20 Jun 2014
Laying down a biomarker
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What are the challenges that researchers face in developing personalised medicine – treatment that is tailored to an individual? And what are the implications for finding the right talent to see through this major technological development?
It might come as something of a surprise to learn that no less than 60 per cent of the 5,600-plus products in the global pharmaceutical industry’s pipelines are for personalized medicines – so says research company IMS in its data compiled in 2013 for the Association of the British Pharmaceutical Industry. The industry is changing, as medicine moves away from a broad-brush approach and towards precision therapy.
The basis of personalized medicine is the biomarker. This can be a stretch of genetic code, a protein, a peptide (a chemical compound containing two or more amino acids) – in fact any measurable characteristic where the presence or absence signposts health or disease. In personalized medicine, also known as ‘precision therapy’, the biomarker is used to place patients into groups that are most likely to respond well to the treatment. For investigational drugs, this approach can speed development by making clinical trials shorter and more efficient. And for approved drugs, it can improve quality of life for patients and cut costs for payors, because outcomes are likely to be better, expensive drugs won’t be used in patients who aren’t likely to benefit, and time and resources won’t have to be used to deal with unpleasant side effects.
"Too often [biomarkers have] been an afterthought, brought in when … data in a general population is not looking as strong as anticipated from pre-clinical studies. We now need to involve biomarker experts at all stages of drug development,” says Ian Pike, COO, Proteome Sciences, a company that is involved in developing protein and peptide biomarker solutions for pharmaceutical and diagnostics applications.
Personalised medicine will be most effective in diseases with clear-cut biomarkers that make it easy to spot the patients who will benefit. However, just because a disease has a biomarker, it doesn’t necessarily mean that everything will be easy from thereon in.
In cancer, there has been a good deal of research success, based on the plethora of tissue samples and cell lines available, and this has translated into much progress.
"Twenty years ago breast cancer was thought of as one disease, with a very limited number of options available for treatment. Now we know that there are many different types and sub-types of breast cancer, and this in turn has led to a much more personalized approach to diagnosis and treatment," says Kieran Murphy, CEO, GE Healthcare Life Sciences.
Conversely, in areas such as kidney disease, there hasn’t been as much progress, as Kumar Sharma MD and founder of ClinMet (a company that provides pharmaceutical companies with clinically relevant insights and practical information about drug response and safety), explains: "We don’t have as much information available on the genetics of kidney disease, and we don’t know enough yet about the changes that take place in kidney tissues." Sharma, who is also director of the Institute of Metabolomic Medicine and the Center for Renal Translational Medicine at the University of California, San Diego, adds: "Because of this we are in the very early stages of personalized medicine in this field."
The map of the human genome, effectively our codebook, is smaller than that of some plants, such as maize. Yet it is able to manufacture, ‘code for’, the proteins that create human beings and their complex processes. A growing understanding of how this works, and how it can go wrong, is the first step towards truly personalised medicine. While the advent of the sequencing of the human genome was a very exciting scientific breakthrough, it hasn’t yet lived up to its hype where personalised medicine is concerned. So the next step involves following the science.
According to Sharma, new breakthroughs will be guided by metabolomics (the study of all the metabolic processes going on in the body), which will allow us to sneak a peek at the pathways, and see how disruptions lead to disease. This could lead to drugs to repair those pathways or replace the metabolites, as well as allowing physicians and researchers to gauge the benefit of medications, or monitor the progress of disease.
However, this requires enormous sets of personal data. Companies need to ‘think outside the box’ for new approaches to gain information. One opportunity could be crowdsourcing information, through websites such as 23andMe and PatientsLikeMe, or from the ‘quantified self’ movement.
The creation of a successful personalised medicine offering needs the right factors to coalesce at the same time. Successful personalized medicine strategies are more likely to include biologic products such as monoclonal antibodies and cell-based therapies, rather than the older ‘small molecule’ chemicals used for decades. They will have to include a companion diagnostic (also known as a theranostic) to pair the right treatment with the right patient at the right time.
"These new approaches will change the ways in which drugs are developed, manufactured and distributed,” says GE’s Murphy. "Not only will manufacturers have to make a new generation of drugs such as cell-based therapies and antibody-drug conjugates, there will be a need for much greater manufacturing flexibility and smaller batch sizes than economically achievable today."
The new paradigm will combine the skills of traditional drug development with a completely new set of abilities and experiences from across a number of different disciplines, including systems and cell biology, chemistry, big data, computational sciences, engineering and manufacturing, as well as drug and diagnostic R&D. It will be a financial challenge too, according to Proteome Science’s Ian Pike: "The economics of drug development will become increasingly marginal and the cost per patient for each new, approved treatment will continue to escalate. Drug developers, regulators and payors will each have to swallow hard."
ClinMet’s Kumar Sharma avers that: "[Personalised medicine] will require a team approach, from clinicians with understanding of translational medicine and an in-depth understanding of basic biology, through to scientists who can use technology such as mass spectrometry to measure the activity of small molecules in a quantitative manner, to biostatisticians, bioinformaticians and computer science experts."
Companies will have to market the diagnostics as well as the drugs, and as very few companies understand how to blend diagnostics and therapeutic business cultures, a successful business model will almost certainly need to include collaborations.
Discovering the route to personalised medicine will clearly require the combined talents of experts in biology, IT and big data analytics. Creating drugs and companion diagnostics that cure disease comes down to effective leadership, and an ability to deal with change.
"Organisations undergoing change management will have to bridge the gap between the skills their leaders have now and those that will be needed going forward," says Nigel Gaymond, Chair of the Personalised Healthcare Alliance, an organisation that unites life science leaders in a new ‘action tank’ to improve the environment in personalised healthcare innovation.
Getting to the next stage will involve recruiting unusually skilled leaders, as Richard J. Lipscombe, Managing Director of Proteomics International, explains: "There will be a need for people who can lead a cross-disciplinary scientific team, and who have understanding of basic biology and medicine, and the development of therapeutics and diagnostics. They need to be able to talk to people across all these areas."
Yet leaders need to be able to offer even more than this. They need to be polymaths who can pull together crossfunctional teams from across the life sciences, tech, consumer and health sectors, and who can manage teams that cross over between academia and industry, and between companies, even those that would once have been regarded as competitors.
To reach their destination, companies will need to find potential leaders with skill sets beyond the ‘usual’, and in a major step-change for the industry, they are likely to be scientists who understand leadership rather than commercially trained leaders. They will need to be people who:
- Understand patients and why they do what they do
- Understand the tensions associated with the increased use of patient and public data
- Understand how personalised medicine will create smaller and more defined markets
- Understand doctors and how they will prescribe under this new paradigm
- Understand the regulators, and work with them to develop new ways to approve and regulate drug and diagnostic combinations
- Understand the crossovers between previously unconnected industry sectors
- Understand the importance of communication, both internally and externally
They also need to be people who understand the importance of flexibility, as Nigel Gaymond explains: "In light of the convergence across multiple organisations, industries and technologies, as well as the co-operative and collaborative ethos that will be mandated as we shift into a more open innovation environment, a fair degree of fluidity will become essential to leadership teams."
This journey to a new world of dynamic personalised medicine is daunting and exhilarating in equal proportion. Ultimately, life science businesses need to find the game-changing leaders with the skills to lead unusually broad cross-functional teams. Most important of all, they need to have the skill to crystallise a vision for a wider audience, to tell the story of what lies ahead.