Have an idea to improve LinkedIn? Please submit your suggestion below.
Is bioinformatics still a viable career choice or a business model?
Bioinformatics was pretty hot in the mid- to late- '90s, when biological data management and data integration was largely a new topic for most Academic institutions, biotech companies, and Pharma. Similar to the IT and financial service industries, bioinformatics was also initially perceived as a "good business model" to serve the biotech/pharma industry by providing discovery-oriented services. However, with the open-source "free software" spirits in the field, the complex scientific marketing challenges, the long discovery process, the generally high-risk nature of biotech, the booming of bioinformatics seemed to be "short-lived" as a business practice or an independent practice in the industry, except for in the Academia (correct me if this is not the case in your company). As an educator, technologist, and an entrepreneur, I'd like to poll expert opinions on the future of this field. Is Bioinformatics still a viable career choice for many aspiring students who expect a rewarding career returns after BS/MS/PhD trainings? Would the future of bioinformatics exist only as a service to the biotech/pharma industry where continued integration of biological sciences/applications may take place, or as a brand-new industry (e.g., Bloomberg/morningstar in financial services) to be developed in the future era of "personalized medicine"?
Good Answers (7)
I think one of the reasons bioinformatics as a business model got such a bad rap in the 90s is that the hype (and hope) was centered on genome-related discoveries solving all the riddles of human diseases. Who can blame such souring of expectations when years later we are still grappling with the reality of a complex, often polygenic and multifactorial etiology of most human disorders?
That being said, many viable bioinformatics businesses abound today, though many creating niche products, for example, pathway analysis or 'omics' systems biology suites. Most of us in the bioinformatics field do not consider open source the threat it ought to sound like simply because free doesn't mean free of all costs. There is often an enormous cost to implementing and configuring open sourceware and providing continual support for its users, which works in the favor of commercial vendors. Wise buyers (ie: those who have been burnt before!), consider long and hard when making the build (or configure open source/freeware) vs. buy (commercial vendor solution) decision. I've put a "10 things to consider" on the FAQs of our website (see below) to help guide those in the decision making process for our product but equally applicable to others.
Bioinformatics as a career choice is still a good option. As many comments have already noted, there is more data out there than scientists who know how or have the time to make use of it. The genetics field in particular is a great place where enormous contributions are being made thanks to new technologies allowing genome wide association studies, for example. These types of studies require people skilled in both biology, comp sci, computational and statistical methods. Vendors of equipment and software analysis packages alike are on the constant lookout for qualified bioinformaticists who can contribute both to analysis and development of the tools for analysis by scientists. The same can be said for virtually every other HT, multiplex or -omics field, and there is plenty of opportunity in the biomedical informatics arena both in imaging technologies and tools as well as data analytics.
One highly overlooked subspecialty is in the field of data management. If you look at the groups contributing to discovery, whether in academia, government labs, private institutes or biopharma segments, you will find a hodgepodge of systems, both specialized and ad hoc, to manage research data. If I had a dime for every Excel spreadsheet (un-auditable, no access control) or ad hoc database containing data vital to a study...well, you know the rest of it. Poor data management is often a bottleneck for downstream analysis and generation of insights, when scientists are struggling with inadequate tools for data management and query. Oracle has created a viable life sciences division and near monopoly in the clinical trials data management domain with Oracle Clinical. We are doing the same with translational medicine. Perhaps more in line with biomedical informatics rather than bioinformatics, but still viable business models with much growth expected as data generation and consumption needs continue apace.
Links:
I can't speak for a business model, but I think it is a very viable career choice. I've been watching the job market for a year now, anticipating my own graduation, and I see a lot of job postings for bioinformatics. In fact, I think the need is increasing because the "omics" technologies are producing so much data, and competent computational biologists/bioinformaticists are needed to analyze it. There is also an increasing trend for companies to post jobs for B.S. level "bioinformaticists," when what they really want is a computer scientist with a certain skill set (typically including Perl). This is still a viable career choice for students, but points out the difference between the more IT-type career path and the scientific-Ph.D.-level career path in bioinformatics.
Bioinformatics is not just a viable career choice & business model, it is one of the most critical areas of all of biology today.
Genomics, proteomics, metabolomics, glycomics, -omics ad infinitum; all of these systems biology disciplines simply can not progress without better informatics. There was a honeymoon period where the VC community and Pharma were wooed by the promises of bioinformatics, and as with all complex systems, the answers weren't as readily apparent as most had hoped. Then as all markets are prone to do there was an over-reaction, and bioinformatics was looked at askance because it hadn't delivered on it's vaunted promises.
That said, it doesn't negate the underlying critical need for the types of solutions that are only available through -omics and informatics. John Stultz from Genentech gave a talk I attended at a conference two years ago and summed it up perfectly - I'll ad lib a bit because I can't remember his exact phrase but he said "Yes, validation of biomarkers costs lots of money, and yes, the technology today isn't adequate to the challenge. But it doesn't matter because the necessity for reliable early stage disease detection is so critical that the money will be spent. The next generation of medicine is impossible without -omics."
Open source projects have always been around, and always will be. They're a superb testing ground for the most viable ideas, but they lack the support infrastructure to deliver the service required by any segment except early adopters. The problems are so complex that we'll need entirely new informatics to represent the data so that we can squeeze out the information we need. So, don't think I'm naive at all about he challenges.
However, we built a strong and viable informatics company in proteomics, one of the -omics with the worst reputations currently. Our clients are academics and commercial alike.
I don't know about a bloomberg type model. In fact I think informatics will specialize instead of generalize. All that aside though I see the need for more dedicated bioinformatics professionals arising, as the pendulum swings back, not less.
Links:
Mark P also suggests these experts on this topic:
I’m not sure that the comparison of a career path verses business model for biometrics is valid. If I’m an MD and open a practice, is this a career path or a business model? I’m on the side that bioinformatics is a career path, a mash-up of Computer and Life Sciences, and the position is supported in several business models. As a career path, I believe the question becomes what is the career path interest for an individual looking at biometrics. What does the individual consider to be a career? What level of longevity in that career is acceptable? Were those "aspiring students" focused on studies from the Computer Science industry, or on studies within the Life Sciences industry? If the focus is on Life Science, then the common studies of biology, chemistry, etc. can always be put to use as new discoveries are made, and the those branches of science evolve. Scientific data from past studies are carried forward with lesser or greater importance. If the focus is on Computer Science, then the career path must be carefully evaluated and monitored for sustained value. In the realm of computer technology, in-depth knowledge and expertise in one field can made useless rather rapidly due to advancements in the field. The computer industry does not generally have an evolutionary process. Instead, the industry regenerates itself, casting off the old and plunging into the new. Here, the buckets that hold the scientific data are cast off as new and better buckets are provided. (How many biometric data conversions have been performed because of the need to change data, verses the need to change the database engine?). The focus of bioinformatics is to manage and analyze of biological data. Does the student with a biology background really want to manage data, or is it a need to manage data as they perform studies and experiments that create the data. The student with a computer science background can provide elegant methods of managing and analyzing the data, but does not generally have the insight to the science of how that data context is created. Two differing approaches to the same career path. So, yes a career in biometrics is viable, and probably will remain so, but must be approached with different evaluation criteria as a career path. For the students of the life sciences, enjoy the respite of playing with computers and controlling data, but never lose sight of scientific experimentation and the need someday to jump back into the lab. For students of the Computer Sciences, establish the elegant solutions required to manage biological data and learn well the Life Science industry, but always stay tuned to the changes in computing technologies that some day may render current expertise, valueless.
Jake,
As Lecturer bioinformatics, i can say that bioinformaticians are very needed.
In the most labs I know data is piling. There's not enough time nor knowledge to use appropiate datamining techniques to turn the data in to usable information. Alongside the biotechnology, bioinformatics will grow in the next few years to the main stream in biology! If you look in the pubmed database at bioinformatics related papers, you'll see that since 1995 the papers almost exponential increase.
As the Highthroughput techniqes in the labs increase and become more sophisticated more and more data will be produced.
More data will be piling because of the lack of bioinformaticians. We find difficulties to find students to choose the carreer path of bioinformatics. The combination of molecular biology, informatics and statistics seems to be a strange choice for young people.
We are now already seing that "personalized medicine" will be the future. Still, like the IT revolution in the last decades of the last century, bioinformatics and biotech will grow side by side and become 'the' technology of the 21 st century.
Erik Mols
ALBIN P
Consultant at Oracle- Oracle hiring Product Manager experience in Knowledge of translational medicine and I2B2 or Ca-Big
Best Answers in: Project Management (1), Enterprise Software (1)
You are right to observe that the euphoria that was there in 90s around bioinformatics died, that doesn’t mean the industry doesn’t exist. Majority of the small companies mushroomed perished or was acquired by bigger companies, for various reasons. Lack of common standards in applications and data handling which meant every one came with his own set of programs and formats that cannot be read by a third party applications. And of course all these companies were blinded by the lure of easy money, and made the same mistakes as that of the IT boom and burst era companies.
Bioinformatics started by Biologists using computers but its no longer so and that’s a big divide, and one of the reason why so many companies perished
In any other IT application you create a code and test the application and validate the results by running a simulation, running such a simulation in wet lab for a software predicted result is still expensive, and to be honest the majority of companies doesn’t do this.
People confuse open source with free software. That’s not the case. Just because its open source doesn’t mean there is no investment going into its development. That said, any PhD worth his salt will create some or the other sort of scripts or small applications in Perl, SQL, or java, or R that would run with a commercial application, simply because no commercial application can keep up the changing needs of the life science industry and the scientist. That’s why bioinformatics’ is a career with a solid future in information technology and biotechnology. You just have to choose where your strength and passion is.
Personal genomics is long way from becoming a commercially viable reality, but that’s where we are heading
At present personal genomics is more centered on genetic testing, forensic genetics, or genealogy studies, or ancestry testing etc, though they cannot be considered in its true sense as personal genomics. These new technologies are made more famous by companies such as 23andMe, Knome, DNAPrint Genomics, family tree.com, ancestry.com, DNA Direct , Navigenics, deCodeMe, DNA Direct etc by providing services that can be broadly classified as consumer genetics or .
But personal genomics will make its mark very soon in therapeutics and clinical decision making; for Cancer and Tumor treatment, radiation therapy, and Hormone replacement therapy etc
Bioinformatics will soon find more commercial applications with clinical and diagnostics microarrays. And reducing the dependency on the live animals for testing purpose with simulations and microarrays
The next phase of bioinformatics will see the projects in large scale epidemiology studies such as the 1000 genome project and the UK government backed genetics testing projects, Evidence based pharmacotherapy, and genomic assisted clinical decision making.
Some of the more interesting trends also include collaborative drug discovery, open access journal, and of course the new Law by Dubya about Open access journal for government funded projects
According to the American College of Medical Genetics (ACMG), in the United States, there are approximately 509 physicians with training in genetics. These 509 geneticists are not distributed evenly across the United States. Four states have no physician-geneticists at all. So with all the new technology that is poised to come into the community the reality is that we have not enough people who can use it at the last mile, where it makes difference in the community .
Take a look at the video on google video Google TechTalks February 23, 2006 Russ B. Altman Prof. Altman director of the Center for Biomedical and is director of the biomedical informatics training program. He is also the principal investigator of a project, PharmGKB
http://video.google.com/videoplay?docid=5976890974902036286
So the opportunities are certainly bright but keep in mind that it’s not easy and don’t pay too much attention to the hype.
Links:
ALBIN P also suggests these experts on this topic:
The short answer is yes, this is a viable, rewarding field.
The long answer is a bit more complicated.
Yes, the field was certainly overhyped by the media in the late '90's. Even the Rolling Stone talked about it! Then when the dotcoms crashed a lot of people tried to flee to bioinformatics as 'the next big thing'. Unfortunately, they did not realize that this was simply a lot more difficult than building a web page or two. When people like this would come to me for advice, I would talk to them about where to go for Grad school, and this surprised them as they thought that it would be easy to get a job. One said to me, 'Come on, it's not like this is rocket science!'
My reply was, 'You are correct. It is much harder than that. And, as a former aerospace engineer, I ought to know!'
The number of jobs in the field is increasing dramatically right now, as so many people are purchasing next-gen sequencers. My opinion is that once the pipelines are built, and the data flow is rather settled, that some of these people will be back out on the street again in a few years.
It should also be noted that when the hype was high, the number of Universities around the world that began to throw together Programs was astonishing. Is there enough demand to justify the number of PhDs that are in these programs? Time will tell.
One of the difficulties is getting CS people interested in this area. There are perhaps 100 times more jobs for database programmers than for Bioinformatics programmers. The training and work is less rigorous for the database guys, and the pay is frequently better. This is because bio people make less than CS people.
I support the notion that Biology and Biochemistry students should have more Bioinformatics training, rather than have the Universities churn out a lot of PhDs in the field. Some will always be necessary, but I don't think that anyone knows what the optimal number will be.