The Audacity of Hope: Biomarkers Edition

The end of the nineteenth century was a turning point in the field of medicine marked by incredible accomplishments, such as the discovery of the smallpox vaccine (Stewart and Devlin) and antibiotics (Landsberg). Medical practitioners no longer used herbs and folk remedies to cure patients, but instead looked towards the emerging developments in biomedical research. In the last one hundred years, progress in biotechnology has enabled the pharmaceutical industry to deliver very sophisticated remedies. Advances have allowed illnesses to become increasingly stratified across multiple populations and disease subtypes. Consequently, some therapies have been developed to target specific, molecularly-defined populations. All of these developments hinge on the hope that we can identify gene or protein biomarkers that can differentiate members of individual populations.

The Problem

Biomarkers, and their corresponding assays and drug targets, were initially developed with the intent of making drugs everybody could use. This philosophy is the idealistic “blockbuster drug” model that is currently entrenched in our industry. The movement for personalized medicine and developing drugs for smaller, more well-defined target populations is catching on, however, the large pharmaceutical companies are reluctant to change their research approaches. At the 2010 Personalized Medicine Conference held at the Harvard Medical School, one of the speakers reported that 94% of companies say they have invested in personalized medicine, but only 10% actually have compounds in late clinical development (phase IIb-IV) (Milne). This suggests that these companies have not made a real commitment to personalized medicine in spite of clear signs that this approach is necessary.

Plato's allegory of the cave. Image taken from Prote Philosophia, Ethica, and Politike (http://ontologicalstatus.blogspot.com/2009/09/platos-allegory-of-cave.html).

In the fourth century BCE philosophical dialogue, The Republic, Plato makes an analogy about people confined to live in a cave. The captives were forced to face a wall for their entire lives, unable to see anything except for the shadows cast on this wall by the objects behind them. Hence, the captives never knew the true nature of the shadows. Their understanding of the world was based on their imagined interpretation of what the shadows represented. Today, Plato might say that the pharmaceutical industry is staring at fuzzy shadows of targeted drugs and calling them blockbusters, when in reality they are missing opportunities to identify promising, targeted drug candidates. In today’s environment, it is increasingly difficult to develop drugs for a broad market since it is harder to prove efficacy for a diverse group—especially with the danger of less controllable risks and side effects for the general population. What will distinguish “good” drug targets in the future is going to be the good biomarkers that lead to them.

While serving as diagnostics for diseases and treatment responses, biomarkers will likely prove that the best treatments are targeted ones. The industry is, however, not yet free from blockbuster drug thinking partly due to a degree of difficulty in identifying effective biomarkers that differentiate sick individuals from healthy ones. Plato might liken the freed captives to the relatively few who pursue personalized medicine approaches, but this liberated group may not get support from the bigger companies who are still shackled to the wall. I argue that organizations investing in personalized medicine are the key to freeing the industry from cave captivity.

As investment in biomarker discovery technology increases, we should establish consistent criteria for biomarker evaluation (Mosedale and Grainger). In spite of the current craze for biomarkers, there are few biomarker candidates that have actually been validated. This hype originates from the lack of such consistent criteria. Designing biomarker discovery and validation studies in a consistent manner would give more legitimacy to biomarker discovery programs, making regulatory approval more facile. Evaluation criteria will also help organize technology development around efficiently obtaining the appropriate information from experiments.

In the post-genomic era, we cave captives have seen “the sun” of incredible amounts of biological information. This information illuminates hundreds of thousands of possible drug targets, but casts a shadow on our collective wall that seems to represent the elusive blockbuster drugs for which our industry yearns. To harness the power of this information, we are in great need of another inflection point. The only way to create it is by facilitating innovation in biotechnology for diagnostics. This challenge is exacerbated by uncertainties in diagnostics reimbursement from health insurance plans, regardless of a diagnostic’s clinical value (Quinn). Comfort is the enemy of greatness, and progress in biomarker discovery and assay development is suffering because of comfort with the prevalent model of drug development.

Escaping the Rut of Comfort

Comfort is the word I choose to describe the industry right now because of the findings of a recent report on the biotechnology industry (Ernst & Young). The industry has a positive cash flow, but long-term concerns are looming. Although the profits of the biotechnology industry have increased over the last year, R&D budgets declined by 20% to leave less “innovation capital” for creating targeted drugs. This problem is exacerbated by the fact that newer, smaller companies are receiving less public and private funding than established companies—according to the Ernst & Young report, 82.6% of funding went to just 20% of US biotechnology companies. Adding to these difficulties, FDA drug approvals are scarcer in the post-Vioxx era.

Funding for biotechnology companies over the past several years. Instead of funding smaller companies with "innovation capital", larger companies are increasingly taking a larger share of the available funding.

Funding challenges aside, scientific instruments are dispensing data as excessively as coins from a winning slot machine in Vegas with, ironically, little reward. Today’s arduous methods of proteomic profiling for blood, urine or tissue produce extremely complicated datasets. Worse yet, these complicated methods are actually simpler than the herculean task of analyzing the data from these experiments! Interpreting this data necessitates a breakthrough in information technology. More importantly, we need a technological breakthrough in high-throughput discovery that supersedes the information technology problem by simplifying the data stream. Genomics has microarrays for high-throughput discovery, but the genome is the tip of the iceberg for many disease etiologies. Unfortunately, protein array technology that can query the entire proteome with a variety of probes is not yet mature for commercial use (Ray et al.), but could one day provide a deep understanding of diseases without data as complicated.

Nevertheless, difficult times inspire great breakthroughs. In the last three years, orphan drugs that target rare diseases have increased from 119 to 175 (Ernst & Young), bringing along with them biomarkers and diagnostics to identify the right patients for their drugs. As industry shifts to developing drugs with particular populations in mind, there is an urgent need to focus on biomarkers and diagnostics. Because the pharmaceutical industry of the future will be focused on targeted drugs, it must invest in developing technology for finding biomarkers. This investment will increase the number of commercially available biomarkers, disease diagnostics and treatment efficacy measures.

A Tough Path to a Sunny Future

In just a little over the course of a century, medicine has changed dramatically. Our industry has gone from understanding relatively nothing about the biology of disease to being able to detect molecular risk factors at an early stage. While we continue to make major progress in biomarkers, we face the need to change the methods industry has become comfortable with in the past few decades of enormous growth.

Science is only part of the solution for improved disease detection and monitoring. Three major things need to change to allow biomarkers to make a much-needed impact in the next era of diagnostics and therapeutics: more innovation capital must go to smaller companies; better reimbursement structures need to be devised for biomarker diagnostics; and collaboration between hospitals, biotechnology, pharmaceutical, academic, and federal institutions must be leveraged for technological breakthroughs. Science and technology will certainly continue to progress, but several important factors lie outside the jurisdiction of science, such as the economics of bringing biomarkers and diagnostics to the market. Specifically, the reimbursement system must be re-built to quickly phase in new diagnostics technologies. Even though the medical diagnostics development and funding process allows only the most valid technologies to reach the market, entire innovative efforts are sometimes wiped out by payer unwillingness. If nobody is going to pay for a diagnostic, the economics make it tough to continue making it (Quinn).

The tangible outcome of these three major changes would be faster discovery of valid biomarkers that illuminate the molecular heterogeneity of diseases. More biomarkers will lead to better diagnostics technologies that will allow us to monitor diseases and treatments more effectively than ever before. Downstream of the assays, good biomarkers will even play a critical role aiding pharmaceutical companies early on in the drug discovery process. With an adjustment of innovation capital, reimbursements, and collaboration partners, the resulting technological innovations will be just what our industry needs for another great inflection point in medicine.

References

  1. Ernst & Young, LLP. Beyond Borders: Global Biotechnology Report 2011. Ed. Gautam Jaggi. 2011. PDF.
  2. Landsberg, H. “Prelude to the Discovery of Penicillin.” Isis 40.3 (1949): 225.
  3. Milne, Cristopher-Paul. “Briefings: Investments in Personalized Medicine.” Personalized Medicine: Impacting Healthcare Conference. Harvard Medical School, Boston, MA. 18 Nov. 2010. Lecture.
  4. Mosedale, David, and Grainger, David. “Biomarkers: Lessons from History | Biomarkerblog.” Total Scientific Ltd. Web. 27 June 2011. <http://www.totalscientific.com/biomarkerblog/?p=55>.
  5. Quinn, Bruce. Coverage and Reimbursement for Molecular Diagnostics: Current Issues and Options. Foley Hoag, LLP, 2009. PDF.
  6. Ray, Sandipan, Mehta, Gunjan, Srivastava, Sanjeeva. “Label-free detection techniques for protein microarrays: Prospects, merits and challenges.” Proteomics 10.4 (2010): 731-748.
  7. Stewart, Alexandra J., and Devlin, Phillip M. “The History of the Smallpox Vaccine.” Journal of Infection 52.5 (2006): 329-34.

 

This was an essay I submitted to the Kelly Scientific Future Scientist Program Scholarship Contest this summer while working at Biogen Idec. That’s why this post is a bit more formal (and more meticulously researched) compared to others on this blog.

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