Pharmacogenomics Program – mayo.edu

Drugs and Genes Conference

Getting you the right drug at the right dose at the right time is the goal of pharmacogenomics, which involves studying how your specific DNA sequence influences your response 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 your genes.

By using your unique genetic makeup as a factor when prescribing a drug for you, your doctor can maximize treatment effectiveness while avoiding potentially life-threatening side effects.

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

Results from a subset of the 77 "pharmacogenes" will be placed into the electronic health record (EHR) and an interpretive report will be placed into the patient's medical record.

Most electronic medical record systems are not equipped to alert the pharmacist or physician to these drug-gene interactions. The RIGHT10K study is utilizing the infrastructure built together with the RIGHT study at Mayo Clinic, which alerts to physicians in the drug prescription process so that patients get the right drug at the right time in the right amount.

The BEAUTY study performed whole-genome sequencing before and after neoadjuvant therapy (drug therapy before surgery) in women newly diagnosed with breast cancer.

Pharmacogenomics Program researchers are then comparing then compared the tumor genome before and after neoadjuvant therapy against the patient's germline genome the sequence of DNA in normal, noncancerous tissue in order to match the genomic response to therapy.

Read results of the BEAUTY study.

Based on the findings to-date from BEAUTY, clinicians are personalizing therapy to help ensure that women with breast cancer resistant to current therapy receive the right combination of drugs resulting in the highest chance of a cure. BEAUTY 2 participants will experience this approach and seamless health care in the treatment of breast cancer, during the crucial time between diagnosis and prior to surgery.

The PROMISE study will use participants' biopsies of metastatic breast cancer to obtain detailed information regarding the genetic makeup of the tumor as well as the host (germline) genome, with the goal of developing personalized treatment approaches to improve patient outcomes. Endocrine resistance is common in breast cancer patients, and while the drug palbociclib in combination with endocrine therapy has provided substantial improvements in progression free survival in women with metastatic breast cancer, that is not the case for all patients.

The PROMOTE study took an approach similar to the BEAUTY study, but for prostate cancer. The Pharmacogenomics Program hopes to elucidate the DNA sequences associated with response to therapy in order to identify new treatment options for patients with advanced prostate cancer that has resisted all conventional therapies.

This study also included groundbreaking work with mouse avatars, again to identify new and novel treatment options.

Patients with coronary artery disease often come into the emergency room requiring placement of one or more stents. In the TAILOR-PCI study, we are determining the specific DNA variant that might indicate whether the patient should receive the anticoagulant drug clopidogrel or an alternative drug, a question that has vexed cardiologists for years.

Safer and more effective treatment decisions will be systematically based upon genetic information.

Projects in Computational and Genomic Medicine, such as the joint NIH U54 and an NSFcenter grant project, blend the computational analysis, pharmacogenomics, and supercomputing expertise of the University of Illinois at Urbana-Champaign with the medical informatics and clinical practice expertise of Mayo Clinic. Researchers will develop new and innovative processes, such as artificial intelligence, that facilitate the translation of genomics and other high-dimensional data into clinical care.

The University of Illinois at Urbana-Champaign and Mayo Clinic as well as our affiliate, the University of Chicago, which are leading institutions in these areas and already have strong ties to each other, have established the Center for Computational Biotechnology and Genomic Medicine (CCBGM), a collaborative environment that will improve the applicability, timeliness, efficiency, and accuracy of the computational infrastructure that will address pressing genome-based challenges.

The Mayo Clinic and Illinois Strategic Alliance for Technology-Based Healthcare was organized in 2010 to advance research, technology, and clinical treatment options in health care. It's a collaboration of The Interdisciplinary Health Sciences Initiative at Illinois (IHSI).

The Alliance is a framework for collaboration in individualized medicine, and involves innovative educational programs, integrated research activities and projects, and entrepreneurial modes to deploy and commercialize outcomes.

BD2K funds research and training activities that support the use of Big Data to advance biomedical research and discovery. This includes efforts in enhancing training, resource indexing, methods and tools development, and other data science-related areas. As part of this NIH award, Mayo Clinic is developing tools for standardizing research metadata.

Richard Weinshilboum, M.D., director, Pharmacogenomics Program

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

The Pharmacogenomics Program investigates how variations in genes affect response to medications, thereby using a patient's genetic profile to predict a drug's efficacy, guide dosage and improve patient safety.

Sequencing uncovers genetic makeup of aggressive tumor.

The Center for Individualized Medicine is a strategic priority for the Campaign for Mayo Clinic.

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Read more here:
Pharmacogenomics Program - mayo.edu

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