Implementation of pharmacogenomics into inpatient general medicine.

Pharmacogenomics is a crucial piece of personalized medicine. Preemptive pharmacogenomic testing is only used sparsely in the inpatient setting and there are few models to date for fostering the adoption of pharmacogenomic treatment in the inpatient setting. We created a multi-institutional project in Chicago to enable the translation of pharmacogenomics into inpatient practice. We are reporting our implementation process and barriers we encountered with solutions. This study, 'Implementation of Point-of-Care Pharmacogenomic Decision Support Accounting for Minority Disparities', sought to implement pharmacogenomics into inpatient practice at three sites: The University of Chicago, Northwestern Memorial Hospital, and the University of Illinois at Chicago. This study involved enrolling African American adult patients for preemptive genotyping across a panel of actionable germline variants predicting drug response or toxicity risk. We report our approach to implementation and the barriers we encountered engaging hospitalists and general medical providers in the inpatient pharmacogenomic intervention. Our strategies included: a streamlined delivery system for pharmacogenomic information, attendance at hospital medicine section meetings, use of physician and pharmacist champions, focus on hospitalists' care and optimizing system function to fit their workflow, hand-offs, and dealing with hospitalists turnover. Our work provides insights into strategies for the initial engagement of inpatient general medicine providers that we hope will benefit other institutions seeking to implement pharmacogenomics in the inpatient setting.

Clinically actionable genotypes for anticancer prescribing among >1500 patients with pharmacogenomic testing.

BACKGROUND: In recent years, there has been increasing evidence supporting the role of germline pharmacogenomic factors predicting toxicity for anticancer therapies. Although somatic genomic data are used frequently in oncology care planning, germline pharmacogenomic testing is not. This study hypothesizes that comprehensive germline pharmacogenomic profiling could have high relevance for cancer care. METHODS: Between January 2011 and August 2020, patients at the University of Chicago Medical Center were genotyped across custom germline pharmacogenomic panels for reasons unrelated to cancer care. Actionable anticancer pharmacogenomic gene/drug interactions identified by the FDA were defined including: CYP2C9 (erdafitinib), CYP2D6 (gefitinib), DPYD (5-fluorouracil and capecitabine), TPMT (thioguanine and mercaptopurine), and UGT1A1 (belinostat, irinotecan, nilotinib, pazopanib, and sacituzumab-govitecan hziy). The primary objective was to determine the frequency of individuals with actionable or high-risk genotypes across these 5 key pharmacogenes, thus potentially impacting prescribing for at least 1 of these 11 commonly prescribed anticancer therapies. RESULTS: Data from a total of 1586 genotyped individuals were analyzed. The oncology pharmacogene with the highest prevalence of high-risk, actionable genotypes was UGT1A1, impacting 17% of genotyped individuals. Actionable TPMT and DPYD genotypes were found in 9% and 4% of patients, respectively. Overall, nearly one-third of patients genotyped across all 5 genes (161/525, 31%) had at least one actionable genotype. CONCLUSIONS: These data suggest that germline pharmacogenomic testing for 5 key pharmacogenes could identify a substantial proportion of patients at risk with standard dosing, an estimated impact similar to that of somatic genomic profiling. LAY SUMMARY: Differences in our genes may explain why some drugs work safely in certain individuals but can cause side effects in others. Pharmacogenomics is the study of how genetic variations affect an individual's response to medications. In this study, an evaluation was done for important genetic variations that can affect the tolerability of anticancer therapy. By analyzing the genetic results of >1500 patients, it was found that nearly one-third have genetic variations that could alter recommendations of what drug, or how much of, an anticancer therapy they should be given. Performing pharmacogenomic testing before prescribing could help to guide personalized oncology care.

Anesthesia providers as stakeholders to adoption of pharmacogenomic information in perioperative care.

OBJECTIVES: Integration of pharmacogenomics into clinical care is being studied in multiple disciplines. We hypothesized that understanding attitudes and perceptions of anesthesiologists, critical care and pain medicine providers would uncover unique considerations for future implementation within perioperative care. METHODS: A survey (multiple choice and Likert-scale) was administered to providers within our Department of Anesthesia and Critical Care prior to initiation of a department-wide prospective pharmacogenomics implementation program. The survey addressed knowledge, perceptions, experiences, resources and barriers. RESULTS: Of 153 providers contacted, 149 (97%) completed the survey. Almost all providers (92%) said that genetic results influence drug therapy, and few (22%) were skeptical about the usefulness of pharmacogenomics. Despite this enthusiasm, 87% said their awareness about pharmacogenomic information is lacking. Feeling well-informed about pharmacogenomics was directly related to years in practice/experience: only 38% of trainees reported being well-informed, compared to 46% of those with 1-10 years of experience, and nearly two-thirds with 11+ years (P < 0.05). Regarding barriers, providers reported uncertainty about availability of testing, turnaround time and whether testing is worth financial costs. CONCLUSIONS: Anesthesiology, critical care and pain medicine providers are optimistic about the potential clinical utility of pharmacogenomics, but are uncertain about practical aspects of testing and desire clear guidelines on the use of results. These findings may inform future institutional efforts toward greater integration of genomic results to improve medication-related outcomes.

Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial.

BACKGROUND: Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS: The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS: Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS: Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.

Impact of CYP2D6 Pharmacogenomic Status on Pain Control Among Opioid-Treated Oncology Patients.

BACKGROUND: Several opioids have pharmacogenomic associations impacting analgesic efficacy. However, germline pharmacogenomic testing is not routinely incorporated into supportive oncology. We hypothesized that CYP2D6 profiling would correlate with opioid prescribing and hospitalizations. MATERIALS AND METHODS: We analyzed 61,572 adult oncology patients from 2012 to 2018 for opioid exposures. CYP2D6 metabolizer phenotype (ultra-rapid [UM], normal metabolizer [NM], intermediate [IM], or poor [PM]), the latter two of which may cause inefficacy of codeine, tramadol, and standard-dose hydrocodone, was determined for patients genotyped for reasons unrelated to pain. The primary endpoint was number of opioid medications received during longitudinal care (IM/PMs vs. NMs). Secondary endpoint was likelihood of pain-related hospital encounters. RESULTS: Most patients with cancer (n = 34,675, 56%) received multiple opioids (average 2.8 ± 1.6/patient). Hydrocodone was most commonly prescribed (62%), followed by tramadol, oxycodone, and codeine. In the CYP2D6 genotyped cohort (n = 105), IM/PMs received a similar number of opioids (3.4 ± 1.4) as NMs (3.3 ± 1.9). However, IM/PMs were significantly more likely to experience pain-related hospital encounters compared with NMs, independent of other variables (odds ratio [OR] = 5.4; 95% confidence interval [CI], 1.2-23.6; p = .03). IM/PMs were also more likely to be treated with later-line opioids that do not require CYP2D6 metabolism, such as morphine and hydromorphone (OR = 3.3; 95% CI, 1.1-9.8; p = .03). CONCLUSION: CYP2D6 genotype may identify patients with cancer at increased risk for inadequate analgesia when treated with typical first-line opioids like codeine, tramadol, or standard-dose hydrocodone. Palliative care considerations are an integral part of optimal oncology care, and these findings justify prospective evaluation of preemptive genotyping as a strategy to improve oncology pain management. IMPLICATIONS FOR PRACTICE: Genomic variation in metabolic enzymes can predispose individuals to inefficacy when receiving opioid pain medications. Patients with intermediate and/or poor CYP2D6 metabolizer status do not adequately convert codeine, tramadol, and hydrocodone into active compounds, with resulting increased risk of inadequate analgesia. This study showed that patients with cancer frequently receive CYP2D6-dependent opioids. However, patients with CYP2D6 intermediate and poor metabolizer status had increased numbers of pain-related hospitalizations and more frequently required the potent non-CYP2D6 opioids morphine and hydromorphone. This may reflect inadequate initial analgesia with the common "first-line" CYP2D6-metabolized opioids. Preemptive genotyping to guide opioid prescribing during cancer care may improve pain-related patient outcomes.

Appraisal and development of evidence-based clinical decision support to enable perioperative pharmacogenomic application.

Variable responses to medications complicates perioperative care. As a potential solution, we evaluated and synthesized pharmacogenomic evidence that may inform anesthesia and pain prescribing to identify clinically actionable drug/gene pairs. Clinical decision-support (CDS) summaries were developed and were evaluated using Appraisal of Guidelines for Research and Evaluation (AGREE) II. We found that 93/180 (51%) of commonly-used perioperative medications had some published pharmacogenomic information, with 18 having actionable evidence: celecoxib/diclofenac/flurbiprofen/ibuprofen/piroxicam/CYP2C9, codeine/oxycodone/tramadol CYP2D6, desflurane/enflurane/halothane/isoflurane/sevoflurane/succinylcholine/RYR1/CACNA1S, diazepam/CYP2C19, phenytoin/CYP2C9, succinylcholine/mivacurium/BCHE, and morphine/OPRM1. Novel CDS summaries were developed for these 18 medications. AGREE II mean ± standard deviation scores were high for Scope and Purpose (95.0 ± 2.8), Rigor of Development (93.2 ± 2.8), Clarity of Presentation (87.3 ± 3.0), and Applicability (86.5 ± 3.7) (maximum score = 100). Overall mean guideline quality score was 6.7 ± 0.2 (maximum score = 7). All summaries were recommended for clinical implementation. A critical mass of pharmacogenomic evidence exists for select medications commonly used in the perioperative setting, warranting prospective examination for clinical utility.

Impact and applicability of pharmacogenomics in rheumatology: an integrated analysis.

OBJECTIVES: Rheumatology medications are often associated with adverse drug reactions (ADRs) or inadequate response (IR). Pharmacogenomics may be a solution, but there is limited knowledge of its potential utility within rheumatology. METHODS: We analysed medication changes and pharmacogenomically actionable prescriptions for all adult rheumatology outpatient encounters at our medical centre between 10/2012-12/2018. Three sources defined pharmacogenomic actionability: FDA labels, Clinical Pharmacogenetics Implementation Consortium guidelines, and our institutionally-deliverable pharmacogenomic clinical decision support (CDS) summaries. A subset of patients (validation cohort) had previously undergone broad, preemptive pharmacogenomic testing within other clinics but results were unavailable within rheumatology. We assessed the occurrence of specific pharmacogenomic ADRs/IRs in this group. RESULTS: From 174,834 prescribing events, 6300/7761 patients (81%) had clinically actionable pharmacogenomic drug prescriptions (i.e. institutional CDS summaries would have been deployable if testing had been done). Using more conservative standards (pharmacogenomically actionable by ≥2 guidance bodies), 4158/7761 (54%) patient prescriptions could have been impacted. The greatest proportions of potentially impacted rheumatologic prescriptions were for tramadol (47%), allopurinol (21%), azathioprine (17%) and celecoxib (8%). Among our validation cohort (94 previously-genotyped patients), 29 (31%) patients had a pharmacogenomic genotype that would have cautioned possible ADRs/IRs for ≥1 medication. Four patients actually suffered ADRs/IRs that would have been predicted by preemptive genotyping. CONCLUSIONS: Pharmacogenomic genotyping could inform prescribing for the majority of rheumatology patients and may prevent a subset of ADRs/IRs. These findings justify prospective evaluation of pharmacogenomic testing including assessment of cost-effectiveness in selected rheumatology populations to further understand impact on therapy-related toxicities and treatment outcomes.

Patient insights on features of an effective pharmacogenomics patient portal.

OBJECTIVES: We built a novel mock pharmacogenomics web portal to deliver pharmacogenomic information and results to patients. Utilizing a patient focus group, we then sought to understand patient insights on desired features of an effective pharmacogenomics patient portal. METHODS: The mock YourPGx Portal delivered four sample pharmacogenomic results (omeprazole, simvastatin, clopidogrel, and codeine). Patients from our existing institutional, prospective pharmacogenomics implementation study were recruited to pilot the mock portal and then asked to participate in a focus group discussion led by two facilitators. All patients had been previously genotyped, but none had been directly provided access to their own genotyping results and none had previously used the YourPGx portal. The focus group discussion explored nine domains: (1) factors influencing drug response, (2) concerns about drug effects, (3) understanding of genomics and pharmacogenomics, (4) reasons to undergo pharmacogenomic testing, (5) sources of pharmacogenomic information for patient education, (6) attributes of pharmacogenomic sources of information, (7) considerations about privacy and personal pharmacogenomic information, (8) sharing of pharmacogenomic information, and (9) features of an effective patient portal. RESULTS: The median age of patients (n = 10) was 65.5 years old (range 38-72), 70% female, 50% Caucasian/30% Black, and 60% held a bachelor/advanced degree. When asked about resources for seeking pharmacogenomic information, patients preferred consulting their providers first, followed by self-education, then using information provided by university research organizations. A theme emerged regarding attributes of these sources, namely a desire for understandability and trust. Patients said that the effectiveness of a pharmacogenomics patient portal is improved with use of symbolisms/graphics and clear and concise content. Effective use of colors, quantifying information, consistency, and use of layperson's language were additional important facets. Patients communicated the appeal of secured phone/app-enabled access and said that they would desire linking to their electronic medical records to allow sharing of information with different members of their healthcare team. CONCLUSIONS: Patients named providers as their primary source of pharmacogenomic information, but a pharmacogenomics patient portal that is carefully constructed to incorporate desired features may be a favorable tool to effectively deliver pharmacogenomic information and results to patients.

Pharmacogenomic genotypes define genetic ancestry in patients and enable population-specific genomic implementation.

The importance of genetic ancestry characterization is increasing in genomic implementation efforts, and clinical pharmacogenomic guidelines are being published that include population-specific recommendations. Our aim was to test the ability of focused clinical pharmacogenomic SNP panels to estimate individual genetic ancestry (IGA) and implement population-specific pharmacogenomic clinical decision-support (CDS) tools. Principle components and STRUCTURE were utilized to assess differences in genetic composition and estimate IGA among 1572 individuals from 1000 Genomes, two independent cohorts of Caucasians and African Americans (AAs), plus a real-world validation population of patients undergoing pharmacogenomic genotyping. We found that clinical pharmacogenomic SNP panels accurately estimate IGA compared to genome-wide genotyping and identify AAs with ≥70 African ancestry (sensitivity >82%, specificity >80%, PPV >95%, NPV >47%). We also validated a new AA-specific warfarin dosing algorithm for patients with ≥70% African ancestry and implemented it at our institution as a novel CDS tool. Consideration of IGA to develop an institutional CDS tool was accomplished to enable population-specific pharmacogenomic guidance at the point-of-care. These capabilities were immediately applied for guidance of warfarin dosing in AAs versus Caucasians, but also provide a real-world model that can be extended to other populations and drugs as actionable genomic evidence accumulates.

Analysis of comprehensive pharmacogenomic profiling to impact in-hospital prescribing.

INTRODUCTION: In-hospital adverse medication events result in increased morbidity and mortality. Many implicated drugs carry pharmacogenomic information. We hypothesized that comprehensive pre-emptive pharmacogenomic profiling could have high relevance for in-hospital prescribing. PATIENTS AND METHODS: We retrospectively analyzed the in-hospital medications of a genotyped outpatient cohort admitted at our institution from 2012 to 2015. The endpoints were medication changes (new medications initiated, dose adjustments, or medications discontinued) involving drugs with pharmacogenomic annotations from three sources: Clinical Pharmacogenetics Implementation Consortium guidance, Food and Drug Administration label information, and drugs with clinical decision supports in our institutional pharmacogenomic Genomic Prescribing System. RESULTS: Of 867 genotyped outpatients, 20 were hospitalized (mean: 78.2 years, 65% male). This hospitalized cohort was significantly older (78.2 vs. 61.3 years, P<0.0001) and took more medications (8.9 vs. 5.0 medications, P<0.0001). Out of 159 medication changes made, most (67.9%) were new medications (average: 2.5/hospitalization) with one-third of these having clinically annotated pharmacogenomic information. Half of all hospitalizations involved at least one pharmacogenomic medication. Over half (55%) of the hospitalized cohort was newly prescribed at least one of eight key pharmacogenomic medications, including high-risk drugs such as clopidogrel, codeine, and warfarin. CONCLUSION: Our study suggested that older patients and those with polypharmacy were at increased risk for hospitalizations, where many new prescriptions included frequently used pharmacogenomic drugs. Targeting this group for pre-emptive genotyping would facilitate the delivery of highly relevant information to inform inpatient prescribing.

Assessment of provider-perceived barriers to clinical use of pharmacogenomics during participation in an institutional implementation study.

OBJECTIVE: The objective of this study was to study provider attitudes of and perceived barriers to the clinical use of pharmacogenomics before and during participation in an implementation program. PARTICIPANTS AND METHODS: From 2012 to 2017, providers were recruited. After completing semistructured interviews (SSIs) about pharmacogenomics, providers received training on and access to a clinical decision support tool housing patient-specific pharmacogenomic results. Thematic analysis of SSI was conducted (inter-rater reliability κ≥0.75). Providers also completed surveys before and during study participation, and provider-perceived barriers to pharmacogenomic implementation were analyzed. RESULTS: Seven themes emerged from the SSI (listed from most frequent to least): decision-making, concerns with pharmacogenomic adoption, outcome expectancy, provider knowledge of pharmacogenomics, patient attitudes, individualized treatment, and provider interest in pharmacogenomics. Although there was prestudy enthusiasm among all providers, concerns with clinical utility, time, results accession, and knowledge of pharmacogenomics were frequently stated at baseline. Despite this, adoption of pharmacogenomics was robust, as patient-specific results were accessed at 64% of visits, and medication changes were influenced by provided pharmacogenomic information 42% of the time. Providers reported they had enough time to evaluate the information and the results were easily understood on 74 and 98% of surveys, respectively. Nevertheless, providers consistently felt there was insufficient pharmacogenomic information for most drugs they prescribed and clear guidelines for using pharmacogenomic information were lacking. CONCLUSION: Despite initial concerns about adequate time and knowledge for adoption, providers frequently utilized pharmacogenomic results. Provider-perceived barriers to wider use included lack of clear guidelines and evidence for most drugs, highlighting important considerations for the field of pharmacogenomics.

Patient-provider communications about pharmacogenomic results increase patient recall of medication changes.

Effective doctor-patient communication is critical for disease management, especially when considering genetic information. We studied patient-provider communications after implementing a point-of-care pharmacogenomic results delivery system to understand whether pharmacogenomic results are discussed and whether medication recall is impacted. Outpatients undergoing preemptive pharmacogenomic testing (cases), non-genotyped controls, and study providers were surveyed from October 2012-May 2017. Patient responses were compared between visits where pharmacogenomic results guided prescribing versus visits where pharmacogenomics did not guide prescribing. Provider knowledge of pharmacogenomics, before and during study participation, was also analyzed. Both providers and case patients frequently reported discussions of genetic results after visits where pharmacogenomic information guided prescribing. Importantly, medication changes from visits where pharmacogenomics influenced prescribing were more often recalled than non-pharmacogenomic guided medication changes (OR = 3.3 [1.6-6.7], p = 0.001). Case patients who had separate visits where pharmacogenomics did and did not, respectively, influence prescribing more often remembered medication changes from visits where genomic-based guidance was used (OR = 3.4 [1.2-9.3], p = 0.02). Providers also displayed dramatic increases in personal genomic understanding through program participation (94% felt at least somewhat informed about pharmacogenomics post-participation, compared to 61% at baseline, p = 0.04). Using genomic information during prescribing increases patient-provider communications, patient medication recall, and provider understanding of genomics, important ancillary benefits to clinical use of pharmacogenomics.

Analyzing the clinical actionability of germline pharmacogenomic findings in oncology.

BACKGROUND: Germline and tumor pharmacogenomics impact drug responses, but germline markers less commonly guide oncology prescribing. The authors hypothesized that a critical number of clinically actionable germline pharmacogenomic associations exist, representing clinical implementation opportunities. METHODS: In total, 125 oncology drugs were analyzed for positive germline pharmacogenomic associations in journals with impact factors ≥5. Studies were assessed for design and genotyping quality, clinically relevant outcomes, statistical rigor, and evidence of drug-gene effects. Associations from studies of high methodologic quality were deemed potentially clinically actionable, and translational summaries were written as point-of-care clinical decision support (CDS) tools and formally evaluated using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument. RESULTS: The authors identified germline pharmacogenomic results for 56 of 125 oncology drugs (45%) across 173 publications. Actionable associations were detected for 12 drugs, including 6 that had germline pharmacogenomic information within US Food and Drug Administration labels or published guidelines (capecitabine/fluorouracil/dihydropyrimidine dehydrogenase [DPYD], irinotecan/uridine diphosphate glucuronosyltransferase family 1 member A1 [UGT1A1], mercaptopurine/thioguanine/thiopurine S-methyltransferase [TPMT], tamoxifen/cytochrome P450 [CYP] family 2 subfamily D member 6 [CYP2D6]), and 6 others were novel (asparaginase/nuclear factor of activated T-cells 2 [NFATC2]/human leukocyte antigen D-related ß1 [HLA-DRB1], cisplatin/acylphosphatase 2 [ACYP2], doxorubicin/adenosine triphosphate-binding cassette subfamily C member 2/Rac family small guanosine triphosphatase 2/neutrophil cytosolic factor 4 [ABCC2/RAC2/NCF4], lapatinib/human leukocyte antigen DQ α1 [HLA-DQA1], sunitinib/cytochrome P450 family 3 subfamily A member 5 [CYP3A5], vincristine/centrosomal protein 72 [CEP72]). By using AGREE II, the developed CDS summaries had high mean ± standard deviation scores (maximum score, 100) for scope and purpose (92.7 ± 5.1) and rigour of development (87.6 ± 7.4) and moderate yet robust scores for clarity of presentation (58.6 ± 25.1) and applicability (55.9 ± 24.6). The overall mean guideline quality score was 5.2 ± 1.0 (maximum score, 7). Germline pharmacogenomic CDS summaries for these 12 drugs were recommended for implementation. CONCLUSIONS: Several oncology drugs have actionable germline pharmacogenomic information, justifying their delivery through institutional pharmacogenomic implementations to determine clinical utility. Cancer 2018;124:3052-65. © 2018 American Cancer Society.

Simplifying the use of pharmacogenomics in clinical practice: Building the genomic prescribing system.

BACKGROUND: A barrier to the use of genomic information during prescribing is the limited number of software solutions that combine a user-friendly interface with complex medical data. We built and designed an online, secure, electronic custom interface termed the Genomic Prescribing System (GPS). METHODS: Actionable pharmacogenomic (PGx) information was reviewed, collected, and stored in the back-end of GPS to enable creation of customized drug- and variant-specific clinical decision support (CDS) summaries. The database architecture utilized the star schema to store information. Patient raw genomic data underwent transformation via custom-designed algorithms to enable gene and phenotype-level associations. Multiple external data sets (PubMed, The Systematized Nomenclature of Medicine (SNOMED), National Drug File - Reference Terminology (ND-FRT), and a publically-available PGx knowledgebase) were integrated to facilitate the delivery of patient, drug, disease, and genomic information. Institutional security infrastructure was leveraged to securely store patient genomic and clinical data on a HIPAA-compliant server farm. RESULTS: As of May 17, 2016, the GPS back-end housed 257 CDS encompassing 112 genetic variants, 42 genes, and 46 PGx-actionable drugs. The GPS user interface presented patient-specific CDS alongside a recognizable traffic light symbol (green/yellow/red), denoting PGx risk for each genomic result. The number of traffic lights per visit increased with the corresponding increase in the number of available PGx-annotated drugs over time. An integrated drug and disease search functionality, links to primary literature sources, and potential alternative PGx drugs were indicated. The system, which was initially used as stand-alone CDS software within our clinical environment, was then integrated with the institutional electronic medical record for enhanced usability. There have been nearly 2000 logins in 43months since inception, with usage exceeding 56 logins per month and system up-times of 99.99%. For all patient-provider visits encompassing >3years of implementation, unique alert click-through rates corresponded to genomic risk: red lights clicked 100%, yellow lights 79%, green lights 43%. CONCLUSIONS: Successful deployment of GPS by combining complex data and recognizable iconography led to a tool that enabled point-of-care genomic delivery with high usability. Continued scalability and incorporation of additional clinical elements to be considered alongside PGx information could expand future impact.

Adoption of a clinical pharmacogenomics implementation program during outpatient care--initial results of the University of Chicago "1,200 Patients Project".

Pharmacogenomic testing is viewed as an integral part of precision medicine. To achieve this, we originated The 1,200 Patients Project which offers broad, preemptive pharmacogenomic testing to patients at our institution. We analyzed enrollment, genotype, and encounter-level data from the first year of implementation to assess utility of providing pharmacogenomic results. Results were delivered via a genomic prescribing system (GPS) in the form of traffic lights: green (favorable), yellow (caution), and red (high risk). Additional supporting information was provided as a virtual pharmacogenomic consult, including citation to relevant publications. Currently, 812 patients have participated, representing 90% of those approached; 608 have been successfully genotyped across a custom array. A total of 268 clinic encounters have occurred at which results were accessible via the GPS. At 86% of visits, physicians accessed the GPS, receiving 367 result signals for medications patients were taking: 57% green lights, 41% yellow lights, and 1.4% red lights. Physician click frequencies to obtain clinical details about alerts varied according to color severity (100% of red were clicked, 72% yellow, 20% green). For 85% of visits, clinical pharmacogenomic information was available for at least one drug the patient was taking, suggesting relevance of the delivered information. We successfully implemented an individualized health care model of preemptive pharmacogenomic testing, delivering results along with pharmacogenomic decision support. Patient interest was robust, physician adoption of information was high, and results were routinely utilized. Ongoing examination of a larger number of clinic encounters and inclusion of more physicians and patients is warranted.

Creation of a pharmacogenomics patient portal complementary to an existing institutional provider-facing clinical decision support system.

BACKGROUND: Applied pharmacogenomics presents opportunities for improving patient care through precision medicine, particularly when paired with appropriate clinical decision support (CDS). However, a lack of patient resources for understanding pharmacogenomic test results may hinder shared decision-making and patient confidence in treatment. We sought to create a patient pharmacogenomics education and results delivery platform complementary to a CDS system to facilitate further research on the relevance of patient education to pharmacogenomics. METHODS: We conceptualized a model that extended the data access layer of an existing institutional CDS tool to allow for the pairing of decision supports offered to providers with patient-oriented summaries at the same level of phenotypic specificity. We built a two-part system consisting of a secure portal for patient use and an administrative dashboard for patient summary creation. The system was built in an ASP.NET and AngularJS architecture, and all data was housed in a HIPAA-compliant data center, with PHI secure in transit and at rest. RESULTS: The YourPGx Patient Portal was deployed on the institutional network in June 2019. Fifty-eight unique patient portal summaries have been written so far, which can provide over 4500 results modules to the pilot population of 544 patients. Patient behavior on the portal is being logged for further research. CONCLUSIONS: To our knowledge, this is the first automated system designed and deployed to provide detailed, personalized patient pharmacogenomics education complementary to a clinical decision support system. Future work will expand upon this system to allow for telemedicine and patient notification of new or updated results.

Underrepresented patient views and perceptions of personalized medication treatment through pharmacogenomics.

Within an institutional pharmacogenomics implementation program, we surveyed 463 outpatients completing preemptive pharmacogenomic testing whose genetic results were available to providers for guiding medication treatment. We compared views and experiences from self-reported White and Black patients, including education level as a covariate across analyses. Black patients were less confident about whether their providers made personalized treatment decisions, and overwhelmingly wanted a greater role for their genetic information in clinical care. Both groups similarly reported that providers asked their opinions regarding medication changes, but White patients were more likely (59% vs. 49%, P = 0.005) to discuss the impact of personal/genetic makeup on medication response with providers, and Black patients reported initiating such discussions much less frequently (4% vs. 15%, P = 0.037). Opportunities exist for enhanced communication with underrepresented patients around personalized care. Tailored communication strategies and development of support tools employed in diverse healthcare settings may facilitate pharmacogenomically guided medication treatment that equitably benefits minority patient populations.

Validation of a Large Custom-Designed Pharmacogenomics Panel on an Array Genotyping Platform.

BACKGROUND: Pharmacogenomics has the potential to improve patient outcomes through predicting drug response. We designed and evaluated the analytical performance of a custom OpenArray® pharmacogenomics panel targeting 478 single-nucleotide variants (SNVs). METHODS: Forty Coriell Institute cell line (CCL) DNA samples and DNA isolated from 28 whole-blood samples were used for accuracy evaluation. Genotyping calls were compared to at least 1 reference method: next-generation sequencing, Sequenom MassARRAY®, or Sanger sequencing. For precision evaluation, 23 CCL samples were analyzed 3 times and reproducibility of the assays was assessed. For sensitivity evaluation, 6 CCL samples and 5 whole-blood DNA samples were analyzed at DNA concentrations of 10 ng/µL and 50 ng/µL, and their reproducibility and genotyping call rates were compared. RESULTS: For 443 variants, all samples assayed had concordant calls with at least 1 reference genotype and also demonstrated reproducibility. However, 6 of these 443 variants showed an unsatisfactory performance, such as low PCR amplification or insufficient separation of genotypes in scatter plots. Call rates were comparable between 50 ng/µL DNA (99.6%) and 10 ng/µL (99.2%). Use of 10 ng/µL DNA resulted in an incorrect call for a single sample for a single variant. Thus, as recommended by the manufacturer, 50 ng/µL is the preferred concentration for patient genotyping. CONCLUSIONS: We evaluated a custom-designed pharmacogenomics panel and found that it reliably interrogated 437 variants. Clinically actionable results from selected variants on this panel are currently used in clinical studies employing pharmacogenomics for clinical decision-making.

Applicability of Pharmacogenomically Guided Medication Treatment during Hospitalization of At-Risk Minority Patients.

Known disparities exist in the availability of pharmacogenomic information for minority populations, amplifying uncertainty around clinical utility for these groups. We conducted a multi-site inpatient pharmacogenomic implementation program among self-identified African-Americans (AA; n = 135) with numerous rehospitalizations (n = 341) from 2017 to 2020 (NIH-funded ACCOuNT project/clinicaltrials.gov#NCT03225820). We evaluated the point-of-care availability of patient pharmacogenomic results to healthcare providers via an electronic clinical decision support tool. Among newly added medications during hospitalizations and at discharge, we examined the most frequently utilized medications with associated pharmacogenomic results. The population was predominantly female (61%) with a mean age of 53 years (range 19-86). On average, six medications were newly prescribed during each individual hospital admission. For 48% of all hospitalizations, clinical pharmacogenomic information was applicable to at least one newly prescribed medication. Most results indicated genomic favorability, although nearly 29% of newly prescribed medications indicated increased genomic caution (increase in toxicity risk/suboptimal response). More than one of every five medications prescribed to AA patients at hospital discharge were associated with cautionary pharmacogenomic results (most commonly pantoprazole/suboptimal antacid effect). Notably, high-risk pharmacogenomic results (genomic contraindication) were exceedingly rare. We conclude that the applicability of pharmacogenomic information during hospitalizations for vulnerable populations at-risk for experiencing health disparities is substantial and warrants continued prospective investigation.

COVIDOSE: A Phase II Clinical Trial of Low-Dose Tocilizumab in the Treatment of Noncritical COVID-19 Pneumonia.

Interleukin-6 (IL-6)-mediated hyperinflammation may contribute to the mortality of coronavirus disease 2019 (COVID-19). The IL-6 receptor-blocking monoclonal antibody tocilizumab has been repurposed for COVID-19, but prospective trials and dose-finding studies in COVID-19 have not yet fully reported. We conducted a single-arm phase II trial of low-dose tocilizumab in nonintubated hospitalized adult patients with COVID-19, radiographic pulmonary infiltrate, fever, and C-reactive protein (CRP) ≥ 40 mg/L. We hypothesized that doses significantly lower than the emerging standards of 400 mg or 8 mg/kg would resolve clinical and laboratory indicators of hyperinflammation. A dose range from 40 to 200 mg was evaluated, with allowance for one repeat dose at 24 to 48 hours. The primary objective was to assess the relationship of dose to fever resolution and CRP response. Thirty-two patients received low-dose tocilizumab, with the majority experiencing fever resolution (75%) and CRP decline consistent with IL-6 pathway abrogation (86%) in the 24-48 hours following drug administration. There was no evidence of a relationship between dose and fever resolution or CRP decline over the dose range of 40-200 mg. Within the 28-day follow-up, 5 (16%) patients died. For patients who recovered, median time to clinical recovery was 3 days (interquartile range, 2-5). Clinically presumed and/or cultured bacterial superinfections were reported in 5 (16%) patients. Low-dose tocilizumab was associated with rapid improvement in clinical and laboratory measures of hyperinflammation in hospitalized patients with COVID-19. Results of this trial provide rationale for a randomized, controlled trial of low-dose tocilizumab in COVID-19.