Cheap genomes are coming, but which model will pharma adopt to use them?
By Keith Johnson, Edward Oakeley and Frank Staedtler
September 28, 2010 | The imminent, eagerly anticipated arrival of the $1,000 genome has caught the attention of sections of the media and the scientific community. But what will be its impact on health care and will it be embraced by the pharmaceutical industry as the key piece of technology required to deliver personalized medicine?
Undoubtedly the answer to the first part of the question is that it will be game changing. But the second part will require significant downstream understanding of human biology, disease processes, and the way in which these interact with drugs and biotherapeutics before it can be achieved. There is no doubt that using whole human genome resequencing we will uncover many causative rare mutations in targets for important human diseases. Knowing about these mutations and how they interact with our lifestyle choices will have a huge impact on disease prevention, progression, and prevalence.
Eventually, as these “risk of disease causing” variants are understood, it will be common practice for an individual’s genome sequence to be generated and available to their health care providers. In the interim, next-generation sequencing (NGS) could replace single nucleotide polymorphism (SNP)-based approaches currently used during clinical trials to search for associations with efficacy and safety end-points. It is even possible that an incentive for people to enroll in a clinical trial could be the generation and return of that person’s genome sequence—if the inevitable legal issues could be addressed. This would not apply to all trials, but would apply in development programs where population stratification, based on genotype, is essential to the successful registration and approval of that molecule.
NGS technologies and their applications are already impacting and eventually will transform the process of drug discovery and development. However, the real impact of NGS will initially come from our ability to rapidly sequence many other genomes of relevance to human disease. These are the bacteria and viruses that are still major causes of morbidity and mortality globally and which rapidly mutate their genomes to generate resistance to treatments. Experiments to identify resistance-causing mutations that used to take months and required complex bacterial culture techniques can now be accomplished in a few weeks thanks to our ability to deeply resequence bacterial genomes. This approach enables us to find de novo mutations that cluster in genes in the same targets or pathways and identify the mechanistic basis of resistance. These findings will lead to a far greater understanding of the development of pathogen resistance and will usher in multiple new drug discovery programs. Likewise, as we monitor response to anti-viral therapies, we will be able to use NGS approaches to monitor and eventually predict and positively impact the emergence of drug resistant organisms.
NGS will also be used in the quality control of drug manufacturing processes that utilize biological processes such as vaccine production. The ability to look with unparalled sensitivity at mRNA expression (soon at single-molecule detection levels) will increase our understanding of the impact of non-synonymous mutations on the regulation of gene expression. The level of understanding of the genome and its regulation will be hugely advanced by the ability to capture all of the DNA methylation changes, the regulatory impacts of histone marks on gene expression. The field of epigenetics will be transformed.
All of these scientific advances will lead into better-targeted therapies, which coupled with the ability to predict efficacious and adverse responses to different mechanisms, will finally end the era of “one size fits all” medicine. There will be a shift from clinical trials determining the population mean size of drug effects to our goal of “determining the right dose of the correct mechanism of action at the right time for the individual” that will lead to the ultimate goal of targeted, preventative and predictive medicine.
One key challenge that we all face is the sheer scale of the data generated in NGS experiments and the pace at which we can generate it, which will continue to outpace Moore’s Law. Will outsourcing to genome analysis factories such as BGI in Hong Kong (see p. 44) provide the answer as a model for the pharma industry? That is possible for really large scale approaches such as whole-genome resequencing, but in niche areas pharma will continue to maintain these capabilities in house.
The future models that pharma adopts to address this game changing technology will vary according to need and culture within the individual companies. There is little doubt that the scale of investments needed and the rapid rate of advances in the technologies will continue to favor a strongly outsourced model for quite some time. By the time the $1,000 genome is delivered and the market arrives at the best solution in terms of providing high volume genome resequencing as a service, pharma will have moved onto the next technology challenges. •
Keith Johnson, Edward Oakeley and Frank Staedtler are with the Novartis Human Genetics and Genomics Group, Novartis Institutes for Biomedical Research, Cambridge, Mass. Keith can be reached at firstname.lastname@example.org.
This article also appeared in the September-October 2010 issue of Bio-IT World Magazine. Subscriptions are free for qualifying individuals. Apply today.