The Human Genome Project, completed in 2003, was hailed as a scientific milestone that would provide a foundation for a new generation of cures and diagnostics. Over a decade later, there has been robust growth in the creation of precision therapeutics, as biopharma companies seek to develop medicines that can be targeted to treat specific patient populations.
Interestingly, there has been much less focus on precision diagnostics, defined as the tools necessary to identify these populations. We founded GreyBird Ventures in 2013 and remain the only venture firm exclusively dedicated to developing these kinds of targeted medical tests.
Investing in diagnostics has never been for the faint-hearted. Yet, at GreyBird, we believe we are at the beginning of a very profitable investment wave marked by what are currently low asset values and the potential to deliver high returns. Increasingly, the practice of medicine has evolved from being primarily experienced-based to being evidence-based. The demise of the radical mastectomy, and the ability to substitute less expensive pharmaceutical interventions for invasive cardiac procedures, are two different examples of how longitudinal, population-based data has dramatically altered the standard of care.
This shift from experience-based to evidence-based medicine is enabled by precision diagnostics: ‘algorithm-based’ tests designed to identify smaller and smaller patient subgroups, using an increasingly complex set of genomic, imaging and phenotypic markers. Currently, these diagnostics are most often used in oncology, where they identify disease signatures with extremely high sensitivity and specificity. Indeed, these precise tests have enabled the development of more than 800 ‘targeted therapies’, which are now in clinical trials.
A confluence of four forces makes now the right time to invest in precision diagnostics.
In this environment, the only way to move from experience-based to evidence-driven diagnoses is via precision tests. Clinically, physicians face an impossible challenge of matching patients to the appropriate therapy. As disease subgroups become ever smaller, pharmaceutical companies are presently unable to identify patients for their trials without high-specificity diagnostic tests and diagnostic decision support IT.
The good news is the cost of analysing disease signatures, whether they are genetic, physiological, or image-based, continues to fall. Meanwhile, the uninterrupted monitoring of patients through passive sensors and mobile devices has become ever easier, generating a wealth of health data that can be mined. Simultaneously, more sophisticated machine learning technologies can be applied to analyse the complex data, to extract patterns and aid the increasingly overwhelmed practitioner.
Finally, the extremely high prices for these new targeted therapies is forcing policy changes from both governments and insurers to reduce overdiagnosis and ensure that non-responders to the therapies are quickly identified. The reality is that payers and at-risk providers around the globe don’t have the budgets to make high-priced drugs (for example, the congestive heart- failure drug Entresto or the new PCSK9 inhibitors) available to all patients. In the absence of credible data showing the clinical utility in a certain patient subgroup, these organisations are taking it upon themselves to classify which patients are the most appropriate candidates for a given medicine.
These dynamics are likely to be in greater evidence in emerging markets such as China, which is responsible for more than 40 per cent of global pharmaceutical growth in the last decade. There, adopting the former population/evidenced-based approaches would result in healthcare system bankruptcy.
Although the full impact of the four forces described above has yet to be felt, we are inevitably moving towards a world of greater therapeutic, and hence greater diagnostic precision. President Obama’s 2015 announcement of the Precision Medicine Initiative, followed by a similar announcement from the Chinese government one year later, provides further clear policy support for the underlying industrial and technical dynamics.
As all medicine begins with diagnosis, we believe that the trends in precision medicine will turn the diagnostics sector from its current moderate value/moderate growth status to one replicating the explosive growth of biotech. Such a scenario will benefit clever entrepreneurs and technically savvy investors alike.
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