The Human Genome Project (HGP) heralded the development of a new branch of biological science, Genomics, and the creation of an entire industry. The project cost the US federal government $3.8 billion through to completion and generated $796 in economic returns. This is a return-on-investment for the US economy of 141 to 1. Should South Africa follow the lead and make similar investments into Genomics? If it does, will it be able to reap similar benefits? If we had a model to adequately measure what these benefits are, would it help policy makers and funders to support bold initiatives? An investigation of the socio-economic impact generated by the HGP suggests that we can model the benefits derived from investments made into Genomics. But, such a model will never replace the need for decisive leadership when working at the cutting edge of innovation in the biological and biomedical sciences…
The Human Genome Project (HGP)
Undoubtedly, the Human Genome Project (HGP) was one of the greatest scientific endeavours ever undertaken by mankind and the largest Genomics research project carried out to date. Commonly, the HGP refers to the large-scale initiative aimed at determining the complete sequence of the 3 billion base pairs of DNA contained in every cell of the human body. Here are some key facts pertaining to the HGP: the project itself was initiated in 1990; it lasted for 13 years; it was coordinated by the US Department of Energy (DoE) (1) and the National Institutes of Health (NIH) (2); and, it cost the US federal government $3.8 billion through to completion (3). In addition to the US government funded initiative, a private effort spearheaded by Craig Venter at Celera (4) was also in for the race to scientific glory and contributed to the successful completion of the project.
Much has been written about the scientific endeavour itself (for example, ‘Drawing the Map of Life: Inside the Human Genome Project’ by Victor K. McElheny, offers an interesting historical account of the HGP (5)) and the rippling effect it has had on the global fabric of science. To put a number of related trends into perspective, highlighted on the graph below is the year-on-year increase of the following PubMed (6) search items: ‘Genomics’, ‘Sequencing’, ‘Next Generation Sequencing’ and ‘Bioinformatics’. It indicates that ‘sequencing’ has been around since the early 1990s, growing steadily in relevance, if only more rapidly with the emergence of NGS technologies. The strong growth of ‘Bioinformatics’ points to the dramatically increased need for analysis and interpretation of data in the wake of an exploding number of ‘genomics’ projects.
In addition, the HGP has led to the creation of entire genomic industry. As a direct consequence of the investments made in the scientific endeavour itself a substantial economic sector has developed, benefiting the US economy in terms of business volume, jobs, and personal income supporting American families (3). To put the extent of technological innovation into perspective, I think it suffices to mention that the cost of sequencing an entire human genome has dropped by more than 4 orders of magnitude since the beginning of this century (7). As is evident from the graph below, it took 5 years for a one-order of magnitude drop in costs. From 2005 onwards, there has been a one-order of magnitude drop every 3 years. If this trend continues, we’ll hit the $1000 barrier in early 2013 (of course, by now we know that this is going to happen, thanks to the next wave of technological advancements driven by Oxford Nanopore Technologies, and others), and we can expect a drop to $10 in 2016. These gains in sequencing cost-effectiveness were made possible because of breakthrough innovations generated by companies such as 454 (now Roche Diagnostics), Illumina (still Illumina), IonTorrent (now Life Technologies), LifeTechnologies (SOLID) and (soon) Oxford Nanopore Technologies.
Socio-economic impact of the HGP
Until recently, the socio-economic impact of the HGP has not been assessed or documented in greater detail. An attempt to close this gap was undertaken by Battelle, a US-based independent research and development organization (8) in a report published in May 2011 (3).
The report tackles the impact generated by the HGP from two distinct angles. Firstly, it looks at the functional impacts generated in the wake of the HGP, such as in the form of new knowledge that leads to the better understanding of disease pathways, with consequential effect on drug development and human health; or, leads to plant and livestock improvement – either by altering input traits (such as nutrient uptake or pest resistance) or output traits (such a nutrient content, yield or flavour). These impacts also include the development of genomics tools, technologies and techniques – an area of fundamental importance to making the sequencing feasible (3). It is interesting to note that the report views economic impacts as a ‘bonus’ that has occurred in addition to the primary functional impacts. Amongst others, it makes reference to the fact that the HGP’s key goal was to create benefits for humankind by elucidating basic molecular processes governing life and via the application of knowledge gained to human health care and multiple other fields that would benefit from advancements in genomics knowledge and technology (3).
Secondly, the report considers expenditure impacts, such as in the form of follow-on federal R&D spending or spending by the genomics-enabled industry. The expenditure impacts stemming from the HGP are those impacts generated in the economy from the direct investments in the HGP, the investments in follow‐on HGP enabled research, and through the genomics‐enabled industry that has been developed and fostered through the science and technological requirements of the HGP (3). Expenditure impacts consist of three impact types:direct (the specific expenditures impact of the program and/or sector(s) in question, indirect (the impact on suppliers to the focus industry or program), and induced (the additional economic impact of the spending of these suppliers and employees in the overall economy) (3). The key metrics used in the report to measure expenditure impacts were R&D funding and investment (made by the performing sectors) and employment.
The following schematic is from the Batelle report (3) and neatly summarises the measures used to determine HGP related socio-economic impact.
Key report findings
The report goes into much detail when describing the various impact sub-categories and measures. Here, I will merely highlight its key findings:
It found that between 1988 and 2010 and vis-à-vis expenditures of $3.8 billion, the HGP generated
- an economic (output) impact of $796 billion;
- personal income exceeding $244 billion;
- 3.8 million job-years of employment. A job‐year is equivalent to one person employed full time for one year. Taking into account the time period underlying the Batelle report, an average of 172.000 jobs were created per annum between 1988 to 2010;
- A return on investment (ROI) of 141 to 1. That is, for every $1 invested, the project generated $141 in return.
These findings are remarkable, for a number of reasons. Firstly, in the past, measuring returns on investment made into scientific research have proven rather difficult. In fact, economists have been debating the difficulties accompanying the economic value assessment of research spending, some arguing that it is an impossible feat altogether (9). Secondly, even in view of other representative assessments, the reported impact made by the HGP is massive (for an impression, see the following schematic). To put the HGP impact into context, data derived from investments made in agricultural research suggested annual returns between 20 and 70% (9). A more recent study by the Welcome Trust estimated economic returns made into the biomedical research to be in the order of 7 to 9% (10).
In 2010 alone, the Batelle report found that the genomics-enabled industry generated over $3.7 billion in federal taxes and $2.3 billion in US state and local taxes, i.e. an aggregate tax income of $6 billion. This suggests, that 20 years post inception of the program and several years since the publication of the first draft of the Human Genome, the genomics industry in the US is well and alive and actively contributing to the US GDP.
Key conclusions we can derive from the report
- The HGP was initiated and completed on the basis of a strong, if not exclusive, public interest and non-profit agenda. All information and knowledge generated by the project has been made available to the public.
- Yet, it can be argued that the HGP generated a significant economic return for the US, in the form of new knowledge, follow-on investment, employment, innovation spearheaded by genomics-enabled companies, and tax revenues made from these companies. One explanation for the comparatively large economic impact made by the HGP may rest in the fact that the (sequencing) technologies developed to read DNA are scalable in nature and less risky than the biological questions that emerge from generating terabytes of genetic code. Therefore, they lend themselves more easily to the creation of economic returns. It will take much longer for us to see returns made by the introduction of genomics-enabled drugs and diagnostic tests;
- Scientific and technological gains seem to emerge in a symbiotic, inter-dependent fashion, where components in a system are stimulating each other in a reflexive manner.
- Developments are made by individuals residing in enabling institutions that know how to engage with each other. In the absence of such viable interactions, collaboration, cross-pollination and innovation (at the interface of these institutions) is difficult to occur.
- Projects and investments of this scale and nature require unity and significant will-power amongst all the key role players and stakeholders, in addition to a strong, coherent long-term vision. Without this, there is a considerable risk that the funder (the US government in this particular case) may drop the ball in face of problems (which are inevitable in a project of this size) and stakeholders may lose interest or drift into disharmony.
- For a project like the HGP to generate returns it must be imbedded in amature and healthy environment of public, private and voluntary institutions. At the time of inception of the project, the US was certainly a nation with strong institutions established in all of the three spheres. For example, capitalising on the massive amounts of knowledge generated by the HGP required a healthy investment sector, ready to support entrepreneurial ventures that sprung from the project. Equally important, there had to be sound non-profit organisations who’d tackle ethical concerns or would cater for the needs of patient groups. Of course, there had to be government departments and funding agencies with a track record and vision to support a project of this size and nature.
A crude Genomics research economic impact model for South Africa
In order to understand what relevance the HGP, and the lessons we can learn from it, may have for South Africa, it’s useful to review some of the publically available data about R&D spending in this country.
In the 2007/2008 fiscal year, combined research spending for the biological sciences and medical & health sciences was about R 1 billion (government and business expenditures), equalling just about 6.6% of total R&D spending (11). Spending on these categories is probably the best proxy we have for ‘Genomics research’. Between 2000 and 2009, GERD (Gross Expenditures for R&D) grew at an average annual rate of 10% (data not shown; value derived from data provided in ref. 11).
Taking this into account, the following is a very simple ‘back-of-the-envelope’ calculation of what economic impacts could be generated by investments into genomic research in South Africa:
- I assumed that R&D spending will continue to grow at the rate (10%) seen in previous years. Therefore, in the 10-year period between 2009 and 2018, at a constant 6.6% of the total, the SA government would have made an accumulated investment into the biological and biomedical sciences in the order of R 19 billion. (I am using 2008/2009 data simply because these are the ones I have had available. Also, I assume that in 2018, the majority of the investment made into these research areas will still be coming from government and other non-private sources, and not from the private sector.).
- I also assumed that investments made into Genomics will be a constant 5% of the total spending on biological and biomedical sciences. Consequently, the accumulated investment in this area made by that time would be roughly R 950 million.
- Very crudely, I have assumed that South Africa does have 50% of the institutional capacity of the US with respect to supporting genomics-enabled innovation. Therefore, a multiplier of 70.5 applies. Considering this, the economic return generated by the investment into Genomics would be R 67 billion over a 10 year period.
- Using the R 3000 billion GDP of 2010 as a basis (12), at an average annual GDP growth rate of 3% South Africa’s GDP in 2018 would be R 3800 billion. The accumulated impact made by R&D investment into Genomics would contribute an estimated 0.018% of total economic output to GDP in 2018.
As crude and hypothetical this calculation may seem, it provides an impression of how any impact derived from investments made into Genomics R&D (any investments made into scientific research for that matter) can be determined. In my mind, the accuracy of these figures is less relevant than considerations as tohow we could arrive at generating any meaningful returns from investments into Genomics (or any other aspect of modern biotechnology, such as stem cells, nanotechnology or biomarker diagnostics). Also, it provides an approximation of what the returns into fledgling scientific fields such as Genomics can be. Theimportant take home message is that (i) investments made into Genomics generate sizeable economic returns and (ii) a model that simulates or measures the performance of projects, programs and entire systems can be built.
One aspect that puzzles me about the HGP is that a significant portion of the knowledge generated by it is in the public domain. It appears that the stakeholders involved in the project were less concerned with protecting the potential value it was going to create than with enabling the whole of mankind. As a consequence, every nation and organisation interested in competing in Genomics has an equal opportunity for innovation, in principle.
Considering that there are some nations that have made significantly more progress in the genomics space than others (notably the US but also China), we can assume that other factors are responsible for driving sizeable outputs, outcomes and economic impacts.
Most likely, these can be found in the fabric of mature and sound systems and institutions, collectively enabling the conversion of scientific output into economic impact (e.g. by investing into genomics start-up companies developing new diagnostic tests). No investment made into Genomics, or any other science for that matter, will yield economic returns in the absence of an enabling environment. That assumes, of course, that there is an environment for making such an investment in the first place.
Possibly one of the most interesting lessons to be learned from the HGP is that the project was initiated in the absence of an adequate understanding of the economic impact it could generate. Clearly, there were measures of success (progress made towards sequencing pre-defined stretches of DNA being just one of them) but none of these were linked with hard and fast economic metrics.
In times of austerity and systemic constraints (such as in the context of an emerging economy), we are hard pressed to make the most effective use of the resources we have. Worried about wasting time and money, we may opt to do what is necessary, but possibly not what is satisfactory; yet we hope for extraordinary returns.
As a consequence, we may choose to count what we already know. However, this may put the whole effort into jeopardy. In order to gauge progress towards objectives we must find and use indicators that make sense. To use an analogy, when assessing the performance of my personal wealth creation strategy, I am not counting the number of socks in my wardrobe, just because I can. I am using indicators that give me a fair and realistic impression of what progress I am making. Every nation with an interest in becoming a serious player in modern biotechnology will have to measure what is relevant, not what is accessible.
An economic impact model can help us to guide our decision-making. However, it will always be just an approximation or a model of what is happening in reality.No model, however sophisticated it may seem, can replace the need for the formulation of ‘heroic’ goals, taking decisive action and demonstrating adaptive leadership. The actions we take and the models we build will have to be grounded in reality and evolve in response to the lessons we learn.
It appears to me that one of the biggest opportunities presented by a project of this scale and nature is the large number of mistakes one can make, each one of them possibly presenting the starting point for innovation. If we don’t invest into risky ventures, we deprive ourselves from opportunities to learn.
Perhaps, the biggest mistake of all is not to invest into genomics at all, or only in a half-baked fashion! Perhaps, the key lesson we can learn from the HGP as a role model project for making investments into Genomics is: ‘Screw it, let’s do it!’
5. ‘Drawing the Map of Life: Inside the Human Genome Project’ by Victor K. McElheny, Basic Books