How Successful are new Bioinformatics Software Companies?
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8.1 years ago

I'm interested in learning more about the success rates of bioinformatics companies. I'm very happy with my current job in a large institution and have no plans to start a company but I am curious about this phenomenon.

It seems like a lot of bioinformatics companies are getting formed these days. I have been hearing about people forming bioinformatics companies since before I even learned how to code. Additionally, I have personally known people who had either launched a company or were preparing to do so at every single institution I've worked or volunteered; in fact I've known multiple such people at every institution.

But whenever I've spoken to people about their bioinformatics companies, I've gotten very little indication of how well things were going. I can understand someone being cagey about their fledgling business but I've also seen very little to indicate business success from bioinformatics start-ups I've interacted with professionally.

One lab had me working with their sequencing data using some very nice looking web-based tools that seemed to completely eliminate the need for any coding/computer science skills. The company providing those tools also stored our sequencing data for us and provided incredible customer service by offering very thorough solutions that went well beyond issues directly related to the software. I found out later that my lab didn't pay them for data storage, access to their software OR their excellent customer service; apparently we got all of that in exchange for user feedback (which was pretty minimal as the product was pretty market-ready) and exposure (we mentioned them in at least one publication).

Come to think of it, I don't think I've ever used bioinformatics software that wasn't free-to-use unless you count the cloud storage services some of my labs have used. My current institution pays for subscriptions to a variety of analysis programs that go completely unused by me and the rest of my lab (which includes bench scientists with no computational skills). I guess someone in the institution must be using them but everything I know these programs to be capable of can be done using free software. Coupled with the often-repeated idea that open-source software is better for research because people develop more variety of modules for it - I find it hard to understand how bioinformatics software companies can be profitable unless they are either:

  • part of a larger company that can leverage the strength of their brand
  • offering software that controls/interacts with some kind of machine
  • selling their software bundled with other products (like cloud storage)
  • making their money off of grants or some other model that doesn't depend on paying customers

So my questions to the community:

  1. How do bioinformatics software start-ups expect to make money despite all the free, open-source alternatives?
  2. Can you name/describe any software companies that have done particularly well without having the advantages of either bundling their software with more indispensable products (cloud storage, benchwork tools, etc) or being part of an pre-existing well-known company?
  3. What resources can you suggest for learning more about the success rates of bioinformatics companies?
business software SAAS • 6.2k views
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I saw a question on StackOverflow not too long ago (cant find the link now) where someone asked how can they sell OR buy software, either to PhD/PostDocs or as a PhD/PostDoc, where the money is provided through grant funding.

There was no answer. Unless it was available through the in-house procurements web-page page, grant money couldn't be used for it - much like your PI cant walk into a BMW garage and buy themselves a new car.

Although i've only ever worked for startups who offered either a service/consultation or chemistry, or both - it would appear to me that Bioinformatic startups want to enter the "incredibly-complex-problem" space, where the majority of their potential customers are in the "paid-below-minimum-wage-per-hour" demographic. So yeah. I'm sure business is great.

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While not new CLCBio, Ingenuity (both now acquired by Qiagen, who must have seen some value in them), Genologics (Illumina acquired them recently) are some examples. I think you are overlooking commercial entities (e.g. Pharma, AgBiotech) who probably are the real customers in terms of revenue generation.

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Right, sure, and while B2B is probably how these companies survive and keep people on their payroll, I still doubt it's going to be all that profitable. Certainly, being acquired by another company is not a litmus test for things going great. When a software company acquires Qiagen, that would be very different. Of course, it all depends on the specifics of those deals - but even so - I think if the question is "how profitable are bioinformatics startups?" the answer really, unfortunately, is "it would be more profitable to write code that sends 140 characters between two phones".

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If being acquired is not a litmus test of success then what is? In fact that is the very definition of startup success. That's the only reason VCs invest in these.

I think we need to give credit to the acquiring company that they did their due diligence and found that the target company is profitable or will make them more competitive.

CLC Genomic Workbench is an excellent product. I think when it comes to desktop applications it is most likely the best.

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I agree CLC is good - but is it profitable? :) (it probably is, because CLC is the only paid software i see people using)

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This discussion started out about success, that is what the OP is asking about as well. Profits are unrelated to this ;-)

CLC looks like a major success. The company has been acquired and (very likely) the founders of it have been rewarded for their efforts - and most likely have achieved financial independence for the rest of their lives.

It is also possible (though very unlikely) that company was going under and being acquired saved them.

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Considering the fact that Qiagen (CLCBio/IPA), Life Tech (Vector NTI), Agilent (GeneSpring) keep these software packages around and available for a decade or more must mean that they are contributing favorably to the bottom line of the parent companies. Considering the size of possible target audience they can never hope to reach the level of success of the company to refer to [apparently that company is not doing so well either :-)].

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Heheh, yeah, it doesn't get more profitable than selling water as "elution buffer" and all the other things the reagent companies pull off, hehe - but still, maintaining a product doesn't necessarily mean it's profitable. It might not even break-even. They might keep the company running for tax reasons, to keep an ear to the ground in the field, to have some loyal in-house expertise in software development, political reasons that product cant be disbanded, HR reasons those people can't be let go... there are a ton of factors, so other than by looking at their annual reports (..zzz..) its not so easy to say.

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8.1 years ago

The issues that you describe apply equally well to any startup, not just bioinformatics oriented ones. Now take into account that over 90% of startups fail. So the simple and straightforward answer is that the vast majority of these startups will fail. Hence there is no magical secret sauce.

Your bullet points perfectly describe what one actually needs to be successful. So instead of saying "how to be successful unless this or that" it is the other way around: don't start a business unless you know how are you going to make money and if none of those bullet points apply perhaps it is best if you do not start that business.

I have actually attempted to start a bioinformatics business around consulting (and I hoped to involve Biostars members in some way), and I have learned a lot in the process. The most important lesson is that being a domain expert and understanding your field really well has nothing to do with a business success. In fact it may be counterproductive as you are prone to overthinking it and you are not like your potential customers.

Being around for sufficient time and with luck I have made connections and today my mini-consulting company is what you could say "profitable". That means I don't regret spending the effort of building it up over time. It is basically a part-time consulting service that my current job allows me to pursue. I have also learned something else, running your own company is not that great if you like and are good at the work that you currently do. When you run a company you will be doing something completely different.

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Do you find that your customers tend to be from industry? I would imagine there to be a lot more complications in terms of grant funding usage or authorship issues when dealing in academia.

Consulting or freelancing is something I've often thought about. But I just don't really see it happening anywhere.

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The tasks that I take on in a consultant capacity do not involve scientific discoveries or publications. I would strongly advise against freelancing as "scientists/bioinformatician". It is not a good long term model since no matter how skilled one is the results are only as good as the data - which can be of awful quality or the real phenomenon may turn out unexpectedly complex . This is very different from other crafts where the craftsman is able to deliver the desired product via their own skill alone.

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8.1 years ago
Carlos Borroto ★ 2.1k

I don't think there is much value in selling bioinformatics software. Mostly for the reasons you described about the advantages of the open source model. However, I do think there is value selling consulting, services or platforms leveraging such open source tools. Not every lab, institution or even small companies in need of bioinformatic expertise will afford having in-house expertise. I stopped using CLC a while back, but I remember even them were going in that direction allowing easy integration of open source tools along their proprietary ones.

I have no internal data about how profitable is SevenBridges, however they seem to be doing well and growing quite fast.

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In addition the problem is that we don't even know what the software should be able to deliver. The expectations of what a software should be doing are in constant flux.

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