Researcher, physician, and entrepreneur, Ruaño has traded the bench for clinical records, the dishes for drug formularies, and the DNA sequencing machine for a personal computer that, with the click of a mouse, can call up a patient’s genetic profile. To Ruaño, the future of personalized medicine lies at the interface between patient and doctor.

“I want to stress the ‘bedside’ in the bench-to-bedside,” he says. “In fact, I want to turn that paradigm around, from patient care to mechanism of drug action.”

The Chasm between Bench and Bedside

He is referring to the traditional way that researchers have viewed drug development – as a linear pipeline, beginning with basic research at the intake and ending with a drug in a pharmacy at the output. For decades, this approach has generated extraordinary knowledge and many lifesaving therapies.

Even so, investigators have encountered many challenges in this traditional process. 

The Human Genome Project, and subsequent research studies, have generated vast amounts of genetic information. But without better tools for sharing the information at each step in the pipeline, data has been slow to travel from what gets evaluated at the bench to what gets administered at the bedside.

Ruaño argues that one solution is to turn the data flow backwards, or direct it two ways. This approach is already beginning to open up some of the choke points, and thus apply knowledge gleaned from basic research studies into “clinically actionable” resources.

The Statin Story

For example, Ruaño works with heart disease medications called statins, which lower cholesterol. Statins provide dramatic benefits for patients with high cholesterol.  In fact, one NIH official said that if all patients took their statins according to guidelines, heart disease would no longer be the number one killer in the United States.¹ In addition, research has shown that every dollar spent on statins yields health gains valued at up to $9.44.²

Use of any medical intervention involves balancing risks and benefits.  In rare instances, patients who are taking statins at high doses experience a range of side effects, from muscle cramps to severe muscle damage and liver toxicity.

Ruaño wants to avoid such disabling side effects, particularly because so many individuals do benefit from the drugs.

Thus, he has teamed up with the director of cardiology at Hartford Hospital, in Connecticut, Paul D. Thompson, M.D. The two have recruited 400 patients – now taking statins – to donate blood samples for DNA analysis. In fact, Ruaño has started a company, Genomas, to conduct those analyses. At the same time, cardiologists at Hartford Hospital are conducting business as usual – monitoring the patients for changes in levels of blood molecules that flag eventual muscle and liver toxicity.

When the two teams combine data, breakthroughs emerge. As they reported in the journal Pharmacogenomics, the researchers discovered that statin-taking patients who develop side effects – as measured by higher levels of a blood enzyme called creatine kinase – also are carriers of specific DNA markers, termed single nucleotide polymorphisms (SNPs).  More specifically, these SNPs occur in 10 genes that control proper blood vessel functioning.

By contrast, those patients who do not experience side effects are carriers of other SNPs that are actually protective of untoward effects.

Taken together, these findings mean that there are genes, related to blood vessels, involved in the risk of developing a negative response to statins. And there are also protective genes with different activities involved in stopping the rare side effects.

Creating New Diagnostics

This knowledge, in its own right, is interesting to basic researchers. Knowing that blood vessel-controlling genes such as angiotensin II type I receptor and nitric oxide synthase 3 respond to statins can help uncover new mechanisms behind heart disease.

But resting on those basic research laurels is not enough if personalized medicine is to advance into the clinic.

“If you could help the doctor prescribe more accurately – to avoid side effects, improve efficacy, or to stage the disease – then you could create a diagnostic of great medical value,” Ruaño says.

Ruaño is now actualizing this type of diagnostic. He begins by choosing genetic responses with the most statistical power. His team at Genomas then assembles those highlighted genes into actual tests. These tests can potentially predict who is going to experience side effects and who is naturally protected from them. And these tests are intended to work before statin therapy begins. (Previously, doctors had only blood tests that monitor patients already taking their medications).

A New Wave of Genetic Diagnostic

This kind of diagnostic, based on gene ensembles, represents a breakthrough, not only in heart disease, but also in the realm of personalized medicine.

First, the test is individualized and predictive. The idea is that every person has a unique genetic proclivity for drug response. But taken together, these individual responses fit into patterns, some associated with negative drug responses and others associated with positive ones. Thus, if you measure enough people, you can accrue all the patterns, and so use that information to steer individuals towards the best treatments early on.

Second, the novel diagnostics involve many genes, unlike genetic tests for cystic fibrosis or Huntington’s disease, which give “yes” or “no” answers based on one gene mutation. Multi-gene tests allow researchers to incorporate many more bits of genetic information that might factor in – creating a spectrum of responses and a range of treatments.

Ruaño has also successfully created innovative technology to support this new wave of genetic diagnostics. While at BIOS, he developed a DNA analysis tool that became the first pharmacogenomic test approved by the FDA. It is called the TRUGENE® HIV-1 Genotyping Test, marketed worldwide by Bayer.  This new technology contains diagnostics for monitoring HIV-resistant strains and for guiding antiretroviral therapy, thereby enabling researchers to deliver resistance information to physicians, and allowing physicians to make more informed treatment decisions for their patients.

Back to the Bench

At the same time, the genetic knowledge emerging from testing in the clinic also feeds back to benefit the fundamental work of pharmaceutical innovators and basic researchers. For example, results from Ruaño’s statin work show all statins do not act genetically alike.

“That might explain their differences in side effects,” Ruaño says.

And pharmaceutical innovators can use that knowledge to better tailor their drugs toward more desired outcomes.

Meanwhile, basic researchers also obtain new clues to the biochemical culprits that cause disease. For example, Ruaño had uncovered several unsuspected genes that act in response to statins. These regulate smooth muscle function in a pathway never before associated with heart disease. 

“That, hopefully, will trigger some basic science investigators to modulate these genes in animal models,” Ruaño says. 

And these animal models might help in the discovery of new molecular pathways and targets for heart disease therapeutics.

The Physician as User

Because the newer tests are multi-genetic, their results involve statistical probabilities. In other words, the answers situate an individual patient in a continuum of risk. Ruaño points out that manufacturers need to take this complexity into account and, therefore, design ways to make the tests doctor-friendly.

“We cannot expect all physicians to be geneticists any more than manufacturers of imaging devices expect doctors to have Ph.D.s in physics or engineering,” Ruaño asserts.

Thus, he has come up with one clearer way to depict complex statistical analyses. On their personal computers, doctors get an image, a bell curve. The patient’s genetic result is a dot on that curve.

If the patient falls near the middle, the drug is a good choice. But if he or she falls near the right side, then the risk is higher for getting untoward side effects. Another drug might work better. Too far left on the curve, and the person may have a genetic makeup that protects them from the side effect. 

This user-friendly idea is but one example of what will emerge in this new paradigm of diagnostic development.

“The people who have the most use for these technologies are the physicians, those who make decisions on a daily basis,” he says.  “We can do so much better if we can provide the guidance.”

This article is based on a personal interview with Dr. Ruaño.

¹G. Kolata, "U. S. Panel Backs Broader Steps to Reduce Risk of Heart Attacks," The New York Times, 16 May 2001, sec. A, p.1.

² Impact of Medicines: Chart Pack, page 39, chart 21 http://www.innovation.org/documents/Value%20of%20Medicine%20FINAL%200712061.pdf