Skip to main content
Premium Trial:

Request an Annual Quote

Will Dracup on Office Kick-Boxing and his Eight Years of Profitability


At A Glance

Name: Will Dracup

Position: Founder and CEO, Nonlinear Dynamics.

Background: Developer, life sciences image analysis products, Joyce Loebl, 1989.

Freelance Developer, 1984-89.

BA in economics, Manchester University, 1984.


Tell me about the genesis of Nonlinear Dynamics.

We founded the company back in 1989, and basically I’d been working in [image analysis for the life sciences] area for about a year. I could see that PCs were soon going to be powerful enough to do this kind of work, whereas the company I was working for and most companies out there at the time were using big, expensive computers for it. I never managed to convince anybody about what I was saying, because I think they all thought, ‘yeah, but every time we sell one of these computers we make a huge margin, we don’t want to give that up.’ So after awhile I got frustrated and left and decided to put my money where my mouth was, and if I thought it could be done I thought I’d go off and do it.

What exactly were you working on at that time?

I had been working on a variety of tasks in the life sciences area, one of which was looking at electrophoresis gels, but [also] a very interesting project looking at people’s leg stumps, where if someone’s had an amputation, it’s very difficult to fit them with a leg, because the stump tends to be a very individual shape. So the company I was at had come up with a way of swinging a camera around the leg to get a series of images, but they couldn’t work out how to turn these series of images into a 3-D image of the leg stump. And I had lots of fun coming up with an algorithm which did just that.

So you decided to start a company — tell me about the beginnings.

At the beginning it was just myself, going off and sitting in a dark room and coming up with the first notion of a product, which was for 2D gel analysis. This has been revised as our main product line. At the time, I was looking at 2D gel and 1D gel analysis. But I actually thought that because 1D gel analysis was relatively easy, the market would be sewn up by the time I could come up with a product. So I wrote the first 2D product. Then looked out there and found that the 1D market [had] hardly changed at all, so I went out and did the 1D one as well.

We made our first sale in the summer of 1991.

So how did you get from there to where you are now?

The growth has all been organic: We haven’t made any acquisitions. We took our first employees in 1993. We took our first venture capital in 1995, but we actually have had only approximately $1 million [in venture capital] over 14 years, because we’ve very much tried to run the business as a going concern. The company broke even over lifetime in 1996, and we’ve not looked back since. [There are] 65 people [working here now].

Describe Nonlinear’s corporate culture.

We try very hard to make it a place where people like to work and [to make it] reasonably relaxed. For example I hardly ever wear shoes in the office. It’s just one of my little foibles, but it sort of lets everyone else realize that there’s no point in standing on ceremony. And a few do things like kick-boxing. So we’re one of the few companies where if you disagree with what the boss says, you get a chance to kick him in the head. But there’s a caveat to that that he’ll try to kick you back.

We’re working now towards what we call cross-team working. Whereby, rather than have management make a decision, we get a team of people from all different disciplines in the company — the developers, the sales people, the marketing people, the applications scientists — and they work together as a team to decide some of the key decisions on where a product should be going. The impetus for where the company’s going comes more from most of the people in the company rather than just being one or two calling the shots.

We’re looking to go for a pretty serious spurt of growth over the next few years, and if we keep the current structure, then that puts an incredible load on the people in top management. So we’re trying to empower people so that they can make decisions and we just say ‘yes’ to the ideas that people have, rather than have to come up with the idea and get people to buy into it and then make sure it happens. It never works out perfectly, but that’s what we’re aiming for.

Why is Nonlinear making a push toward growth and toward being more visible now?

The last couple of years have been really tough out there. We did manage to maintain profitability throughout that period and managed to grow sales, but not by as much as we would have liked. What’s really made me look toward the future is that all our competitors seemed to have had a much worse time than we’ve had. So I really have the feeling that we stand to be in a very good position as this year rolls out. And in fact, we do full competitive analysis of all the customers that we go in to see and to sell to, and the amount of competition we’re seeing out there is declining fairly drastically.

Another reason that gives me reason to be cheerful is that we’ve concentrated the last two years on 2D gel analysis, [and] a lot of the technologies we developed for that we’re now looking at applying to the other techniques that we support. That’s going to put us in a strong position, because in 1D analysis, mass spectrometry, microarrays, we don’t see that much going on.

The third area that excites me is what we refer to as cross-technique analysis — this is sort of long term, over the next five years. But where people are looking to do systems biology, at Nonlinear we haven’t got all the answers by a long way, but we think we know a pretty good start[ing] point for how we can start bringing this data together. If I’m studying proteins I might use 2D gels, I might use ICAT, I might use 1D gels — but I use different techniques than if I’m trying to study genes. So how can we bring that data together so you can get meaningful information about different techniques?

Nonlinear already has strong products in four of the key areas that extract information from [a] signal. It’s getting information from 2D gels, from 1D gels, from microarrays and from mass spectrometry. We’ve also got the informatics package at the moment that’s concentrating mainly on 2D, but fundamentally it’s been designed from scratch to cope with more than one technique. So we think we’ve got ourselves a sort of springboard for for implementing cross-technique analysis. But it’s not like we solved it and we’re going to release something next week — it’s a very very hard problem. And a lot of the areas where some cross-technique thinking is going on — for example looking at trying to bring the data that’s in SwissProt, together with the data that’s in Genbank, together with the data that’s in all the other databases — that’s actually a very small part of the problem. Because you’re usually comparing things that were generated using the same techniques and trying to answer the same sorts of questions. We’re talking about stepping up to a much bigger problem space. And we’re very much looking at a step-by-step approach, so [at] each step on the way to solving the problem, we’ll be able to release products that will make a real impact to the people working on this.

Tell me about the Institute you’re starting up.

We’ve just been given the OK from the UK government for an Institute for Bioinformatics. The idea behind this is that it’s an institute for research but [one] that has a commercial focus. So in blue-sky research you say ‘well, let’s tackle this problem, and we’ll sort of see what happens,’ and then sometimes universities will look at it and say, ‘we’ve done some pretty clever stuff there, I wonder if we can sell it to anybody.’ So turn it the other way around, and say there are companies who know about a set of problems which are really hard and therefore will be valuable if we can solve, and which big pharma and high-end researchers will be willing to pay good money for the solutions if you can solve them. That’s the premise behind what we’re trying to do with the Institute.

The idea is that we would hire a number of researchers and very much try to learn from the experiences of Nonlinear. We know how to A, do the top-flight research, but [also] B, turn that into a commercial product. So we’ll actually be nurturing that commercial culture, and instilling that way of working into people.

So will Nonlinear be in charge of the Institute?

We’re the commercial driving force, and I’m personally going to be the chairman. But we wouldn’t be the only company able to access its outputs, although we would get on the order of a year and a half early access. And I believe we can more than make the case that we’ll be the best route to market for these products.

Who will you tap to work at the Institute?

Rather than trying to recruit too many ‘star’ researchers, we’ll be looking to get a team of sort of young, hungry post-docs — people who have got the potential to do really great stuff but haven’t done it yet. Then, in the budget for the Institute there’s money for pulling in outside collaborations, using some time of the established stars to guide the guys in the right direction. The stars would get to make sure that we were really heading for the stratosphere.

What’s your timeline for starting up the Institute?

I hope to have the first board meeting this quarter.

Where do you see your company in five years?

We have a mantra we use in-house: building the best bioinformatics company in the world. In five years time, I want to be able to say we are the best bioinformatics company in the world. I very strongly believe we will.

The Scan

UCLA Team Reports Cost-Effective Liquid Biopsy Approach for Cancer Detection

The researchers report in Nature Communications that their liquid biopsy approach has high specificity in detecting all- and early-stage cancers.

Machine Learning Improves Diagnostic Accuracy of Breast Cancer MRI, Study Shows

Combining machine learning with radiologists' interpretations further increased the diagnostic accuracy of MRIs for breast cancer, a Science Translational Medicine paper finds.

Genome Damage in Neurons Triggers Alzheimer's-Linked Inflammation

Neurons harboring increased DNA double-strand breaks activate microglia to lead to neuroinflammation like that seen in Alzheimer's disease, a new Science Advances study finds.

Long COVID-19 Susceptibility Clues Contained in Blood Plasma Proteome

A longitudinal study in eBioMedicine found weeks-long blood plasma proteome shifts after SARS-CoV-2 infection, along with proteomic signatures that appeared to coincide with long Covid risk.