PDX models for functional precision oncology and discovery science

Precision oncology relies on detailed molecular analysis of how diverse tumours respond to various therapies, with the aim to optimize treatment outcomes for individual patients. Patient-derived xenograft (PDX) models have been key to preclinical validation of precision oncology approaches, enabling the analysis of each tumour's unique genomic landscape and testing therapies that are predicted to be effective based on specific mutations, gene expression patterns or signalling abnormalities. To extend these standard precision oncology approaches, the field has strived to complement the otherwise static and often descriptive measurements with functional assays, termed functional precision oncology (FPO). By utilizing diverse PDX and PDX-derived models, FPO has gained traction as an effective preclinical and clinical tool to more precisely recapitulate patient biology using in vivo and ex vivo functional assays. Here, we explore advances and limitations of PDX and PDX-derived models for precision oncology and FPO. We also examine the future of PDX models for precision oncology in the age of artificial intelligence. Integrating these two disciplines could be the key to fast, accurate and cost-effective treatment prediction, revolutionizing oncology and providing patients with cancer with the most effective, personalized treatments.

Development of Customizable Implementation Guides to Support Clinical Adoption of Pharmacogenomics: Experiences of the Implementing GeNomics In pracTicE (IGNITE) Network

Introduction

Clinical adoption of genomic medicine has lagged behind the pace of scientific discovery. Practice-based resources can help overcome implementation challenges.

Methods

In 2015, the IGNITE (Implementing GeNomics In pracTicE) Network created an online genomic medicine implementation resource toolbox that was expanded in 2017 to incorporate the ability for users to create targeted implementation guides. This expansion was led by a multidisciplinary team that developed an evidence-based, structured framework for the guides, oversaw the technical process/build, and pilot tested the first guide, CYP2C19-Clopidogrel Testing Implementation.

Results

Sixty-five resources were collected from 12 institutions and categorized according to a seven-step implementation framework for the pilot CYP2C19-Clopidogrel Testing Implementation Guide. Five months after its launch, 96 CYP2C19-Clopidogrel Testing Implementation Guides had been created. Eighty percent of the resources most frequently selected by users were created by IGNITE to fill an identified resource gap. Resources most often included in guides were from the test reimbursement (22%), Implementation support gathering (22%), EHR integration (17%), and genetic testing workflow steps (17%).

Conclusion

Lessons learned from this implementation guide development process provide insight for prioritizing development of future resources and support the value of collaborative efforts to create resources for genomic medicine implementation.

PARC report: a health-systems focus on reimbursement and patient access to pharmacogenomics testing

Pharmacogenomics test coverage and reimbursement are major obstacles to clinical uptake. Several early adopter programs have been successfully initiated through dedicated investments by federal and institutional research funding. As a result of research endeavors, evidence has grown sufficiently to support development of pharmacogenomics guidelines. However, clinical uptake is still limited. Third-party payer support plays an important role in increasing adoption, which to date has been limited to reactive single-gene testing. Access to and interest in direct-to-consumer genetic testing are driving demand for increasing healthcare providers and third-party awareness of this burgeoning field. Pharmacogenomics implementation models developed by early adopters promise to expand patient access and options, as testing continues to increase due to growing consumer interest and falling test prices.

Insights From a Temporal Assessment of Increases in US Private Payer Coverage of Tumor Sequencing From 2015 to 2019

OBJECTIVES

To examine the temporal trajectory of insurance coverage for next-generation tumor sequencing (sequencing) by private US payers, describe the characteristics of coverage adopters and nonadopters, and explore adoption trends relative to the Centers for Medicare and Medicaid Services' National Coverage Determination (CMS NCD) for sequencing.

METHODS

We identified payers with positive coverage (adopters) or negative coverage (nonadopters) of sequencing on or before April 1, 2019, and abstracted their characteristics including size, membership in the BlueCross BlueShield Association, and whether they used a third-party policy. Using descriptive statistics, payer characteristics were compared between adopters and nonadopters and between pre-NCD and post-NCD adopters. An adoption timeline was constructed.

RESULTS

Sixty-nine payers had a sequencing policy. Positive coverage started November 30, 2015, with 1 payer and increased to 33 (48%) as of April 1, 2019. Adopters were less likely to be BlueCross BlueShield members (P < .05) and more likely to use a third-party policy (P < .001). Fifty-eight percent of adopters were small payers. Among adopters, 52% initiated coverage pre-NCD over a 25-month period and 48% post-NCD over 17 months.

CONCLUSIONS

We found an increase, but continued variability, in coverage over 3.5 years. Temporal analyses revealed important trends: the possible contribution of the CMS NCD to a faster pace of coverage adoption, the interdependence in coverage timing among BlueCross BlueShield members, the impact of using a third-party policy on coverage timing, and the importance of small payers in early adoption. Our study is a step toward systematic temporal research of coverage for precision medicine, which will inform policy and affordability assessments.

An Electronic Strategy for Eliminating Unnecessary Duplicate Genetic Testing

OBJECTIVES

To determine the impact of an electronic intervention designed to block duplicate constitutional genetic tests.

METHODS

We constructed, implemented, and studied an electronic intervention that stopped duplicate genetic tests. The activation frequency, types of tests affected, and cost savings achieved with this intervention were determined. The frequency and justification of override requests were also studied.

RESULTS

This intervention stopped 710 unnecessary duplicate genetic tests over a 3-year period and saved $98,596. The tests with the highest numbers of alerts were those used for screening presurgical or transplant patients and were commonly part of an order set or test panel. Most override requests were justified because of the lack of exclusion codes in the initial programming.

CONCLUSIONS

Electronic interventions that stop duplicate genetic testing, if properly constructed, can reduce waste, save health care dollars, and facilitate patient care by directing the provider to a test that has already been performed.

Pharmacogenomic Testing In Pediatrics: Navigating The Ethical, Social, And Legal Challenges

For the past several years, the implementation of pharmacogenetic (PGx) testing has become widespread in several centers and clinical practice settings. PGx testing may be ordered at the point-of-care when treatment is needed or in advance of treatment for future use. The potential benefits of PGx testing are not limited to adult patients, as children are increasingly using medications more often and at earlier ages. This review provides some background on the use of PGx testing in children as well as mothers (prenatally and post-natally) and discusses the challenges, benefits, and the ethical, legal, and social implications of providing PGx testing to children.

Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines

Despite monumental advances in genomics, relatively few health care provider organizations in the United States offer personalized or precision medicine as part of the routine clinical workflow. The gaps between research and applied genomic medicine may be a result of a cultural gap across various stakeholders representing scientists, clinicians, patients, policy makers, and third party payers. Scientists are trained to assess the health care value of genomics by either quantifying population-scale effects, or through the narrow lens of clinical trials where the standard of care is compared with the predictive power of a single or handful of genetic variants. While these metrics are an essential first step in assessing and documenting the clinical utility of genomics, they are rarely followed up with other assessments of health care value that are critical to stakeholders who use different measures to define value. The limited value assessment in both the research and implementation science of precision medicine is likely due to necessary logistical constraints of these teams; engaging bioethicists, health care economists, and individual patient belief systems is incredibly daunting for geneticists and informaticians conducting research. In this narrative review, we concisely describe several definitions of value through various stakeholder viewpoints. We highlight the existing gaps that prevent clinical translation of scientific findings generally as well as more specifically using two present-day, extreme scenarios: (1) genetically guided warfarin dosing representing a handful of genetic markers and more than 10 years of basic and translational research, and (2) next-generation sequencing representing genome-dense data lacking substantial evidence for implementation. These contemporary scenarios highlight the need for various stakeholders to broadly adopt frameworks designed to define and collect multiple value measures across different disciplines to ultimately impact more universal acceptance of and reimbursement for genomic medicine.

Insurance coverage does not predict outcomes of genetic testing: The search for meaning in payer decisions for germline cancer tests

In this work, we explore the results of germline cancer genetic tests in individuals whose insurance would not cover this testing. We enrolled 31 patients with a personal history of cancer whose health insurer denied coverage for a clinical germline cancer panel genetic test recommended by a medical genetics provider into a study providing exome sequencing and return of cancer-related results. Five participants (16%) had a pathogenic variant identified related to increased cancer risk. Three participants (10%) had a variant of uncertain significance (VUS) in a gene related to their cancer history. These rates are not significantly different than the 12% rate of pathogenic or likely pathogenic (P/LP) variants and VUS in 1,462 patients approved by insurance to have a similar clinical germline cancer test (p = .59 for P/LP variants; p = .87 for VUS; Shirts et al., Genet Med, 18:974, 2016). Health insurance guidelines may not meaningfully differentiate between patients with cancer who are likely to benefit from germline cancer genetic testing and those who will not. Failure to identify pathogenic variants in this research cohort would have led to suboptimal care. Strategic evaluation of current germline cancer genetic testing coverage policies is needed to appropriately deliver precision medicine.

Implementation and obstacles of pharmacogenetics in clinical practice: An international survey

AIMS

Eight years ago, a paper-based survey was administered during the World Pharma 2010 meeting, asking about the challenges of implementing pharmacogenetics (PGx) in clinical practice. The data collected at the time gave an idea about the progress of this implementation and what still needs to be done. Since then, although there have been major initiatives to push PGx forward, PGx clinical implementation may still be facing different challenges in different parts of the world. Our aim was therefore to distribute a follow-up international survey in electronic format to elucidate an overview on the current stage of implementation, acceptance and challenges of PGx in academic institutions around the world.

METHODS

This is an online anonymous LimeSurvey-based study launched on 11 November 2018. Survey questions were adapted from the initially published manuscript in 2010. An extensive web search for worldwide scientists potentially involved in PGx research resulted in a total of 1973 names. Countries were grouped based on the Human Development Index.

RESULTS

There were 204 respondents from 43 countries. Despite the wide availability of PGx tests, the consistently positive attitude towards their applications and advances in the field, progress of the clinical implementation of PGx still faces many challenges all around the globe.

CONCLUSIONS

Clinical implementation of PGx started over a decade ago but there is a gap in progress around the globe and discrepancies between the challenges reported by different countries, despite some challenges being universal. Further studies on ways to overcome these challenges are warranted.

Precision Pharmacotherapy: Integrating Pharmacogenomics into Clinical Pharmacy Practice

Precision pharmacotherapy encompasses the use of therapeutic drug monitoring; evaluation of liver and renal function, genomics, and environmental and lifestyle exposures; and analysis of other unique patient or disease characteristics to guide drug selection and dosing. This paper articulates real-world clinical applications of precision pharmacotherapy, focusing exclusively on the emerging field of clinical pharmacogenomics. This field is evolving rapidly, and clinical pharmacists now play an invaluable role in the clinical implementation, education, and research applications of pharmacogenomics. This paper provides an overview of the evolution of pharmacogenomics in clinical pharmacy practice, together with recommendations on how the American College of Clinical Pharmacy (ACCP) can support the advancement of clinical pharmacogenomics implementation, education, and research. Commonalities among successful clinical pharmacogenomics implementation and education programs are identified, with recommendations for how ACCP can leverage and advance these common themes. Opportunities are also provided to support the research needed to move the practice and application of pharmacogenomics forward.

The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study: Protocol for a point-of-care randomized controlled trial of statin pharmacogenetics in primary care

BACKGROUND

The association between the SLCO1B1 rs4149056 variant and statin-associated muscle symptoms (SAMS) is well validated, but the clinical utility of its implementation in patient care is unknown.

DESIGN

The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study is a pseudo-cluster randomized controlled trial of SLCO1B1 genotyping among statin-naïve primary care and women's health patients across the Veteran Affairs Boston Healthcare System. Eligible patients of enrolled primary care providers are aged 40-75 and have elevated risk of cardiovascular disease by American College of Cardiology/American Heart Association (ACC/AHA) guidelines. Patients give consent by telephone in advance of an upcoming appointment, but they are enrolled only if and when their provider co-signs an order for SLCO1B1 testing, performed on a blood sample already collected in clinical care. Enrolled patients are randomly allocated to have their providers receive results through the electronic health record at baseline (PGx + arm) versus after 12 months (PGx- arm). The primary outcome is the change in low-density lipoprotein cholesterol (LDL-C) after one year. Secondary outcomes are concordance with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for simvastatin prescribing, concordance with ACC/AHA guidelines for statin use, and incidence of SAMS. With 408 patients, the study has >80% power to exclude a between-group LDL-C difference of 10 mg/dL (non-inferiority design) and to detect between-group differences of 15% in CPIC guideline concordance (superiority design).

CONCLUSION

The outcomes of the I-PICC Study will inform the clinical utility of preemptive SLCO1B1 testing in the routine practice of medicine, including its proposed benefits and unforeseen risks.

Impact of SLCO1B1 Pharmacogenetic Testing on Patient and Healthcare Outcomes: A Systematic Review

Demonstrated improvements in patient outcomes will facilitate the clinical implementation of pharmacogenetic testing. Using the association between solute carrier organic anion transporter family member 1B1 (SLCO1B1) and statin-associated muscle symptoms (SAMSs) as a model, we conducted a systematic review of patient outcomes after delivery of SLCO1B1 results. Using PubMed and Embase searches through December 19, 2017, we identified 37 eligible records reporting preliminary or final outcomes, including six studies delivering only SLCO1B1 results and five large healthcare system-based implementation projects of multipharmacogene panels. Two small trials have demonstrated at least short-term improvements in low-density lipoprotein cholesterol after SLCO1B1 testing among previously statin intolerant patients. Evidence from large implementation projects suggests that SLCO1B1 results may change prescribing patterns for some high-risk patients. No study has reported improvements in SAMSs or cardiovascular events or tracked the economic outcomes of SLCO1B1 testing. Ongoing studies should collect and report outcomes relevant to pharmacogenetics stakeholders.

Preemptive pharmacogenetic testing: exploring the knowledge and perspectives of US payers

PURPOSE

Preemptive pharmacogenetic testing aims to optimize medication use by having genetic information at the point of prescribing. Payers’ decisions influence implementation of this technology. We investigated U.S. payers’ knowledge, awareness, and perspectives on preemptive pharmacogenetic testing.

METHODS

A qualitative study was conducted using semi-structured interviews. Participants were screened for eligibility through an online survey. A blended inductive and deductive approach was used to analyze the transcripts. Two authors conducted an iterative reading process to code and categorize the data.

RESULTS

Medical or pharmacy directors from 14 payer organizations covering 122 million U.S. lives were interviewed. Three concept domains and ten dimensions were developed. Key findings include: clinical utility concerns and limited exposure to preemptive germline testing, continued preference for outcomes from randomized controlled trials, interest in guideline development, importance of demonstrating an impact on clinical decision making, concerns of downstream costs and benefit predictability, and the impact of public stakeholders such as the FDA and CMS.

CONCLUSION

Both barriers and potential facilitators exist to developing cohesive reimbursement policy for pharmacogenetics, and there are unique challenges for the preemptive testing model. Prospective outcome studies, more precisely defining target populations, and predictive economic models are important considerations for future research.