are hiring across all of them. We are in need of mechanical engineers, control engineers, software engineers, and even talking about informatics again versus data analytics versus instrument control. All of that is on the website. It's moving rapidly because we are a fairly small company so please please go and have a look at it.
Carlos: My friend, thank you so much. Once again you've been wonderful and I always get great pleasure to chat with people that are 100x smarter than me and you'd certainly are so thank you for taking the time, for making the time and energy and thoughtfulness that you've put into this session, so thank you so much.
David: My pleasure.