The future outlook of bioinformatics

By: Geoffrey Chen.

What is bioinformatics? To put it simply, it uses computer technology to store, manage, analyze, and interpret the data in the life science sector. As we know, DNA has four nucleotide bases: A, T, G and C while the human genome has approximately 3 billion base pairs. The typical data size of individual human genome can grow from gigabyte level to terabyte level. With the advancement of genomics, bioinformatics will give hope for humans to completely unlock the secret of life and generate next-generation biomedical products.

In the employment perspective, bioinformatics creates values by reducing the workloads of researchers and providing new perspectives to data mining. In the practical setting, it can be used effectively with healthcare analytics to ensure more effective treatment of patients and better patient outcomes. So much data is used in the medical industry that technological improvements in data analysis is incredibly useful. The development of bioinformatics creates new business, such as Nextbio. However, in the big picture of Research and Development, the rapid growth of bioinformatics may have killed and will kill more research jobs than it will create. Because computers eventually would take more shares of roles in the whole value added process. The upside is that it is killing boring and tedious jobs. Nevertheless, the crucial reality is that new employees must deal with hard-core puzzles and those who can keep the pace with rapidly evolving technology will be in demand.

The current bioinformatics giants mainly focus on creating direct values for the researchers by developing software with which scientists can have a seamless and convenient experience to conduct their R&D work. Ultimately, there is no denying that developing software can be a complex process. It is for these reasons that a significant amount of time must be dedicated to determining how the resulting software is sold to different users. One of the most common business models for selling software involves the use of a managed subscription. Essentially, software users set up a recurring payment in exchange for continued use of the software in question. Recurring payment business models have a wide range of advantages, but most importantly, they lead to high customer retention rates.

That being said, when selling software in the bioinformatics industry, the most important value we should look into is the ultimate customers, such as life science companies or patients. In the value chain, bioinformatics is bound to accelerate drug discovery (especially in the field of personalized medicine) since life science companies are facing the problem of lower productivity in the traditional research model. Admittedly, bioinformatics has much academic value. However, at the industry level, we can safely argue that the bioinformatics solutions should be able to reduce the time or cost in bringing new biomedical solutions to market. Without creating such value in the downstream proportional to its investment, bioinformatics may foresee its bubble collapse in the near future. According to Transparency Market Research, the global bioinformatics market, was estimated at $2.3 billion in 2012 and is forecasted to reach a market size of $9.1 billion in 2018, at a CAGR (Compound Annual Growth Rate) of 25.4% from 2012 to 2018[1]. Importantly, we should notice that the worldwide average R&D growth rate in the biotech/pharma industry is forecasted to be 1.6%[2] CAGR from 2009 to 2018. With this trend, in the year of 2020, the growth of bioinformatics will account for almost 100% the yearly increase in whole R&D expenditure. We should keep an eye on the growth rate, which is so high that the industry value chain has not been integrated well and the stakeholders have barely communicated thoroughly. If the output of R&D has not improved, we would be very likely to see the claw back of bioinformatics industry.

Another challenge is that open-source movement would affect the profitability of bioinformatics business. Some activists believe that the shared best solutions in bioinformatics would benefit the human beings by accelerating the basic scientific breakthrough. Some IT companies, including Intel, Microsoft, and Google, have moved quickly into bioinformatics field and would further split up the profit pie. Interestingly, the US government has invested hugely in the human genome projects. Would the US be willing to share the benefits to the world? Indeed, when the personalized medicine gets more popular as a result of bioinformatics, cost containment would be another issue given the US healthcare system is still under overhaul. Here, we conclude, the business risk of bioinformatics is currently underestimated. Investors may be too excited by the double-digit growth. Still, we see great opportunities as the bioinformatics technology is changing the landscape of healthcare services, and even at the philosophy level, raising new question like what is the destiny of bioinformatics to enable our race leap to the next level of prosperity. By carefully examining its unique position in the big healthcare industry ecosystem, we should develop more tactics to ensure the profitability and sustainability of bioinformatics business.





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