From basic research and discovery activities through clinical trial evaluations, the standard collection, processing, storage, and tracking of biospecimens is vital. Genomics, particularly in the context of companion diagnostics, is a key driver for more and better quality biospecimens.
As we learned at the Leaders in Biobanking conference, there is no lack of interest in promoting the value of the biospecimen and best practices to make samples useful. “So what?” you may ask, or even “what’s new?”.
The Blockbuster Drug Age is Over and...
That Pharma takes heat for the cost of drugs and their spending on R&D is not new. That the age of the blockbuster is over is not new. However, Pharma spends more on R&D as a percentage of income than any market sector in the world - a pretty solid rebuke to the notion that not enough is being spent by Industry. Perhaps it’s more that there isn’t enough being invested to yield the return that all could enjoy - a constant theme of the Partnering for Cures conference held in New York this week. Matthew Herper suggested that the real cost for bringing a new drug to market was $5B in Forbes this year. Pharmaceutical R&D is an expensive proposition, but the revenue from a successful R&D effort covers those that fail. And failure is a given in need of rebranding - a common theme across science and technology). Can it cost less?
Taking Advantage of Genomics
Pharma is attempting to change to reduce that failure rate. One long standing aspiration is to take advantage of genomics. In trials where they collect biosamples to perform exploratory pharmacogenomics, they commonly focus their analysis on a subset of patients representing the most likely respondents, based on and limited by the information that is available. In plain language - a best guess. In the vernacular, this would be known as “the most probable sub cohorts” within trials they run.
Improving that guess, and targeting sequencing more efficiently, requires knowing more about the characteristics of patients before the trial begins. Data from previous trials and from public sources are rich veins to be mined. Pharmacogenomics efforts that take place in parallel with pre-clinical development provide the best opportunity to start a trial with solid biomarkers. That work takes samples. And individuals. And more data. That will reduce the spending on herculean data efforts that are repeated across large companies and small and get spending to become more precise.
Our premise is that precision spending will be possible by increasing access to greater breadth and depth of data. The depth of data on the people who are participating in the trials (or not) is the fundamental issue that is impeding efficiency and progress. Reconsenting, particularly as it relates to biospecimens, often cause organizations to not ask questions that would increase the value of the R&D as it applies to pipelines and patients. Precision medicine not only will drive value to patients, it drives business opportunity for decreasing spending on what doesn’t work, derisking the equation by being able to try more times at getting it right.
What Can Be Done?
1. Assemble the Data
Assembling the data, from as many trials as one can, to look for patterns of use and response is one. This is being done today, though we have witnessed it discussed far more than it is implemented. In addition, linking data to existing biospecimens will allow new assays to be brought to bear in the areas of greatest need.
2. Acquire Public Data
Acquiring the data from public resources to organize along with the trial data is another. There are technology capabilities available to do so today, and can be applied to realize value there. Again, biospecimens are key area - many existing samples could be valuable if they were discoverable and truly available.
3. Acquire Personal Data
This is an area that is not currently well addressed. Investing in a prospective collection of broader data on patients and individuals, from a variety of perspectives, could enable increased insight into R&D and trial design & enrollment. It will also allow more efficient application of next-generation technologies by sequencing whole genomes, for instance, from specific known classes of responders or non-responders.
4. Build the Missing Link
Finally, the longitudinal record. The acquisition of longitudinal data is a missing link in the ability for precision medicine to exist. Only by knowing how a patient’s condition changes over time can we target the therapies and diagnostics to areas where they will be most successful.
With these capabilities Pharma will be able to assess which people, under what circumstances, at what times and over what period a therapy is likely to work. They can then more reliably turn potential biomarkers into the companion diagnostic products needed for Precision Medicine to reduce cost and increase value for all.