Increasing the Safety and Efficacy of Precision Medicine through Next-Generation Clinical Decision Support Tools
Every year, millions of people in the US suffer drug side effects, from serious to life threatening, caused by treatment with inappropriate prescription medications. Even the most commonly used drugs can cause adverse reactions resulting in a range of side effects, from weight gain and heart disease to depression and, in some cases, suicidal impulses.
For several decades, researchers have attempted to reduce the occurrence of drug side effects through pharmacogenomics. Using genetic tests, this early phase approach to drug-gene testing enabled health care providers to identify which medications were likely to cause adverse reactions in a specific patient. However, the tests were limited in various ways, including their ability to predict adverse interactions among multiple drugs (drug-drug interactions), drug doses, and beneficial drug combinations.
In recent years, a second-generation approach to drug-gene testing—known as pharmacoepigenomics—has offered a more sophisticated understanding of how genes are regulated and expressed, and what negative effects are likely to occur.
Pharmacophenomics – A New Research Paradigm in Personalized Medicine
In 2015, a team of University of Michigan biomedical researchers and bioinformatics specialists led by Dr. Brian D. Athey, Michael Savageau Collegiate Professor, Founding Chairman of Michigan’s Department of Bioinformatics and Computational Medicine (DCMB), and Professor of Psychiatry, set out to develop a more advanced and detailed approach to pharmacoepigenomic research, a field they have helped to create. Their goal was to increase the precision of pharmacologically-based clinical treatments and assure patient safety by providing an exhaustive analysis of individual genes and how their behavior is regulated in response to specific drugs.
Their work was inspired by two new discoveries in the field of gene regulation: the Regulome and the 4-D Nucleome. Using a combination of next-generation “phenomic” variants, bioinformatics and high-throughput analysis, Athey’s team was able to generate a phenomic profile of multiple genes that reflected the impact not only of a specific drug, but also other external factors such as ethnicity, environment, family history, and sociological effects. This information was then used to generate a highly predictive, evidence-based physiological assessment (phenotype) of a patient’s unique drug response and tolerance—personalized data that could guide prescribing decisions across many therapeutic areas and medication classes.
Capturing the Global Market Potential: The Launch of Phenomics Health
Athey joined forces with Dr. James S. Burns, a biotechnology entrepreneur and former chairman and CEO of Assurex Health, Inc., a precision medicine company focused on treatment decision support products. Working with Tech Transfer, the two licensed more than a half-dozen patent applications developed in Athey’s laboratory, developed a business plan and, in 2017, launched Phenomics Health Inc. (PHI). Their first broad platform patent was just issued by the US Patent and Trademark Office.
As a next step in the commercialization process, PHI will conduct validation studies for its patent-pending Pharmacophenomic Clinical Decision Support Platform in collaboration with the University of Michigan, the UM-Peking University Health Systems Center (PUHSC) Joint Institute (LI) in Ann Arbor and Beijing, and other national and international partners.
PHI’s clinical treatment decision platform has the potential to address multiple healthcare areas, disease categories, and medical disorders. First-phase products will include precision medical products and services for stress, depression, anxiety and bipolar disorders. Future product roll-outs will address conditions ranging from chronic pain, addiction and schizophrenia to cardiovascular disorders. The company will also provide contract-based and collaborative research services with pharmaceutical companies to identify and test new and repurposed drugs.
While acknowledging the strong market potential for PHI’s bioinformatics-based pharmacophenomics platform, Athey emphasizes that the company’s mission is focused on substantially improving treatment outcomes for patients with various medical conditions. For example, PHI’s platform has identified multiple genetic variants for ketamine, a promising antidepressant, that can sort patients among those who would respond from those who would suffer adverse reactions from the medication.
As Athey noted, “This work is about helping patients. PHI has the capability to streamline medical care, avoid adverse events and drug reactions, and enable physicians and medical systems to deliver better healthcare. We are also poised to make a tremendous contribution to pharmacological treatment and research. Right now we’re taking it one step at a time.”