Personalized Medicine Program Research Articles

Personalized medicine as a model of care to improve patient outcomes, communication, and reduce cost.

e270 Background: Cancer treatment based on an individual’s tumor profiling has been associated with increased time to progression. Despite this, adoption has been impeded by various technical, financial, legislative, and ethical issues. Implementation of a personalized medicine program into a healthcare system with a goal of improving patient outcomes includes clinician and patient education, increased tumor profiling of patients, data sharing/analysis, expanded research, and billing/reimbursement practices. Methods: A personalized medicine program was implemented at a hospital system. Measures of physician practice included attendance at genomic medicine education sessions, utilization of genetic/genomic tests, enrollment of patients into clinical trials, modifications in billing practices, and submission of data for analysis. Reimbursement of off-label pharmaceutical agents as well as use of aggregate data to inform treatment and enrollment in biomarker-based clinical trials was recorded. Frequency of genetic and/or genomic tests relative to physician and patient education and access to research opportunities was also assessed. Early patient outcomes, overall costs of care, access to clinical trials, and changes in knowledge and communication are also being monitored. Results: Although analysis is ongoing, the initial assessment indicates an increased utilization of genetic and genomic tests, clarity in billing practices, improved reimbursement for off label therapies, and consumption of educational opportunities from clinicians to patients/caregivers. Analysis of the first year implementation will be reported, including evaluation of preliminary results relative to quality of life and survivorship. Conclusions: Preliminary analysis of data from implementation of a personalized medicine program indicates that utilizing relevant education, research, aggressive billing and reimbursement processes, and IT infrastructure, can provide patients with the individual therapies which reduce cost and improve survivorship.

Building a Personalized Medicine Program

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsThomas D. BrownThomas D. Brown, MD, MBA, is executive director of the Swedish Cancer Institute, Seattle, Wash.

Abstract 2991: Detection of gene rearrangements using OncoPanel: a targeted next-generation sequencing assay

Abstract Identification of structural gene rearrangements is vital for cancer patients as these events can provide definitive diagnoses, prognostic value, and influence the course of treatment. While FISH, karyotype analysis and aCGH array have traditionally been used to identify and confirm the presence of structural variants, the advent of next generation sequencing has enabled genetic testing including detection of multiple structural variants (SVs) from genomic DNA. To this end, we have developed and validated Oncopanel, a cancer-specific targeted next generation sequencing (NGS) assay designed to detect SNVs, indels, and copy number alterations across 300 genes, and 35 clinically actionable or informative SVs. Each rearrangement was specifically targeted by baiting genomic locations frequently identified to contain breakpoints reported in the literature and publicly available databases. Using BreaKmer, an internally developed SV detection tool (Nucleic Acids Res. 2014 Nov 26, doi: 10.1093/nar/gku1211), rearrangements, including the exact breakpoint coordinates and the genes involved in or adjacent to the breakpoint(s), were identified. Here we examine the utility of Oncopanel using genomic DNA to identify structural variants. We report the results of 3,291 cancer patients tested in our personalized cancer medicine program (Profile), a joint venture between Dana-Farber Cancer Institute, Brigham and Women's Hospital, and Boston Children's Hospital. As compared to conventional cytogenetics, FISH analysis, and molecular detection by PCR methods, Oncopanel's overall sensitivity and specificity for SVs was 81.4% and 100%, respectively. Most discordant results were identified in (1) tumors with SVs involving the IGH enhancer regions (60% of discordant results), or (2) in samples with < 20% tumor (25% of discordant results). Several SVs involving the IGH enhancer regions were missed likely due to lack of Oncopanel coverage. Oncopanel was designed to target a finite sequence pool, but due to IGH enhancer region's large size (1.2Mb), only a small portion of this region was specifically interrogated. Inclusion of all possible IGH enhancer sequences would have hampered the effectiveness of SNV, indel and copy number alteration detection for other cancer critical genes. Discrepant Oncopanel and cytogenetic results were also observed in samples with low tumor purity likely due to masking of variant sequences by stromal contamination. In conclusion, we find that Oncopanel has utility to detect structural variants with a sensitivity of 92%, barring detection of rearrangements involving IGH, and a specificity of 100%. Based on the baiting strategy, detection of many rearrangements can also be interrogated in parallel with SNV, indel and CNV detection resulting in reduced sample input requirements and the inclusion of precise information regarding the breakpoints and the class of rearrangement identified. Citation Format: Elizabeth P. Garcia, Azra H. Ligon, Ryan P. Abo, Paola S. Dal Cin, Stanislawa Weremowicz, Priyanka Shivdasani, Phani K. Davineni, Dimity L. Zepf, Matthew D. Ducar, Paul Van Hummelen, Yonghui Jia, Frank C. Kuo, Lynette M. Sholl, Laura E. MacConaill, Neal I. Lindeman. Detection of gene rearrangements using OncoPanel: a targeted next-generation sequencing assay. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2991. doi:10.1158/1538-7445.AM2015-2991

Emerging roles for pharmacists in clinical implementation of pharmacogenomics.

Pharmacists are uniquely qualified to play essential roles in the clinical implementation of pharmacogenomics. However, specific responsibilities and resources needed for these roles have not been defined. We describe roles for pharmacists that emerged in the clinical implementation of genotype-guided clopidogrel therapy in the University of Florida Health Personalized Medicine Program, summarize preliminary program results, and discuss education, training, and resources needed to support such programs. Planning for University of Florida Health Personalized Medicine Program began in summer 2011 under leadership of a pharmacist, with clinical launch in June 2012 of a clopidogrel-CYP2C19 pilot project aimed at tailoring antiplatelet therapies for patients undergoing percutaneous coronary intervention and stent placement. More than 1000 patients were genotyped in the pilot project in year 1. Essential pharmacist roles and responsibilities that developed and/or emerged required expertise in pharmacy informatics (development of clinical decision support in the electronic medical record), medication safety, medication-use policies and processes, development of group and individual educational strategies, literature analysis, drug information, database management, patient care in targeted areas, logistical issues in genetic testing and follow-up, research and ethical issues, and clinical precepting. In the first 2 years of the program (1 year planning and 1 year postimplementation), a total of 14 different pharmacists were directly and indirectly involved, with effort levels ranging from a few hours per month, to 25-30% effort for the director and associate director, to nearly full-time for residents. Clinical pharmacists are well positioned to implement clinical pharmacogenomics programs, with expertise in pharmacokinetics, pharmacogenomics, informatics, and patient care. Education, training, and practice-based resources are needed to support these roles and to facilitate the development of financially sustainable pharmacist-led clinical pharmacogenomics practice models.

Surveillance recommendations in reducing risk of and optimally managing breast cancer-related lymphedema.

Breast cancer survivors are at increased risk for the development of breast cancer-related lymphedema (BCRL), a chronic, debilitating, and disfiguring condition that is progressive and requires lifelong self-management of symptoms. It has been reported that over 40% of the 2.5 million breast cancer survivors in the United States may meet the criteria for BCRL during their lifetimes. Ongoing surveillance, beginning with pre-operative assessment, has been effective in identifying subclinical lymphedema (LE). A prospective model for surveillance is necessary in order to detect BCRL at an early stage when there is the best chance to reduce risk or slow progression. Physical methods for monitoring and assessment, such as circumferential arm measures, perometry, bioimpedance; exercise programs; prophylactic and early-intervention compression garments; and referral for complete decongestive therapy are all interventions to consider in the development of a BCRL surveillance program. In addition, supportive-educative programs and interactive engagement for symptom self-management should also be implemented. The importance of interdisciplinary collaboration is integral to the success of an effective personalized medicine program in breast cancer-related lymphedema surveillance.

The role of surgeons in building a personalized medicine program.

Changes in technology, with decreases in the cost of molecular profiling, has expanded the interest in creating institution-wide personalized medicine platforms to allow selective assessment of a given patient's tumor in real time, with the ability to utilize that information for patient-care decisions. In order for this approach to function adequately, a multidisciplinary team must be created in an environment with dedicated support at an institutional level.

Clinical pharmacogenetics implementation: Approaches, successes, and challenges

Current challenges exist to widespread clinical implementation of genomic medicine and pharmacogenetics. The University of Florida (UF) Health Personalized Medicine Program (PMP) is a pharmacist-led, multidisciplinary initiative created in 2011 within the UF Clinical Translational Science Institute. Initial efforts focused on pharmacogenetics, with long-term goals to include expansion to disease-risk prediction and disease stratification. Herein we describe the processes for development of the program, the challenges that were encountered and the clinical acceptance by clinicians of the genomic medicine implementation. The initial clinical implementation of the UF PMP began in June 2012 and targeted clopidogrel use and the CYP2C19 genotype in patients undergoing left heart catheterization and percutaneous-coronary intervention (PCI). After 1 year, 1,097 patients undergoing left heart catheterization were genotyped preemptively, and 291 of those underwent subsequent PCI. Genotype results were reported to the medical record for 100% of genotyped patients. Eighty patients who underwent PCI had an actionable genotype, with drug therapy changes implemented in 56 individuals. Average turnaround time from blood draw to genotype result entry in the medical record was 3.5 business days. Seven different third party payors, including Medicare, reimbursed for the test during the first month of billing, with an 85% reimbursement rate for outpatient claims that were submitted in the first month. These data highlight multiple levels of success in clinical implementation of genomic medicine.

APhA–APPM recipients honored for a lifetime of work

The APhA Academy of Pharmacy Practice & Management (APhA–APPM) recognizes the achievements of individuals who have made significant or sustained contributions to pharmacy practice. This year's winners shared their thoughts and insights with Pharmacy Today .

Institutional Profile: University of Florida and Shands Hospital Personalized Medicine Program: Clinical Implementation of Pharmacogenetics

The University of Florida and Shands Hospital recently launched a genomic medicine program focused on the clinical implementation of pharmacogenetics called the Personalized Medicine Program. We focus on a pre-emptive, chip-based genotyping approach that is cost effective, while providing experience that will be useful as genomic medicine moves towards genome sequence data for patients becoming available. The Personalized Medicine Program includes a regulatory body that is responsible for ensuring that evidence-based examples are moved to clinical implementation, and relies on clinical decision support tools to provide healthcare providers with guidance on use of the genetic information. The pilot implementation was with CYP2C19–clopidogrel and future plans include expansion to additional pharmacogenetic examples, along with aiding in implementation in other health systems across Florida.

Personalized Medicine in a Phase I Clinical Trials Program: The MD Anderson Cancer Center Initiative

We initiated a personalized medicine program in the context of early clinical trials, using targeted agents matched with tumor molecular aberrations. Herein, we report our observations. Patients with advanced cancer were treated in the Clinical Center for Targeted Therapy. Molecular analysis was conducted in the MD Anderson Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. The clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients who were not treated with matched targeted therapy. Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001). Keeping in mind that the study was not randomized and patients had diverse tumor types and a median of 5 prior therapies, our results suggest that identifying specific molecular abnormalities and choosing therapy based on these abnormalities is relevant in phase I clinical trials.

University of Florida Clinical and Translational Science Institute: Transformation and Translation in Personalized Medicine

We are constantly reflecting on whether and how our efforts are transformational as we work to achieve the ambitious goals articulated for the University of Florida’s Clinical and Translational Science Institute (UF CTSI). As the only Clinical and Translational Science Award (CTSA) recipient in the fourth most populous state, the UF CTSI must aim to support research and improve health care for 19 million Floridians, 6% of the US population. The strong commitment of our university leadership and a team-science approach has enabled us to move swiftly in the context of a very large comprehensive public research university. The UF CTSI involves two major health systems, agricultural extension offices in all 67 counties in Florida, and numerous partners throughout the state. All of UF’s 16 colleges* participate in the CTSI, which supports 140 faculty and staff; 10 programs; 13 clinical research units; five core labs; and six educational programs. As we enter year three of our grant, the UF CTSI is launching a Personalized Medicine Program – a feat made possible by the transformational changes championed by the National Institutes of Health (NIH), its National Center for Research Resources (NCRR) and the CTSA program. We share this as one of many examples unfolding across the country in which CTSA institutions are adding new capacity for translational research, which in turn is leading to new approaches for how we translate scientific discoveries into medical practice – a need around which the NIH is vigorously seeking to catalyze new breakthroughs.1

Personalized medicine in a phase I clinical trials program: The M. D. Anderson Cancer Center Initiative.

CRA2500 Background: We initiated a personalized medicine program hypothesizing that tumor molecular analysis and use of targeted therapy to counteract the effects of specific aberrations would improve the outcomes of affected patients. Methods: Molecular analysis was performed in the M. D. Anderson CLIA-certified pathology laboratory. Patients whose tumors had an aberration were treated in the Phase I Program with a matched targeted agent, when available. Results: Tumor molecular analysis was feasible in 852 (89%) of 955 consecutive patients with advanced cancer. Of 852 patients (median, age 56 yrs; prior therapies 4), 354 (41.5%) had ≥ 1 aberration: 10% of patients had a PIK3CA mutation; 19% KRAS; 8% NRAS; 19% BRAF; 3% EGFR; and 2% had a CKIT mutation; 21% had PTEN loss. Results are shown in the table. Median time to treatment failure (TTF) in 161 patients with 1 aberration treated with matched targeted therapy was 5.3 months (95%CI: 4.1, 6.6) vs 3.2 months (95%CI: 2.9 – 4.0) for their prior systemic antitumor therapy (prior to referral to phase I) (p= .0003). For patients with 1 aberration, the CR+PR rate was 29% with matched targeted therapy vs. 8% without matching (p = .0001). The CR+PR rate was 6% in 438 patients without molecular testing treated on the same studies. Conclusions: Preliminary results suggest that in early clinical trials matching patients with targeted drugs based on their molecular profile results in (a) longer TTF compared to their prior therapy and (b) higher rates of response, survival and TTF compared to those seen in patients treated without molecular matching. Support: 3UL1 RR024148 04 S1 and IPCT. [Table: see text]