By Alexander Vadas, Ph.D., VP in L.E.K. Consulting's Biopharmaceuticals & Life Sciences
Personalized medicine has the potential to revolutionize patient care and transform healthcare. But because this model is still in its infancy, companies will need to plan carefully and correct course quickly to address rapid market shifts.
For the near term, companion diagnostics, in its current “one test/one drug” form, will continue to propel advances in personalized medicine by providing validated biomarkers linked to approved therapies. Additionally, more holistic decision- support tests will emerge for multiple biomarkers (e.g. cancer panels), as well as more holistic decision-support solutions developed that consider a broader range of inputs that inform patient management such as lab test and imaging data, clinical trial activity, outcomes data, electronic medical records (EMRs), and reimbursement and coverage data.
While a comprehensive decision-support solution that considers all available data to support patient management is likely decades away, leaders in personalized medicine are beginning to pursue more holistic models and lay the groundwork for future participation.
New Stakeholders Emerge in Partnership Activities
The all-encompassing scope of personalized medicine is expected to drive new levels of partnership activity across the life sciences spectrum. To better understand the role of collaboration in this area, L.E.K. Consulting assessed publicly available personalized medicine partnership activity from 2009 to 2011 for approximately 150 leading organizations operating in the U.S., including academic medical research, biopharma, healthcare IT, imaging, in vitro diagnostics (IVD), personalized healthcare companies (PHCs), laboratories, tools vendors, and payers. The goal was to look at broader decisionsupport trends and track the emergence of more holistic solutions beyond just companion diagnostic tests. Specifically, the research included analysis of SEC filings, GenomeWeb, internal data, and other resources.
Across the sample, approximately 30% of the 189 publicly announced partnerships featured elements geared toward creating more holistic decision-support models. Partnerships that were categorized as holistic decision support were focused primarily on mining large patient data sets (e.g. from payers or providers), molecular profiling (e.g. deploying nextgeneration sequencing), creating the IT infrastructure needed to enable holistic decision-support models, and integrating various data sets to create richer solutions.
To illustrate this point, examples for each of the four decision-support-focused partnership categories follow:
Notably, holistic decision-support partnerships often included stakeholders outside of biopharma and diagnostics and included organizations such as research tools companies, payers, healthcare IT providers, and PHCs (e.g. Knome, Foundation Medicine, 23andMe).
Partnerships are the Building Blocks
The findings suggest that this emerging group of personalized medicine stakeholders will be increasingly important in influencing care decisions going forward. Holistic models will be powered by increasingly larger data sets, sophisticated decision-making algorithms, and intuitive reporting mechanisms. This will likely require the participation of an increasingly broad range of stakeholders to provide the science, technologies, infrastructure, and tools necessary for deployment.
Your partnership strategy may have a significant impact on the pace of your group’s collaborative medical innovation, as well as your company’s ability to capitalize on associated growth opportunities. Prudent companies will develop strategies that produce value by developing the building blocks of personalized medicine (e.g. companion diagnostics tied to therapies), but will also consider how these blocks might integrate into a more holistic decision-support capability in the future. Companies that don’t define their role in the holistic decision-support ecosystem may find themselves at a significant disadvantage over the long term.