Rows of clear pills with DNA helices inside and tweezers selecting one capsule

Pharmacogenomics Program

Getting each patient the right drug at the right dose at the right time is the goal of pharmacogenomics, which involves studying how people's specific DNA sequences influence their responses to medications.

The drugs available today to treat cancer, heart disease and other conditions are powerful agents that work as intended in most patients. Yet, in some people, a particular drug at the standard dose might not work well enough or may even trigger a serious adverse reaction. The reasons for this lie, at least in part, in each person's genes.

By considering a patient's unique genetic makeup, physical status, demographic information and testing results, health care teams can now build more-sophisticated algorithms to help predict drug response. When prescribing drugs, doctors can use the information to maximize treatment effectiveness while avoiding potentially life-threatening side effects.

Pharmacogenomics can help answer a broad range of questions, such as:

  • Why does standard chemotherapy eradicate breast cancer in some women but work less effectively in other women?
  • What are new treatment options for men with advanced prostate cancer that has resisted all previous therapies?
  • What is the right blood thinner drug for patients who get a stent for their coronary artery disease?
  • How can rules be added to pharmacy systems to take the patient's genome into consideration for each prescription?
  • How can treatment with antidepressants be better individualized?

Projects

Patients with major depressive disorder are often treated with selective serotonin reuptake inhibitors (SSRIs), a standard of care for this group of patients. However, only about 50% of patients respond to the treatment. Using current methods, it's only possible to predict patient response with 55% accuracy.

Mayo Clinic researchers used an approach based in artificial intelligence (AI) to develop the Analytics and Machine Learning Framework for Omics and Clinical Big Data (ALMOND) study, creating an algorithm that incorporates clinical symptoms, demographic information and genetic biomarkers. The SSRI response prediction accuracy of the ALMOND algorithm is between 80% and 90%.

Mayo Clinic is now implementing the ALMOND algorithm in routine practice to advance individualized SSRI therapy. AI algorithms for other conditions also are in development.

In the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT 10K) Study, researchers sequenced a set of 77 "pharmacogenes" and inserted the results into the electronic health record (EHR); they also placed interpretive reports in participants' medical records.

Most electronic medical record systems are not equipped to alert the pharmacist or physician to drug-gene interactions. The RIGHT10K Study uses infrastructure built at Mayo Clinic that can alert physicians as they choose prescriptions, so patients get the right drug in the right dose at the right time.

Scientists are conducting many studies to determine how genetic variation in these 77 pharmacogenes might affect individual drug responses. New findings from these studies will lead to better individualized drug therapy.

BEAUTY and BEAUTY 2 studies

The Breast Cancer Genome-Guided Therapy (BEAUTY) study performed whole-exome sequencing on women who were newly diagnosed with breast cancer. The sequencing was carried out before and after participants received pre-surgical drug therapy (neoadjuvant therapy).

Pharmacogenomics Program researchers were able to compare the tumor genome before and after neoadjuvant anti-cancer therapy with DNA sequences in participants' normal, noncancerous tissue (germline genome) to observe variations in response to therapy.

Based on the findings from the BEAUTY Study, clinicians are personalizing therapy to help ensure that women with chemotherapy-resistant breast cancer receive the right combination of drugs, resulting in the highest possible chance of a cure. The BEAUTY 2 Study tests the effectiveness of drugs that are not commonly used to treat one of the most aggressive breast cancer subtypes, triple negative breast cancer.

The goal of the study is that patients experience seamless and effective health care in the treatment of breast cancer during the crucial time between diagnosis and surgery.

PROMISE study

Endocrine resistance is common in patients with breast cancer, and while the drug palbociclib (Ibrance) in combination with endocrine therapy has provided substantial improvement in progression free survival in women with metastatic breast cancer, that is not the case for all patients.

A Prospective Study to Evaluate the Role of Tumor Sequencing in Women Receiving Palbociclib for Advanced Hormone Receptor (HR)-Positive Breast Cancer (PROMISE) uses biopsies of participants' metastatic breast cancer to obtain detailed information regarding the genetic makeup of the tumor as well as each participant's germline genome, with the goal of developing personalized treatment approaches to improve patient outcomes.

The Prostate Cancer Medically Optimized Genome Enhanced Therapy (PROMOTE) Study took an approach similar to the BEAUTY breast cancer studies, but for prostate cancer. Pharmacogenomics Program researchers hope to elucidate DNA sequences associated with response to the current first-line therapy of prostate cancer — one of a new generation of androgen deprivation therapies, abiraterone (Zytiga) — to identify additional treatment options for patients with advanced prostate cancer that has resisted all standard therapies.

The Pharmacogenomics Program's breast cancer and prostate cancer studies have also included groundbreaking work with murine "avatars" — tumors that were grown in murine models to make it possible to test drugs in these models rather than in the patient to identify new treatment options.

Patients with coronary artery disease often come into the emergency room requiring placement of one or more coronary artery stents. In the TAILOR-PCI study, researchers studied specific DNA variants that might indicate whether the patient should receive the anticoagulant drug clopidogrel (Plavix) or an alternative drug. This is a question that has vexed cardiologists for years and for which an incorrect decision might result in a clot forming in a patient's heart artery. Safer and more effective treatment decisions will now be possible based on genetic information.

Collaborations

Mayo Clinic and the University of Illinois at Urbana-Champaign jointly established the CCBGM as a National Science Foundation center to develop new and innovative approaches — such as the application of data analytics and artificial intelligence — to facilitate the translation of genomics and other high-dimensional data into clinical care and address other biomedical challenges. The CCBGM invites companies with interest in genome-based challenges in health care discovery to join the center.

The Mayo Clinic and Illinois Alliance for Technology-Based Healthcare was organized in 2010 to advance research, technology and clinical treatment options in health care. The alliance is a framework for collaboration in individualized medicine. It involves innovative educational programs, integrated research activities and projects, and entrepreneurial efforts to deploy and commercialize outcomes of the collaboration.

The Office of Strategic Coordination of the National Institutes of Health (NIH) administers the BD2K program, which funds research and training activities that support the use of big data to advance biomedical research and discovery. This includes efforts to enhance training, resource indexing, methods, tools development, and other data science-related areas.

As part of this large NIH award, Mayo Clinic and the University of Illinois at Urbana-Champaign created the Knowledge Engine for Genomics (KnowEnG, pronounced "knowing") as a center of excellence in big data computing.

Pharmacogenomics: Genes and Drugs

Learn about pharmacogenomics research at Mayo Clinic.

Narrator: Why do life-saving drug therapies work for some patients but not for others? And why does a medication that works well for one person cause adverse side effects in someone else?

Some of the answers may lie in our genetic makeup. That's why researchers in the Center for Individualized Medicine at Mayo Clinic are studying pharmacogenomics to better understand how inherited genetic differences affect an individual's response to drug therapy.

The Human Genome Project

Richard Weinshilboum, M.D., Mary Lou and John H. Dasburg Professor of Cancer Genomics, Director Pharmacogenomics Program: So what the genome is, is the three billion letters of the genetic code that make each of us uniquely the wonderful person we are.

We've never had the ability to do this before. And the Human Genome Project, which I think we can take great pride in, it was an international enterprise that involved Europe, Asia, and the United States, but led by the United States. Basically, set out to do what I think most of us 20 years ago thought would be impossible. I, I didn't think it would happen during my lifetime.

That is to basically give us the outline of the sequence of the human genome. Now, everybody's outline is different, because we all have about 7 million variations there that make us who we are. The genome project though, the way in which it was presented to the public, was as if it was a race to the finish line. No, no, no, no. It was a race to the starting line. Because, once we had that outline, we could then begin trying to figure out how to use that to help us understand diseases like cancer. That we really had no ability to deal with before in any meaningful way, to prevent and to treat. Number two, what made us uniquely who we are in terms of the way we respond to the medications we have.

Narrator: Mayo's researchers use knowledge gained from the Human Genome Project to analyze the genomes of thousands of individuals. An enormous task, since a single human genome contains more than three billion DNA base pairs.

Dr. Liewei Wang, and a team of talented researchers, use rapid sequencing tools to identify biomarkers that can predict the patient's response to drug treatments.

Liewei Wang, M.D., PH.D., Associate Director, Pharmacogenomics Program: Now, because we know the whole genome, the entire genome, and we have the technology to assess entire genome in a much faster and efficient way. So now we can incorporate all the genetic information from your entire genome instead of just looking at individual genes. And, by doing that, we have a complete picture and how the whole genome, may impact response to a certain drug.

Narrator: Analyzing these large complex datasets requires powerful computers that can process data and unprecedented speeds.

Dr. Wang: Eventually, we will have three billion nucleotides coming from one individual, not even meshing many other types of omics: like a polio mix, the microbiome data. So, imagine you try to integrate all of these data and you need automatic assistance and you need very sophisticated algorithm.

Narrator: To tackle this data heavy analysis, Mayo has a strategic partnership with the University of Illinois, bringing together top thinkers in technology and medicine. Supported by funding from the National Science Foundation, this Alliance is exploring better and faster ways to analyze and make sense of the pharmacogenomics team's research data.

BEAUTY Study

Breast Cancer Genome-Guided Therapy

What does this work mean for Mayo Clinic patients?

In the BEAUTY study, researchers performed DNA sequencing on breast cancer patients before and after they undergo drug therapy. Then, they compared the tumors genome, from before and after therapy, against a sequence of the patient's DNA in normal, non-cancerous tissue to match the genomic response to the drugs.

Matthew P. Goetz, M.D., Co-leader Women's Cancer Program, Professor of Oncology: I think that one of the things that we learn from the BEAUTY study was that the cancer genome indeed is complex. And, that we can identify some patients that may not derive as much benefit from standard chemotherapy.

Krishna R. Kalari, PH.D., Associate Professor, Biomedical Informatics: So what we try to do in this study is like we obtain millions of data points from these patients and then try to identify patterns using novel computation methods. And determine what are the novel pathways in each of the molecular subtypes, as well as in individual pathways what are the mutations that are altered, and those mutations that can be druggable for that particular patient.

Judy C. Boughey, M.D., Vice Chair of Research, Department of Surgery, Chair, Division of Surgery Research: As we move forward with BEAUTY2, we will be enrolling patients who have chemotherapy resistant disease, i.e., patients that complete standard chemotherapy and still have tumor left in the breast. And, making novel drugs available for those patients as part of BEAUTY2 to further try to drive to improve the outcomes of women with breast cancer.

TAILOR-PCI Study (Angioplasty Study)

Tailored Antiplatelet Initiation after Percutaneous Coronary Intervention

Narrator: In another study, Mayo researchers are performing rapid DNA analysis of patients undergoing angioplasty procedures to help cardiologists determine the right anticoagulant drug to use after the procedure.

Naveen L. Pereira, M.D., Cardiologist, Professor of Medicine: So, TAILOR-PCI is so important. We are all talking about personalized medicine and how it's going to be helpful for patients and TAILOR-PCI has now already become one of the largest genetic based clinical trials in cardiovascular diseases ever conducted.

So, what we are doing with TAILOR-PCI, is trying to prove that genetic testing could perhaps be helpful to identify those patients, one of the 30 percent of patients who could be at risk by taking Plavix (Clopidogrel), and then giving them the alternative drug with improved outcomes. Less heart attacks, less strokes, less clot in the stents, etc... Unless death perhaps, so that's what we're looking at.

RIGHT Study

Pharmacogenomic Data to Individualize Treatment

Narrator: Through the RIGHT Study, the Center for Individualized Medicine is adding data on drug-gene interactions to patients' electronic medical records.

Dr. Weinshilboum: So the RIGHT Study, which was the right drug, at the right dose, at the right time, for the right person, all that stuff... The RIGHT Study was really a pilot study to test the possibility that we can actually do that. We didn't know whether this would work.

And we picked one thousand thirteen local patients, who had their DNA in the biobank, they enthusiastically consented to participate. And what we then did was sequence all of these genes that we currently know play a role in drug response, put that information preemptively in the electronic health record. So, that when their doctor writes a prescription immediately the electronic health record, if there's going to be a problem because of their genes, sends a message to the doctor to either change the drug, lower the dose, or raise the dose, which I find astonishing.

Pharmacogenomics

Narrator: Clearly, pharmacogenomics has the potential to revolutionize the way drugs are used to treat individual patients. With high tech tools and a growing understanding of the human genome, Mayo researchers are helping to launch an era of truly, individualized medicine. Where patients can get the right drug, at the right time, in the right amount.

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Pharmacogenomic Testing — Karen's Story

Pharmacogenomic testing helps a patient and her family members find answers to health-related questions.

Pharmacogenomics Animation

Pharmacogenomics investigates how changes in genes affect how people respond to medications. Scientists can use a patient's genetic profile to predict a drug's efficacy, guide dosage and improve patient safety.

Individualized Medicine — Holly's Story

Sequencing uncovers the genetic makeup of an aggressive tumor.