Yes! If a set of other components is in place to make a complex innovation equation work…


Genomics holds great promises for drug development through the identification of new drug targets, better understanding of disease mechanism, and the elucidation of drug action (Emilien, 2000). The most likely impact in the short term is through the discipline’s ability to enhance patient screening and selection in clinical trials (Stratified Medicine); in the mid-term, its use in pharmacogenetic and companion diagnostic testing has the potential to positively impact the effectiveness of drug treatments (Personalised Medicine) (Khoury, 2007). More recently, genome sequencing has drawn attention as potentially game-changing intervention in re-designing cancer clinical trials (Ledford, 2013) (Rojahn, 2013).

This post concentrates on the role of Genomics in clinical trials as a measure of the discipline’s impact on medical innovation. I use this to make some generalizations on how a Genomics-enabled medical innovation eco-system should look like to stimulate innovation in South Africa.

Genomics & Clinical Trials

In view of the attention Genomics and other ‘disruptive’ technological developments (e.g. Big Data) draw, what does the situation in terms of their use in clinical trials actually look like? A glimpse at the database provides a few clues.

As at 21 September 2014, registered 175,013 trials (open and completed). 4090 of these, or 2.34%, were carried out in Africa:


Conducting a search for ‘Pharmacogenomics’ (PGx) and ‘Genome Sequencing’ (GS) paints the following picture: of the total number of studies, 0.2% and 0.07% included a PGx and GS component, respectively. When limiting the search to open studies (assuming that more recent open studies would have a higher likelihood of including an information-rich component), the share of trials including a PGx and GS component increased to 0.24% and 0.15%, respectively.

The reasons behind Africa’s minute share of the overall clinical trial business warrants detailed exploration and discussion, but for the purpose of this post I am merely focusing on a few big picture issues:

  1. Relationship between drug sales and number of clinical trials: a PhRMA report provides information about drug R&D expenditure and sales by PhRMA member companies in various countries across the world in 2011. Putting this into context with the number of clinical trials carried out in China, India and South Africa suggests that the latter fares comparatively favourably in comparison to China and India: The drug trials to drug sales ratio is 1.6, 1.5 and 2.2 for China, India and South Africa (data not shown).
  2. Relationship of Genomics supply and Genomics clinical trials: Arguably, through BGI, China is a world-leading provider of Genomics capacity. Yet, this doesn’t equate to a dramatically higher share of trials with a PGx or GS component. China, Europe, Tunisia (Africa) and the US own 5.6%, 25.6%, 0.8% and 52.8% of the global share, respectively. Rather, it suggests that sophisticated assays are carried out in the traditional hubs in Europe and the US.

Genomics, medical innovation, Africa

In my mind, Genomics as an isolated effort will not be able to have a dramatic impact on medical innovation on the African continent. It will depend on a range of other components of a more complex equation to fall into place. Right now, an insufficient resource base keeps the African continent from embarking on large-scale and costly R&D endeavours.

Here are components I’d consider crucial for creating a (more) viable medical innovation eco-system from a South African perspective:

  1. Industry involvement & stakeholder compacts: I think there is no point in agonising over the lack of Africa-specific medical innovation, in view of the high burden of disease on local populations and economies, if an effective dialogue between industry and local stakeholders doesn’t occur. A compact is needed that appreciates respective needs and wants, to focus efforts on R&D ‘sweet spots’.
  2. Effective Genomics infrastructure: This doesn’t necessarily require capacity at the scale of the BGI. A properly run facility that can expand its resources and capabilities in response to demand and in line with technological development would suffice to support a variety of projects run on the African continent. Such a facility can serve as an interface between academia and industry and can therefore also function as a stakeholder engagement platform.
  3. Human tissue banking & effective mgmt.: Samples should be collected and stored systematically in a purpose-built facility. This should be centrally managed to create economies of scale and keep the running costs down. The facility should aim at collecting and storing any type of sample, whether it’s been utilised for basic research, a clinical trial or diagnostic testing. Commercial players could be encouraged to participate through adequately designed incentives, such as tax credits for research. The storage costs would have to be borne by the government but a share of these could be recovered through commercial tissue banking activities.
  4. Data sharing & management: Medical data should be stored systematically and made available for life science/medical R&D and innovation efforts. Data can be derived from publically funded research projects; genetic testing in clinical trials; or, diagnostic testing in pathology laboratories. By way of employing data that are generated in routine activities, such as diagnostic testing, the repository could be built faster than what may be feasible through locally funded research. In addition, (South) Africa should perhaps consider a compulsory genomic (e.g. whole exome or genome sequencing, depending on the price point) component in clinical trials conducted with African samples. This would drive genomic reference data generation and stimulate further research efforts. As an incentive, tax credits or preferential pricing for new medicines could be offered. Data could be made available in a tiered fashion (free of charge for academia, at a charge for industry). But, the benefits of making the data available to all stakeholders will speed up value extraction / creation, which in turn will benefit the local environment stronger than the fees collected.
  5. Patient education & connectivity: Patient education and connectivity will be a major component in future clinical trials and in medicine as a whole. Already now, in the developed world, organisations such as PatientsLikeMe have a huge impact on people living with dreadful diseases, with some arguing that network-based organisations could make the current clinical trial model obsolete altogether. Cell phone and, increasingly, smart phone penetration is strong in (South) Africa. Using this as an opportunity to supply and capture health-specific information will have a huge impact on how health care is going to be delivered, clinical trials are going to be run, and patient-specific information is going to be captured. Here, collaboration with mobile communication companies with expertise in creating low-cost innovative solutions (such as MPesa for cell-phone based payments) and tapping into local cell phone app entrepreneurial potential are immediate opportunities for stimulating innovation!
  6. Doctor participation & interdisciplinary decision-making: In the not so distant future, doctors will be part of a decision-making eco-system, working at the interface of rich biological and other data-sets, and dedicated domain experts. This will require a different type of empowered medical professional on the mid-to-long-term, and smart decision-support systems as soon as possible in the near future. Companies such as Foundation Medicine highlight what kind of concentrated resource pools are needed to make Genomics-powered Personalised Cancer Medicine work. Right now, most of the know-how related to Genomics or ‘big data’ is tacit. It will require significant efforts and quite some time to ‘democratise’ innovative new treatments through the creation of tangible solutions and devices that empower customers (doctors) and end-users (patients). In the meantime, this can be overcome by creating integrated centres of expertise.
  7. Funding & financing: Finally, alternative models for funding and financing to stimulate African R&D should be explored. While building a local VC industry with ability to invest into risky R&D, and creating pre-competitive consortia to stimulate development should be encouraged, perhaps even bolder action is required to pump life into medical innovation on the continent. While traditional approaches to financing new medicine development play a role, with a traditionally very strong financial sector South Africa could lead the development of an African mega-fund to fuel local innovation.
  8. Reimbursement for medicines & diagnostics: Not only has the cost it takes to develop new medicines come under increasing pressure from stakeholders who demand more efficiency and, ultimately, better returns from the process; the pricing of medicines, in particular the ones that are innovative but may eventually only benefit a subset of a population, is also being heavily scrutinised, by concerned patients as well as payors. Genomics applications can be used to optimise patient selection in clinical trials, amongst others, which will ultimately reduce R&D costs. What hampers the wide-spread adoption of new genetic tests (e.g. in breast cancer or for prenatal risk assessment) is (a) lack of relevant knowledge in the medical community about these tests (hence the need for creating inter-disciplinary resource pools for testing and interpretation, such as done by Foundation Medicine) and (b) adequate reimbursement. Regarding the latter, this is often motivated by the lack of a complete body of knowledge that demonstrates cost effectiveness of new tests. Owing to their increasing complexity (and, frequently, the difficulty to establish clear cause-effect relations), demonstrating cost-effectiveness may require large-scale and expensive studies, ultimately inflating the price point of these tests or making them economically non-viable (despite a potential benefit to patients). Here, a more flexible approach to collecting data over time (mentioned above) and buy-in from payors to experiment (i.e. fully or partially reimburse) with new diagnostic tests in absence of a complete cost-effectiveness analysis could boost diagnostic innovation in South Africa.

Works Cited

Emilien, G. e. (2000). Impact of genomics on drug discovery and clinical medicine. Qjm, 93(7), 391-423.

Khoury, M. J. (2007). The continuum of translation research in genomic medicine: how can we accelerate the appropriate integration of human genome discoveries into health care and disease prevention. Genetics in Medicine, 9 (10), 665-674.

Ledford, H. (2013). Master protocol’aims to revamp cancer trials. Nature, 498(7453), 146-147.

Rojahn, S. Y. (2013, November 12). Genomics could blow up the clinical trial . MIT Technology Review.