How effective orchestration of resources can overcome the biomedical productivity crisis and unlock an African biotech revolution!

Productivity in biomedical R&D is a frequently discussed topic. Quality has been singled out as a major issue affecting productivity in the life and biomedical sciences alike; the issue is particularly rife in the technology-driven areas of Genomics and Proteomics.

I’d like to explore how R&D capacity can be organised differently, in a productivity enhancing manner. My ultimate goal is to make the case for an entirely different approach to managing Genomics and Proteomics infrastructure in Africa; and, to postulate that it is possible to achieve significant productivity gains on the continent, provided resources are utilised in a particular kind of manner.


Imagine the orchestra pit at the ‘Musikverein’ in central Vienna. A conductor enters the pit and approaches the podium. As she walks past semi-circularly seated musicians, a feeling of uneasiness befalls her. One or two members of the brass ensemble seem to be missing; the tuba player looks as if sick to the bone. She looks at the string instrument section. The condition of cellos and contrabasses is appalling; the varnish on the instruments is coming off, and they are scratched all over. Some of the violins appear to have missing strings, and the lead violinist seems to be looking for her bow. In the centre of the pit, the flutes and woodwinds have difficulties in tuning their instruments. Do they actually know how to handle their sensitive instruments at all? There is a piano in the back but there is no one to play it. The audience is waiting. The conductor feels their excitement as she walks towards the conductor’s stand. What will she do? How will she be able to perform?

Such is the state of Genomics and Proteomics infrastructure in Africa. We have got some capacity, but nowhere at a critical mass. Sometimes, we have got physical assets, but no one to use them effectively. When we invest into creating human resources, we may not have the means to sustain them. When they decide to leave, they migrate elsewhere, for lack of local employment opportunities; we then end up benefiting foreign economies, instead of contributing towards the enhancement of our own. Where we do have infrastructure, it is often not managed properly. Worst of all, where capacity exists, it often does so in isolation. It serves a narrow scope, instead of being utilised in a value-maximising manner for entire regions, countries, or the continent.

When it comes to infrastructure, players in Africa are ready for competition. But, they are focused on battling local peers for scarce resources, rather than joining efforts into building distinctive competencies that have impact on a global scale. All of this tends to happen in face of well-known problems regarding the supply of electricity; the cost-effective provision of reagents; the availability of human resources; and the quality of preventative maintenance of equipment. The net effect is that investments into physical and human resources don’t yield proper returns in terms of scientific publications, patents, and biomedical innovation.

Occasionally, we see indicators of scientific greatness and even pockets of bio-economic activity. But, when we do, these are often generated with substantial contributions – financially or in-kind – from overseas. As well-intended and important as they are, they are only part of the story. We need to learn our own lessons, and make our own mistakes; we need to come up with our own, contextually relevant solutions.

Network orchestration 

Network orchestration is the art of assembling an array of resources into seamless strings of value generation; it is the art of conducting resources and capabilities in unison, to deliver outstanding value to beneficiaries. It is an approach that maximises resource utilisation, and it optimises the delivery of value.

Instead of concentrating on a single resource or capability, orchestration employs an entire network of resources; it assembles individual components into customised cascades of service and product delivery. Orchestration creates and renders networks agile and resilient to external and internal turbulence; it builds critical mass and economies of scale; it delivers products and services at high quality, fast, and – most of all – cost-effectively. It facilitates a self-policing approach, owing to the redundancy that can be built into the network. Where resources are missing, or failing to deliver, they can be replaced by alternates.

The net effect is a virtually integrated web of value providers who – according to their ability to contribute – combine efforts into generating products and services better, faster, cheaper and in much greater volumes.

Features of an ‘omics’ orchestra

Genomics and Proteomics are hallmark areas in today’s life and biomedical sciences. They are characterised by the use of rapidly evolving technologies, employed in the interest of converting biological materials (e.g. blood from cancer patients) into digital data. This is done at previously unknown levels of scale and complexity; it happens in the interest of converting research outputs into meaning and – consequently – into socio-economic value.

At no other point in the history of science have the principles of quality, turnaround (time), cost and volume been more relevant than in today’s industrialised era of biomedical research. Now, more than ever, are the principles of networking, cooperation and coordination essential ingredients of successful innovation in the life sciences. Where else, if applied properly, can these principles have more positive impact than in a resource-scarce environment, such as in many of the emerging economies in Africa? Where, if not in Africa, should the principles of networking and effective resource utilisation be more relevant?

Here are some of the principles we apply at the CPGR in building a viable ‘omics’ network:

  1. The unit of competitiveness is the network, not the individual entity. We can only reach levels of global competitiveness if we move from individual competition towards competition with networks established elsewhere in the world. We compete in an orchestrated manner.
  2. The orchestra, and its members, serves the interest of a beneficiary; in fact, it assembles in response to the need of a beneficiary.
  3. Beneficiaries are customers and end-users, enjoying short-term gains in the form of high-quality data, delivered faster, better, cheaper; and long-term benefits in the form of better diagnostic tests or personalized drug treatment, channeled through the innovation chain at ever decreasing levels of R&D cost and cycle time.
  4. All members of the orchestra are skillful artisans in their respective craft. The network composes of seasoned veterans and upstart talents. In ‘omics’ parlance, it employs mature technology platforms and hot, new, latest-stage technologies. These can be assembled into dedicated value propositions, as needed.
  5. Each player has an ability to perform individually but will only be able to maximise its potential by being part of the orchestra  The network renders support, as needed, and precipitates demand, if warranted.
  6. Individual players are part of proficiency testing schemes. Proficiency testing is carried out regularly and results are used to assess performance, and to facilitate selection of members.
  7. Learning and training (practicing) are hallmark features of the orchestra. Whatever knowledge is gained in one part of the network is transferred across the entire system, to ensure viability of the whole.
  8. Each player in the orchestra has at least three substitutes. This is to ensure a high level of redundancy, to enhance flexibility, and to render the network resilient.
  9. Members of the orchestra can provide capacity or intellectual property to the network. In other words, a member can be a supplier of time (in the interest of delivering a service, or developing a product), or knowledge (e.g. by way of transferring process know-how into the network, where it will be accessible to members, and a greater number of users).
  10. The benefit to users is in the economies of scale and scope the network creates; in rendering outputs in a cost-effective fashion; in the increased flexibility, owing to the diversity of the network; and, in the enhanced resilience due to redundant capacity, significantly reducing the chance of service delivery problems.


The conductor studies the results of a survey her Directorate has carried out amongst the orchestra’s audience over the last 12 months. When finished, she starts devising a concert plan for the upcoming season. From a pool of skilled musicians, she assembles a quartet: they will play Beethoven’s string quartets on Mondays; she puts together a chamber orchestra: they will embark on playing Vivaldi, Haendel, and Bach, on Wednesdays; lastly, she assembles an entire symphonic orchestra: they will focus on playing Anton Bruckner and Gustav Mahler, performing once a month.

Orchestration assembles resources in an agile, customer-focused fashion. It has the potential to create centers of critical mass and economies of scope and scale where previously there were none! It has the ability to enhance the development of bio-economies across the African continent through better resources utilization, coordination and concentration.


Quality issues in biomedical research

I have previously dealt with the issue of quality and reproducibility (Hiller, 2012). So have others! The following list of examples is not exhaustive, it is merely meant to illustrate the known problems:

  • In 2002, a high-profile report of the use of mass spectrometry for the diagnosis of ovarian cancer turned out to be completely flawed because of poor experimental design (Petricoin, et al., 2002);
  • In 2004, a report found that ‘five of the seven largest published studies addressing cancer prognosis did not classify patients better than chance’ (Wacholder, Chanock, Garcia-Closas, & Rothman, 2004);
  • In 2011, a study showed that ‘an empirical assessment of 18 published papers of microarray studies showed that independent analysts could perfectly reproduce the results of only two of the studies, and it sometimes took over a month to reproduce a single figure’ (Ioannidis & Khoury, 2011);
  • Presently, an unspoken industry rule alleges that at least 50% of published studies from academic laboratories cannot be repeated in an industrial setting. As a case in point, Bayer halts nearly two-thirds of its target-validation projects because in-house experimental findings fail to match up with published literature claims, a first-of-a-kind analysis on data irreproducibility found (Mullard, 2011).

Network orchestration

The concept of ‘process orchestration’ was originally introduced by John Hagel and John Seely Brown in ‘The Only Sustainable Edge: Why Business Strategy Depends on Productive Friction and Dynamic Specialization’ (Hagel & Brown, 2005). Earlier, Peter Drucker used the conductor and the orchestra to describe leadership with the flattening of the organisation. Today, the concept is applied by many companies, typically within the confines of outsourcing and extended global supply chains. For example, Boeing’s 777 jet is assembled from three million parts from more than 900 suppliers in 17 countries around the world. The movement from a traditional firm toward a network orchestrator requires a shift in focus from the firm to the network, a shift in management from control to empowerment, and a shift in value creation from specialization to integration. Despite being applied by in aspects by many companies across the world, network orchestration is epitomised by Chinese supply chain giant Li & Fung. Generated in the early 1900s, the company today manages more than 8.300 suppliers, 70 sourcing offices and operates in more than 40 countries (Fung, Fung, & Wind, 2008).


Fung, V. K., Fung, W., & Wind, Y. (2008). Competing in a flat world: building enterprises for a borderless world. Wharton School Publishing.

Hagel, J., & Brown, J. S. (2005). The only sustainable edge: Why business strategy depends on productive friction and dynamic specialization. Harvard Business Press.

Hiller, R. (2012). On ‘omics’ translation and innovation. Retrieved 2013, from CPGR blog

Ioannidis, J. P., & Khoury, M. J. (2011). Improving validation practices in “omics” research. Science, 334(6060), 1230-1232.

Mullard, A. (2011). Reliability of’new drug target’claims called into question. Nature Reviews Drug Discovery, 10(9), 643-644.

Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., et al. (2002). Use of proteomic patterns in serum to identify ovarian cancer. Lancet, 359(9306), 572–577.

Wacholder, S., Chanock, S., Garcia-Closas, M., & Rothman, N. (2004). Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. Journal of the National Cancer Institute, 96(6), 434-442.