The Bioinformatics CRO Podcast

Episode 45 with Jill Reckless & Jon Heal

Jill Reckless, CEO and co-founder of RxCelerate, and Jon Heal, Head of In Silico Designs at RxCelerate, discuss the virtual biotech industry, outsourcing drug development, and using bioinformatics for target optimization.

On The Bioinformatics CRO Podcast, we sit down with scientists to discuss interesting topics across biomedical research and to explore what made them who they are today.

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Jill is co-founder and CEO of RxCelerate, an outsourced drug development platform. Having completed her PhD at the National Heart and Lung Institute in London, Jill was an academic at the University of Cambridge until December 2011 before founding RxCelerate.

Jon is Head of In Silico design at RxCelerate. After completing a PhD at Imperial College London, he founded a computational biology-based drug development company Prosarix, which was acquired by RxCelerate in 2019. 

Transcript of Episode 45: Jill Reckless & Jon Heal

Disclaimer: Transcripts may contain errors.

Grant Belgard: [00:00:00] Welcome to The Bioinformatics CRO Podcast. I’m Grant Belgard and joining me today is a pair. We have Jill Reckless, CEO of RxCelerate and John Hill, the head of in silico design at RxCelerate. Welcome to you both.

Jill Reckless: [00:00:13] Hello.

Jon Heal: [00:00:13] Hi.

Grant Belgard: [00:00:14] So can you tell us about RxCelerate? What do you do?

Jill Reckless: [00:00:17] So RxCelerate is an outsourced drug development platform. We’re a service provider that can take something conceptually from an idea and all the way to proof of concept phase two clinical studies. And essentially we can provide the services that cover that pathway and that covers biology, chemistry, in-silico design, bioinformatics and so forth.

Grant Belgard: [00:00:40] Is there anything along that pathway you don’t offer?

Jill Reckless: [00:00:43] We don’t do preclinical toxicology at the moment and actually manufacturing, but pretty much we’re covered. The rest of the elements, we have GxP accreditation. We’re able to facilitate in vitro, in vivo preclinical models and program management systems, biology. We have a phage display platform that we can tap in for antibody discovery. So we’ve got a lot of the elements as well as clinical that we’re exploring further.

Grant Belgard: [00:01:12] Where do your clients tend to be based?

Jill Reckless: [00:01:15] They’re global, US and Europe predominantly, and from small biotech, which could be virtual with 1 or 2 people to Nasdaq companies and large pharma.

Grant Belgard: [00:01:28] Speaking of the virtual biotechs, have you seen repeat business from serial entrepreneurs where they’ll bring you one company, they’ll exit, they’ll start a new one, come back to you?

Jill Reckless: [00:01:41] Absolutely. That model is what has helped the organic growth of RxCelerate. That repeat business where you’ve got those serial entrepreneurs, where you’ve worked very closely scientifically to help deliver and drive their drug development program. They have an acquisition and so forth, and then they’re on to the next one. And similarly, John as part of that in silico, build that communication and working with somebody and those relationships to be able to help advise and de-risk and due diligence as well as along the drug development pathway with in silico design.

Jon Heal: [00:02:15] I think that’s one of the key things that we would say about CRO is that some people think CROs are paid service providers that work independently and simply function to provide services for things that people ask for. But actually we don’t see things like that way. We see things that CRO really is problem solvers and that if you work very closely with somebody to solve problems together. In fact, that’s the way in which you can do drug discovery to get the benefits from that type of relationship. So that’s very much the way we see things. And once you start solving problems with a certain customer and you’re successful, then they’ll come back and you can solve more problems with them. But it’s having that mindset that you’re a team, not this arm’s length service provider that provides that.

Jill Reckless: [00:03:03] I often say to clients, particularly new clients, that we’re working together as part of the same team and we’re better than the sum of the two individual parts because we are asking questions and scratching at the surface of something that they may have worked on for 10, 15 years. But from a drug development perspective, we’re able to ask different questions and collectively we can enhance where we’re going and making sure that we’re considering all those elements. And that’s really important when you’re trying to do something that’s novel and cutting edge and innovative.

Grant Belgard: [00:03:37] Do you have any relationships with investors?

Jill Reckless: [00:03:40] Simple answer is yes, because as we’ve just alluded to, you do have that repeat business. And with investors, they will come back knowing the service and things like that. So when they’re looking at other new companies and so forth, they will come to you or encourage those founders to come to you and talk to you. And similarly, investors work together so you get other investors and so forth. So yes, you do build relationships with that of which we’ve got a number.

Grant Belgard: [00:04:08] What are the most common mistakes that you see biotech entrepreneurs make?

Jon Heal: [00:04:13] I mean, obviously it depends on who that entrepreneur is. One thing we do find quite commonly is that if it’s an academic founder and particularly wedded to one area of biology, that typically they will want to see that area of biology through to the bitter end, primarily because they’ve worked on it for such a long period of time. So when you have academic founders, one of the pitfalls there can be knowing when to stop a project, to realize that it’s more complicated than you thought. So that can be one of the problems. So if a biotech is based around an academic group and that’s their ethos, then that can be a problem.

Jill Reckless: [00:04:48] And the other thing is making sure in those early stages that you’re de-risking that pathway. I mean, academic founders, as you probably can think that they really want and believe in it, that it’s going to make it a success. And there’s lots of parameters around that that you might need to de-risk. And as John has said, it’s important that you get to those points. And if they’re not able to be de-risked, then that could be the end of the program as opposed to making sure that it’s taking those right decisions in terms of investment and the scientific output.

Grant Belgard: [00:05:22] So I would imagine sometimes for scientific founders coming out of academia who may have never done this before, they may have not a good idea of timelines and levels of investment involved and so on. Do you ever have people engage with you very early before they’ve raised any substantial amounts of funding to put their plan together?

Jill Reckless: [00:05:45] Yes. So we have and do help with those plans to be able to get investment on those things. When they’ve got an idea to help, make sure that we are de-risking and covering all those bits, particularly if it’s for example a platform company where they might have multiple targets. They can’t take every target invariably all the way as a proof of concept. It’s selecting out which target would you take in one of six. And we can help by de-risking and trying to select out priority orders and those kind of things which they may not have. I mean, they’ve got the academic excellence, but there’s also that drug development piece and particularly with John and his in silico team, it’s about de-risking the approach and actually doing that due diligence so that you’ve got all that information before you start.

Grant Belgard: [00:06:36] So what does your in silico team do?

Jon Heal: [00:06:38] Yeah. So we cover a whole range of activities. I mean, primarily it’s computational chemistry. The most common thing that we get asked to do is to identify new hits against a target using algorithms, usually against a protein structure. But also there’s a lot of bioinformatics involved, whether it’s EWAS or GWAS approaches or sequence finding or protein engineering in fact. So we cover a whole range of different sort of problem solving techniques all the way from sequence up to structure and everything in between. And then once we found hits for clients, we then develop them into drugs. So we’re using computers pretty much the whole process from beginning to end to candidate stage.

Grant Belgard: [00:07:23] What’s the history of the in silico capabilities at RxCelerate? Did you come in as part of an acquisition?

Jon Heal: [00:07:29] Yeah. So just to give you a feel for a bit of my journey, so I did a degree in PhD in Chemistry at Imperial College London in the 90s, and then I was working as a software engineer and financial trading systems for a while whilst I was getting a business plan together to set up a new bioinformatics company in the early 2000. I got that funded with Angel funding and then once we grew to nine people, we got VC funding and that primarily was to build a CRO outfit that would have bespoke software capabilities to help with mostly peptide and protein design. And we then built out more small molecule design capability on top of that, which basically led to many collaborations with pharma companies and small biotech companies. And then we took an interesting turn in 2014 when our CRO company that was called Prosarix at the time got acquired by Swiss Biotech Company and they were interested in developing our methodologies for synthetic biology. So we were working with them for about five years, mostly developing novel protein engineering approaches with bioinformatics and structural biology. And then ultimately we then did a spin out from that company to reform another company also called Prosarix , which was then acquired by RxCelerate in 2019.

[00:08:51] So one of the things that you find with a lot of people in working in our industry, particularly in informatics, is that you have a vision and a design approach of what you want to do. And often in pharma the scenery can change quite considerably around you in a two decades of activities. But actually everything we’ve tried to do, myself and the team of people that I’ve worked with over those 20 years, it’s been pretty much the same just in different settings. But now obviously in RxCelerate, the interesting thing is that because we’ve got a long history of doing in silico design in all sorts of different settings. We can now bring that to bear for customers that come in and want to work with RxCelerate.

Grant Belgard: [00:09:32] How important is client education when it comes to informatics services? Do you have clients come to you? They know exactly what they want routinely. They’re aware of the caveats and things, or is that a bit of a longer process?

Jon Heal: [00:09:47] So it’s a whole spectrum typically. Some people have a very clear idea of what the biology is, what they’re after and why they want to develop a drug but don’t have much exposure historically to in silico approaches. In that case, you have to educate from the ground up. And sometimes people, they expect that computational approaches can always solve the problem. And in fact, sometimes they can’t. There is sometimes difficult problems that sometimes the computer isn’t the best thing to solve the problem. So we’re very upfront about those situations in terms of the education. Sometimes you will have customers that know extremely well what computational capabilities can do and they know exactly what they want from us. So those cases are easier and there’s everywhere in between. So but I think one of the key things we’re finding right now is that because there’s an emergence of AI technology in our field, that there’s a lot of misunderstanding around what that means for drug discovery for projects. It’s something that’s been talked about an awful lot in the media and it’s something everybody’s hearing about the fact that AI is something that’s beneficial for drug discovery. So customers want to know about that and wants to know if it’s true or not. And if it is true, how can they use it. So we’re we’re developing AI approaches now for chemistry in particular molecular design. But there’s not one single magic bullet here yet in order to design compounds. It’s a very complicated field with lots of pitfalls and potential benefits, but also the potential for people to get slightly misled around how good these approaches can be as well. So we’re very careful to interact with clients and put them in the picture as to how we see things as well.

Grant Belgard: [00:11:26] And how do you think about what area you expand into next? So it sounds like you started around computational chemistry, which obviously is a very, very different field from statistical genetics, where you also currently operate. Are you working to build out just an end to end portfolio, everything that’s useful for drug discovery that’s in silico and opportunistically building that out? Or how do you think about that?

Jon Heal: [00:11:53] Our approach has been very pragmatic. What really works, what techniques actually work and can deliver compounds for people. There’s often the nature of media now is that it’s very easy to give a very simple message about the fact that if you use this computer program, it will give you these results. And obviously the fact that papers only give you positive data, they only give you the success cases. And as we know in drug discovery, it’s kind of littered with examples of failures as well. And I think not everything works. So what you have to do is to understand what makes things successful versus the things that aren’t successful. Our job really is to try and find those approaches that work the best and will work for people and to pursue that. And really, there’s no single technology where that’s true, for that always works and one that always doesn’t work. It’s a learning exercise as to the right approach to apply at the right time. And it’s only by working through many projects that you end up learning about that. So we’re quite interested in a lot of new approaches and what benefits they can bring to projects.

Grant Belgard: [00:12:58] And when you look across the industry, what in silico technique or family of techniques do you think is most underused currently relative to what it can bring?

Jon Heal: [00:13:09] Yeah. So there’s a lot of new opportunities potentially with things like AlphaFold from DeepMind. Here’s a classic example where there is a sudden improvement in structure prediction capability, but yet people will find it difficult to understand exactly what the benefit of that is on drug discovery. So we can see that there are potential benefits to structure prediction from this, but actually then reducing those benefits to practice and demonstrating that that translates through to the better ability to design molecules will take some time. If people thought that structure based prediction had potential difficulties in certain places, that they should revisit that thinking because of these new technologies. But equally, it’s not the case that it will work in every case, and the benefit is not going to be on every target. But there will be pockets of targets now that are suddenly the structures of those have improved dramatically on where we were previously.

Grant Belgard: [00:14:04] And what approach do you think is most oversold?

Jon Heal: [00:14:07] This is tricky. One of the areas that I think that there’s a lot of papers and a lot of talk, especially at conferences around the benefits of approaches within lead optimization. And obviously Lead Optimizer is extremely poor because you go from the time when a compound is a hit, which has had marginal value to something where it’s a lead, as you know, very high value. So the value increase between is significant and a lot of computational approaches are trying to gear towards trying to optimize leads from hits. But this is actually a very challenging thing to do. And it’s not least challenging because it requires the integration of many disciplines together. So there are many things to consider in driving that forward. And I think that sometimes the role of the computer in that process can be, people think it is the Holy Grail to do this, this whole process in the computer. But it will only work if you’ve got all those other teams on board and that you’ve got this kind of holistic vision about how all those people can integrate together and drive it forward. But a lot of the newer techniques for lead optimization, especially in areas to free energy production, there’s been some big strides forward in those areas. But because of the difficulty of integrating some of these predictions into a team and the complication of running some of these algorithms that it’s not really delivering yet.

Grant Belgard: [00:15:29] And a question to Jill, what was your thinking in bringing in what now is your in-silico design division.

Jill Reckless: [00:15:38] In terms of that overall vision of RxCelerate, it’s that end to end high value bespoke adding value in that service and clearly understanding with the in silico. It’s right at the beginning of a process in drug development, but it also can be added in subsequently along that pathway and it’s a key part that you’re always wanting to understand that scientific value and readdress those things in each program that we are involved in is bespoke. So you need to have in house that integration of biology and chemistry in silico design. For example, if you’re looking at a lead optimization for a small molecule to be able to exquisitely, constantly be looking backwards and forwards between data and that in silico design and of course, if you haven’t got those capabilities in house, you haven’t got that control and being able to have those internal discussions. And as John has alluded to, being able to discuss all those elements together adds value not only to the client, but also within the teams of what we’re trying to do. And we’re always looking at the runway for beyond. And again, you’re wanting to be able to look at those things along that pathway as you get new and interesting results. So it was an important part of the journey, although we started with biology and the core biology, it was always going to be that we’d want to add in that key service. And of course it was one that we acquired quite early on in our journey.

Grant Belgard: [00:17:10] Can you tell us about the history of RxCelerate and its founding?

Jill Reckless: [00:17:13] Yes. So I’m the co founder along with David Granger. David Granger and I worked at the University of Cambridge in the Department of Medicine there doing academic work and translational work in cardiovascular and inflammation. We did get inward investment and set up companies of which they were that translational piece where we did get venture capital and we’re able to translate some of our ideas and in particular David’s ideas for development of new drugs. And as part of that, as I was helping him with along that pathway and supporting the delivery of those plans, we had to outsource. And it was clear early on in 2006, sort of area that there were service providers that were able to do what I would call a lot of process work, but not a lot of bespoke work. And it was clear when you’ve got those virtual or semi virtual companies that you really need to get the nitty gritty because you’ve not got your own labs. And hence when there was a particular acquisition of one of the companies, it seemed like that there was a sweet spot to set up a service provider that actually would be that architect of drug discovery and help with that scientific excellence in drug discovery and development and be able to design and deliver those plans. And hence RxCelerate was founded in late 2012.

Grant Belgard: [00:18:41] Have there been other similar companies that have come up since then? Is the industry still dominated by more process focused providers?

Jill Reckless: [00:18:50] I’m not aware of a company that essentially becomes a one stop shop of drug discovery and development exactly like RxCelerate. But there are lots of service providers that are specialists, but they’re much more bespoke in certain areas. And what potentially you’re finding is that with some of those larger service providers, they are acquiring certain features along that pathway. But I haven’t found anybody as yet that is replicate of what we started and our vision of what we’re trying to achieve.

Grant Belgard: [00:19:22] And would you say this is a big growth area?

Jill Reckless: [00:19:25] It is. To service providers, it’s an emerging and an ever increasing and growing sector and the space and need for all of these different service providers from the really large ones to the really small ones and the ones in between. And it’s all about clients and biotech and academic founders finding the right services for what they need depending on where they’re going and so forth and which part they’re at.

Grant Belgard: [00:19:54] Is there a particular client profile that you think is an especially good fit for RxCelerate?

Jill Reckless: [00:19:59] The vision to start with, I always thought that it would be for those small semi-virtual companies because they haven’t got their in-house capabilities and being able to design and deliver and work as part of that team. But over the years, it’s become clear to me that our service can be for any size, including large pharma. If they’ve got an idea, why can’t they outsource that idea to us rather than bringing it in-house and trying to manage that capability. If we could get it to the clinic, they could then internalize it so we could help de-risk those kind of programs. Similarly for a medium sized company, they may want to scale up their core capabilities or they may want to have certain parts and portions of that delivery of drug development and they could outsource that. And obviously, as I’ve said, those small companies with 1 or 2 people or even, a very small team being able to work very closely with drug developers is an important part of that because they may have the scientific foundation, but drug development is that additional piece. And we like to think that we are the architects of drug discovery and development along that helping them. And that we can try and help them design and deliver their programs.

Grant Belgard: [00:21:22] When did you know you wanted to be in this industry?

Jill Reckless: [00:21:26] That’s an interesting thing. My degree and PhD was biochemistry and I wanted to do drug research. So from being a teenager, that was a key part of wanting to make a difference and help people in terms of the journey you take the opportunities and of course things have progressed quite significantly in the biotech field in the last ten years or so. And it’s that opportunity that you take and seek and it’s led along this pathway. It wasn’t one that I thought, Oh, that’s what I’m going to do. But certainly it’s one that I’ve enjoyed every minute. And it’s something that is making a real impact on people’s life. John, what did you want to do?

Jon Heal: [00:22:10] I always thought there was things that’s missing. So you do some research. You’re doing a PhD and so forth, and you see gaps all the time in areas of research in informatics. And then you wonder whether some of those gaps are worthwhile and whether some of them will be useful. So this is the whole thing about which of those areas of research that have not been done will actually be useful in the commercial entity and try and go after that. And that struck me as that there were some things to try in the early 2000 and that’s obviously a long time ago now in terms of computational method development, and there’s been some incredible changes since then. Notably the advent of high performance computing, where two decades ago I wouldn’t have almost believed what level of high performance computing you’d get your hands on in order to solve some of these problems. But I think I was always very excited by the idea of trying to come up with something new and test it out. And the real world, as I say, there’s lots of papers of success stories, but I’m also interested in when things don’t work as well, because that also is the bit that doesn’t get talked about very much. But it’s extremely important in drug discovery, and it’s the place where you really learn a lot. When you have an algorithmic approach, you try something and it doesn’t necessarily always work, particularly if it’s on a really difficult problem. I think that’s where you learn an awful lot. And so I’ve always been interested in that in the failures as well as the successes and then how to try and improve things. So that’s really the thing that’s stimulated my interest is how can you make things better than they currently are. And we always know that they can get better. And the nice thing now is that we’ve got computers that can answer some of the questions much quicker than they used to be able to.

Grant Belgard: [00:23:48] I have a friend who I’m sure will listen to this podcast soon after it’s posted and is currently an academic looking at starting a virtual biotech company to prosecute a target. What would that look like ideally in your mind? Someone with no background in biotech coming into it, how would you advise they go about that?

Jon Heal: [00:24:13] Without knowing the target area and so forth, obviously it can be extremely complicated. I think the difficulty with these things is knowing what you have to work out very quickly is what proof of concept looks like. So there’s one thing about having a target and having an interest in it, but you’ve got to work out very quickly as to what that’s for and what will convince somebody else that there’s something interesting about this that’s worth investigating further. What is that experiment? And that’s one of the things that we do a lot at RxCelerate is what is the killer experiment that tells you’ve got something useful and work back from there really. And obviously, there could be a whole number of different services that are required in order to get to that point or actually it could be something very really quite simple. And it all depends on what the hypothesis is and what the person is after. So one of the things that you can do if you’re running virtually is there are CRO companies that offer assay services for you on certain targets, and there are these large companies that will just provide assays off the shelf for you run as a service and there are places that you can buy small molecules from places around the world that will sell you millions of small molecules for under £50 each. So the opportunity is there for somebody with very little income or funding to actually go off and explore a target of interest. But let’s say it comes back to that crucial experiment is how do you know when you’ve got something of interest? What often happens is that people develop an interest in a target without really thinking necessarily about what that needs to be in order to convince somebody else to put more money into it.

Jill Reckless: [00:25:49] That proof of concept is one of the key inflection points for funding, but also it’s having the design of the right pathway. Although you are wanting to get a development candidate for a specific target, it’s what that indication is. What’s it going to look like to market? There are multiple things that you may have to de-risk. For example, in that scale up and processing, although you make things that research quantities to be able to put in vitro and in vivo, how do you make kilos and how do you make GMP kilos. That in itself could be an exercise and it may be an important part in that selection of that development candidate. So it’s making sure you de-risking all of the key elements along that pathway. So you might be thinking about things that are three years ahead that you have to de-risk in those early parts. And as drug developers here at RxCelerate, we can identify those and help clients consider elements of things that they might not even be on their radar because it’s not something they need to do right now.

Grant Belgard: [00:26:52] What are the major cultural differences you see among major biotech clusters, given that you work with clients worldwide?

Jill Reckless: [00:27:02] Certainly in the US, although it’s an ever increasing thing in the UK, there are a lot more platform companies which I think they have a technology which they want to explore. They have a number of targets identified. It’s always surprising to me that in some cases they have a list of targets and they don’t necessarily go through the exercise of selecting out which target would be the one to choose first for the proof of concept, because essentially that proof of concept is the research engine for all the rest of the targets. And for them to be able to do all of those kind of targets eventually, they often will choose the target that they’ve identified the first. And it could be that target number six of ten is the target to do a proof of concept. So it’s making sure that you interrogate them and have plans and look at that wider piece, what that phase two might look like. It may be easier to do a proof of concept in idea number six than idea number one. And these are important things to consider. And certainly with platform companies, that is something that is not always evident and it’s a US thing that seems to be something that I often have come across compared to the UK, where often there’s one idea going for one indication, which is a simpler model to interrogate.

Grant Belgard: [00:28:30] Do you work much with clients in Asia?

Jill Reckless: [00:28:33] It’s an emerging area that we are working with, but to be honest we focused first and foremost in the UK and around Cambridge cluster and obviously Oxford and London and the wider UK, and then have gone into the US where we have an office in Cambridge, Mass and obviously California. So those were our main areas to start with. But as you might expect, it becomes that people reach out to you globally for us to be looking at. So it’s an area that certainly we want to expand into further.

Grant Belgard: [00:29:06] It certainly makes scheduling easier.

Jill Reckless: [00:29:09] Yeah.

Grant Belgard: [00:29:10] And how about in Continental Europe? Are there any distinctive cultural characteristics within biotech companies in contrast to the US and or the UK? Or is it all pretty scientific, homogeneous?

Jill Reckless: [00:29:22] It’s not become clear to me. I mean, you’ve got obviously with Evolver and things like that where you had a bit more exposure into Europe. Would you say that?

Jon Heal: [00:29:32] I think European scientists generally get on and work well together. I don’t think there’s a large difference in culture between different countries within Europe. There may be a slight difference between some of the funding models in different countries. For example within Europe, the kind of local changes of funding. And obviously the government grant schemes and all those things have a big impact on how companies can get funding and different routes for funding. So they change between the actual countries in Europe. And obviously the UK were not subject to the European grant system that we used to be, for example. So there are differences like that. But in terms of actually how scientists like to operate and work together generally the biotech industry is always been cosmopolitan and I think it always will be in that respect.

Grant Belgard: [00:30:21] What advice would you have for early career scientists who are taking their first steps from academia into this industry?

Jon Heal: [00:30:30] On the in silico side, one thing I would say is don’t be scared to try things that are new. Have a go. There are so many examples where people have tried to do something to change your method and make it different, and it’s worked out well. It’s always worth trying differently. And don’t be afraid just because you can’t see the software exists and therefore somebody must have tried it and it didn’t work. My experience says that’s not true. It’s just nobody’s done it yet in the general case. So always follow your nose and try things out. And also if things don’t work, don’t be scared by that. That’s actually again, that’s part of the learning process when things don’t work. Try and understand why that is and try and develop beyond that. But not everything works perfectly, but it’s not the goal of the computer program to make everything work perfectly. It’s to make it better than random. So we want to get better than just randomizing things, experiments. We want to have a positive enrichment. Don’t count the failures as failures. Count them as data points, and you’ll feel a lot better.

Jill Reckless: [00:31:35] Yeah, and certainly from RxCelerate point of view and my point of view, it follows along the same vein. It’s question things. Science is about questioning things. And going back to first principles, don’t just copy and follow everybody else. Take those opportunities and question things. That’s how innovation and those step changes. And that’s something that I encourage very much in RxCelerate is that cross-departmental discussion and brainstorming. Those are the things where you can really get different expertise to enable that scientific advancement. So I definitely think it’s important not just to think that just because it’s written, that means that it’s the gospel. You can question why or, try to think about all of those kind of things ultimately, not to be scared.

Grant Belgard: [00:32:24] Great. Do you have any final pearls of wisdom for our listeners?

Jon Heal: [00:32:29] I think the other thing is really just trying to enjoy what you do. If you want to work in this sector, if you want to work in bioinformatics or computational chemistry or systems biology, one of the allied sciences, it’s trying to enjoy it. And generally that can occur. If you’re curious as Jill was said about questioning things and being curious about things, if you take it that you’re going to be running other people’s algorithms and not questioning what you’re doing and you’re probably going to enjoy it less than if you try and really understand what these algorithms are doing and see if you can improve upon them.

Jill Reckless: [00:32:59] That’s what will make a difference. Yeah, absolutely.

Grant Belgard: [00:33:02] Well Jill and John, thank you so much for joining us.

Jill Reckless: [00:33:05] Thank you for having us.

Jon Heal: [00:33:07] It’s so nice to talk to you.