Oncology pharmacy practice in the United States: Results of a comprehensive, nationwide survey.

Introduction: This study was designed to describe the landscape of oncology pharmacy practice at patient facing institutional healthcare organizations throughout the United States. Methods: The Hematology/Oncology Pharmacy Association (HOPA) Practice Outcomes and Professional Benchmarking Committee conducted a multi-organization, voluntary survey of HOPA members between March 2021 and January 2022. Four overarching domains were targeted: institutional description, job function, staffing, and training/certification. Data were evaluated using descriptive statistics. Results: A total of 68 responses were analyzed including 59% and 41% who self-identified their organization as academic and community centers, respectively. The median number of infusion chairs and annual infusion visits were 49 (interquartile range (IQR): 32-92) and 23,500 (IQR: 8300-300,000), respectively. Pharmacy departments reported to a business leader, physician leader, and nursing leader 57%, 24%, and 10% of the time, respectively. The median oncology pharmacy full-time equivalents was 16 (IQR: 5-60). At academic centers, 50% (IQR: 26-60) of inpatient and 30% (IQR: 21-38) of ambulatory pharmacist FTEs were dedicated to clinical activities. At community centers, 45% (IQR: 26-65) of inpatient and 50% (IQR: 42-58) of ambulatory pharmacist FTEs were dedicated to clinical activities. As many as 18% and 65% of organizations required or encouraged certification for oncology pharmacists, respectively. The median number of Board-Certified Oncology Pharmacists was 4 (IQR: 2-15). Conclusion: As the number of patients with cancer rises, the oncology workforce must grow to support this expanding population. These results describe the practice landscape of oncology pharmacy at US healthcare institutions to serve as a foundation for future research evaluating metrics and benchmarks.

Pharmacist value-added to neuro-oncology subspecialty clinics: A pilot study uncovers opportunities for best practices and optimal time utilization.

PURPOSE: To evaluate neuro-oncology clinician time utilization for medication management and identify a cost beneficial role for integration of a dedicated pharmacy specialists. METHODS: A pharmacist was temporarily integrated into a neuro-oncology clinic for a 30-day period to evaluate the clinical practice and perform a 14-day clinical chart evaluation and patient interactions as part of a single institutional exploratory analysis. The pharmacist completed screenings for drug-drug interactions, new therapies, medication reconciliation, and advanced interventions as part of a collaborative practice agreement for pharmacist autonomy. Pharmacist time spent was calculated and documented within the patient encounters to support physician decision-making. A comparative estimate of pharmacist versus physician time utilization and cost for each was completed to derive a savings analysis for integration of a dedicated clinic pharmacist. RESULT: During the 14-day clinical assessment, the pharmacist completed 147 encounters with 338 interventions. Of the encounters, 90% (n = 132) were higher complexity requiring plan modification, and approximately 48% (n = 162) of all interventions required ≥10 minutes of the pharmacist's time. Physician non-patient-facing time devoted to medication tasks was 5-hours weekly (0.125 FTE, full time equivalents), an estimated direct salary cost of $937/week ($45,000 yearly). Hire of a part-time pharmacist at 0.50 FTE would cover the clinical need with supported documentation and medication monitoring at a cost of $45,000/year. CONCLUSION: Defining the roles for dedicated neuro-oncology clinic pharmacists allows for cost-savings through re-allocation of physician time and improves subspecialty clinic operations as well as patient care.

Clozapine drug-induced pancreatitis of intermediate latency of onset confirmed by de-challenge and re-challenge
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Definitive causality for medication-induced illnesses is difficult to determine, as often there are other causes for the condition. Additionally, for disease management there are often alternative treatment paths, and it is therefore clinically unnecessary to re-challenge with the suspected drug causing an adverse reaction; however, that was not the case in this clinical situation. Providers augmented treatment for this patient, but returned to the only therapy that controlled her condition, clozapine, as there appeared to be limited suitable alternatives. As outlined in this medical case, because the patient clinically responded only to clozapine, this forced providers to order multiple de-challenges and re-challenges resulting in confirmed drug-induced pancreatitis. Through courses of re-challenge, they were forced to find an effective dose and timing to maximize options for care using the drug despite inducing pancreatitis. At the time of this submission, providers had resumed a tolerated lower dose of clozapine without inducing pancreatitis. This case adds to the literature of drug-induced pancreatitis confirmation due to clozapine therapy being de-challenge and re-challenge.
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Olaratumab: A Novel Platelet-Derived Growth Factor Receptor α-Inhibitor for Advanced Soft Tissue Sarcoma.

OBJECTIVE: To review and summarize data on olaratumab, which was approved by the US Food and Drug Administration (FDA) in October 2016, in combination with doxorubicin, for the treatment of advanced soft tissue sarcoma. DATA SOURCES: A literature search using PubMed was conducted using the search terms olaratumab, IMC-3G3, and advanced soft tissue sarcoma from January 2005 to June 2017. STUDY SELECTION AND DATA EXTRACTION: The literature search was confined to human studies published in English. Trials of olaratumab for advanced soft tissue sarcomas were prioritized. DATA SYNTHESIS: Olaratumab is a human antiplatelet-derived growth factor receptor α monoclonal antibody. Its accelerated FDA approval was based on a phase II randomized trial of olaratumab plus doxorubicin (n = 66) versus doxorubicin monotherapy (n = 67) in patients with advanced soft tissue sarcoma. Olaratumab 15 mg/kg was administered intravenously (IV) on days 1 and 8 in combination with doxorubicin 75 mg/m2 IV on day 1 every 21 days for a total of 8 cycles compared to doxorubicin 75 mg/m2 IV monotherapy. The response rate was 18.2% with combination therapy versus 11.9% with monotherapy and median progression-free survival of 6.6 and 4.1 months, respectively. Additionally, overall survival was increased by 11.8 months in the olaratumab arm (26.5 months vs 14.7 months). Clinically relevant adverse effects in the olaratumab + doxorubicin arm included neutropenia (58%), mucositis (53%), nausea (73%), vomiting (45%), and diarrhea (34%). CONCLUSION: Olaratumab, in combination with doxorubicin, represents a novel treatment strategy for advanced soft tissue sarcoma and provides a significant survival advantage for this rare disease state with limited treatment options.

Impact of a pharmacist-led telehealth oral chemotherapy clinic.

PURPOSE: Oral oncolytics come with significant concerns of noncompliance due to complex regimens, adverse effects, and high overall costs. The Geisinger Oral Chemotherapy Clinic is a fully telephone-based medication therapy disease management (MTDM) program designed to integrate pharmacists as advanced practitioners in hematology/oncology clinics for comanagement of oral chemotherapy. SUMMARY: To date, Geisinger has 11 oncology clinics and 3 full-time pharmacists designated to the management of oral chemotherapy. Pharmacists receive referrals for comanagement of patients starting oral oncolytics. Under a collaborative practice agreement, they can order laboratory tests as well as supportive care medications and refills. Pharmacists review planned therapies, perform medication reconciliations, and provide medication counseling. Once treatment has been initiated, pharmacists contact patients for laboratory and toxicity assessments. The clinic incorporates the use of customized smart data elements within the electronic medical record to collect data regarding pharmacist interventions and time allocations in the clinic. As of March 31, 2021, the clinic was actively following approximately 1,100 patients, resulting in an average of 80 to 90 encounters per day for new referrals, chemotherapy education, and laboratory and toxicity assessments. Approximately 2,113 patients were followed from December 1, 2019, to March 31, 2021, with 46,929 interventions documented. CONCLUSION: By obtaining provider buy-in for pharmacy services, acquiring enough personnel resources to meet the needs of the growing patient population and respective therapies, and proper utilization of technology, the program has thrived, allowing for increased provider and patient satisfaction. Future goals include expanding collection of pharmacist intervention metrics and analysis of patient perceptions of services provided by the clinic.

A Bioinformatics Practicum to Develop Student Understanding of Immunological Rejection of Protein Drugs.

Objectives. To design and implement a bioinformatics exercise that applies immunological principles to predicting rejection of protein drugs based upon patient genotype. Design. Doctor of pharmacy (PharmD) students used the Immune Epitope Database, a freely available bioinformatics tool. Over a 2-week laboratory, students interrogated whether a protein drug would be predicted to induce an immune response based upon patient genotype. Results were presented at the last laboratory session, and students completed reports discussing their findings. Assessment. Pre-lab quizzes and a final report were graded. Students answered questionnaires assessing perceived learning gains. To determine the impact on student understanding of immunity against protein drugs, the quality of student data analysis and comparisons to class data were graded. Independent measures of student learning demonstrated that students developed a greater understanding of how patient genotype could contribute to treatment failure with protein drugs. Conclusions. This study indicates that questions related to clinical immunology can be posed using bioinformatics tools.

Predicting Hemagglutinin MHC-II Ligand Analogues in Anti-TNFα Biologics: Implications for Immunogenicity of Pharmaceutical Proteins.

The purpose of this study was to evaluate the extent of overlapping immunogenic peptides between three pharmaceutical biologics and influenza viruses. Clinical studies have shown that subsets of patients with rheumatoid arthritis (RA) develop anti-drug antibodies towards anti-TNFα biologics. We postulate that common infectious pathogens, including influenza viruses, may sensitize RA patients toward recombinant proteins. We hypothesize that embedded within infliximab (IFX), adalimumab (ADA), and etanercept (ETN) are ligands of class II major histocompatibility complex (MHC-II) that mimic T cell epitopes derived from influenza hemagglutinin (HA). The rationale is that repeated administration of the biologics would reactivate HA-primed CD4 T cells, stimulating B cells to produce cross-reactive antibodies. Custom scripts were constructed using MATLAB to compare MHC-II ligands of HA and the biologics; all ligands were predicted using tools in Immune Epitope Database and Resources (IEDB). We analyzed three HLA-DR1 alleles (0101, 0401 and 1001) that are prominent in RA patients, and two alleles (0103 and 1502) that are not associated with RA. The results indicate that 0401 would present more analogues of HA ligands in the three anti-TNFα biologics compared to the other alleles. The approach led to identification of potential ligands in IFX and ADA that shares sequence homology with a known HA-specific CD4 T cell epitope. We also discovered a peptide in the complementarity-determining region 3 (CDR-3) of ADA that encompasses both a potential CD4 T cell epitope and a known B cell epitope in HA. The results may help generate new hypotheses for interrogating patient variability of immunogenicity of the anti-TNFα drugs. The approach would aid development of new recombinant biologics by identifying analogues of CD4 T cell epitopes of common pathogens at the preclinical stage.