Empowering personalized pharmacogenomics with generative AI solutions.

OBJECTIVE: This study evaluates an AI assistant developed using OpenAI's GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics and to enhance patient care with equitable access. MATERIALS AND METHODS: The AI assistant employs retrieval-augmented generation (RAG), which combines retrieval and generative techniques, by harnessing a knowledge base (KB) that comprises data from the Clinical Pharmacogenetics Implementation Consortium (CPIC). It uses context-aware GPT-4 to generate tailored responses to user queries from this KB, further refined through prompt engineering and guardrails. RESULTS: Evaluated against a specialized PGx question catalog, the AI assistant showed high efficacy in addressing user queries. Compared with OpenAI's ChatGPT 3.5, it demonstrated better performance, especially in provider-specific queries requiring specialized data and citations. Key areas for improvement include enhancing accuracy, relevancy, and representative language in responses. DISCUSSION: The integration of context-aware GPT-4 with RAG significantly enhanced the AI assistant's utility. RAG's ability to incorporate domain-specific CPIC data, including recent literature, proved beneficial. Challenges persist, such as the need for specialized genetic/PGx models to improve accuracy and relevancy and addressing ethical, regulatory, and safety concerns. CONCLUSION: This study underscores generative AI's potential for transforming healthcare provider support and patient accessibility to complex pharmacogenomic information. While careful implementation of large language models like GPT-4 is necessary, it is clear that they can substantially improve understanding of pharmacogenomic data. With further development, these tools could augment healthcare expertise, provider productivity, and the delivery of equitable, patient-centered healthcare services.

Pharmacogenomics for Prader-Willi syndrome: caregiver interest and planned utilization.

Aim: The study aim was to determine caregiver interest and planned utilization of pharmacogenomic (PGx) results for their child with Prader-Willi syndrome. Methods: Caregivers consented to PGx testing for their child and completed a survey before receiving results. Results: Of all caregivers (n = 48), 93.8% were highly interested in their child's upcoming PGx results. Most (97.9%) planned to share results with their child's medical providers. However, only 47.9% of caregivers were confident providers would utilize the PGx results. Conclusion: Caregivers are interested in utilizing PGx but are uncertain providers will use these results in their child's care. More information about provider comfort with PGx utilization is needed to understand how PGx education would benefit providers and ultimately patients with PGx results.

Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database.

BACKGROUND: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications. AIM: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a large nationally representative population using an insurance claims database. METHODS: Our retrospective cohort study included adults (18+ years) from the IQVIA PharMetrics® Plus for Academics claims database with incident fills of 72 Clinical Pharmacogenetics Implementation Consortium level A, A/B, or B medications from January 2012 through September 2018. Patient-level outcomes included the proportion of days covered (PDC), number of fills, and average days supplied per fill over a 12-month period. RESULTS: Over 1 million fills of pharmacogenetic medications were identified for 605,355 unique patients. The mean PDC for all medications was 0.21 (SD 0.3), suggesting patients were exposed 21% (77 days) of the year. Medications with the highest PDC (0.55-0.89) included ivacaftor, tamoxifen, clopidogrel, HIV medications, transplant medications, and statins; with the exception of statins, these medications were initiated by fewer patients. Pharmacogenomic medications were filled an average of 2.8 times (SD 3.0, range 1-81) during the year following the medication's initiation, and the average days supplied for each fill was 22.3 days (SD 22.4, range 1-180 days). CONCLUSION: Patient characteristics associated with more medication exposure were male sex, older age, and comorbid chronic conditions. Prescription fill data provide patient-level exposure metrics that can further our understanding of pharmacogenomic medication utilization and help inform opportunities for pharmacogenomic testing.

An EMR-Based Approach to Determine Frequency, Prescribing Pattern, and Characteristics of Patients Receiving Drugs with Pharmacogenomic Guidelines.

(1) Background: This retrospective analysis utilizing electronic medical record (EMR) data from a tertiary integrated health system sought to identify patients and prescribers who would benefit from pharmacogenomic (PGx) testing based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. (2) Methods: EMR data from a clinical research data warehouse were analyzed from 845,518 patients that had an encounter between 2015 and 2019 at an academic medical center. Data were collected for 42 commercially available drugs with 52 evidence-based PGx guidelines from CPIC. Provider data were obtained through the EMR linked by specialty via national provider identification (NPI) number. (3) Results: A total of 845,518 patients had an encounter in the extraction period with 590,526 medication orders processed. A total of 335,849 (56.9%) patients had medication orders represented by CPIC drugs prescribed by 2803 providers, representing 239 distinct medications. (4) Conclusions: The results from this study show that over half of patients were prescribed a CPIC actionable medication from a variety of prescriber specialties. Understanding the magnitude of patients that may benefit from PGx testing, will enable the development of preemptive testing processes, physician support strategies, and pharmacist workflows to optimize outcomes should a PGx service be implemented.

Therapeutic drug monitoring in psychiatry.

In medicine, there are two main methods of improving the healthcare provided: perfecting (optimizing) the existing ones and seeking new treatment procedures. Despite of tremendous development in the central nervous system research, current treatment of severe mental illnesses, such as schizophrenia and depressive disorder, is suboptimal. Nowadays, optimization of treatment in psychiatry includes therapeutic drug monitoring (TDM) and pharmacogenomic testing, which examines genetic variation involved in medication metabolism and drug action. The TDM enables to determine drug concentrations in blood and adjust the dose accordingly if clinical effects correlate better with drug blood levels than drug doses. The first international guidelines for TDM in neuropsychopharmacology were published in 2004 and regularly updated. The recent update provides therapeutic reference ranges for a majority of commonly prescribed psychiatric medications and gives example of patients regularly treated in clinical practice profiting from TDM (using antipsychotics and changing their smoking habits). TDM in psychiatry is an underused tool, given its ability to optimize treatment, as well as to improve treatment effectiveness.

Attitudes about pharmacogenomic testing vary by healthcare specialty.

Aim: To understand how attitudes toward pharmacogenomic (PGx) testing among healthcare providers varies by specialty. Methods: Providers reported comfort ordering PGx testing and its perceived utility on web-based surveys before and after genetics education. Primary quantitative analyses compared primary care providers (PCPs) to specialty providers at both timepoints. Results: PCPs were more likely than specialty care providers to rate PGx testing as useful at both timepoints. Education increased comfort ordering PGx tests, with larger improvements among PCPs than specialty providers. Over 90% of cardiology and internal medicine providers rated PGx testing as useful at pre- and post-education. Conclusion: PCPs overwhelmingly perceive PGx to be useful, and provider education is particularly effective for improving PCPs' confidence. Education for all specialties will be essential to ensure appropriate integration into routine practice.

A randomized controlled trial of analogue pharmacogenomic testing feedback for psychotropic medications.

Objective: To examine the impact of various presentations of pharmacogenomic testing results using a published, color-coded decision support tool (DST) format as a standard stimulus to list possible medications. Methods: Participants were randomly assigned to groups and asked to decide which psychotropic medication they would prefer if depressed. Three of the groups varied the color-coded category of fluoxetine and received a statement indicating that this was the most prescribed drug for depression. A fourth control condition omitted base rate information. Participants also provided detail about their decision-making processes through a qualitative interview. Results: Comparison of the first three groups indicated that significantly more participants selected medications from the highest category of likely effectiveness when fluoxetine appeared in this list. Comparison of the control group to its relevant analogue suggested no significant differences in selection strategy. Qualitative interview responses indicated participant comfort with genetic testing despite awareness of having very limited understanding of these techniques and their implications. Conclusions: Both DST color-coding and base rates were influential in driving drug selection decisions, despite most participants indicating they did not understand this information. Innovation: Efforts to standardize pharmacogenomic stimuli may lead to advances in methods of studying quantifiable healthcare decisions. Attention to the context for presenting test results may also be a useful source of understanding patient responses, particularly regarding complex tests that are likely to be interpreted heuristically.

Pharmacogenomic testing and prescribing patterns for patients with cancer in a large national precision medicine cohort.

Population databases could help patients with cancer and providers better understand current pharmacogenomic prescribing and testing practices. This retrospective observational study analysed patients with cancer, drugs with pharmacogenomic evidence and related genetic testing in the National Institutes of Health All of Us database. Most patients with cancer (19 633 (88.3%) vs 2590 (11.7%)) received ≥1 drug and 36 (0.2%) received genetic testing, with a significant association between receiving ≥1 drug and age group (p<0.001), but not sex (p=0.612), race (p=0.232) or ethnicity (p=0.971). Drugs with pharmacogenomic evidence-but not genetic testing-were common for patients with cancer, reflecting key gaps preventing precision medicine from becoming standard of care.

Effect of pharmacogenomic testing on pediatric mental health outcome: a 6-month follow-up.

Aim: This retrospective, case-control study evaluated the effect of pharmacogenomic testing (PGT) on the management of pediatrics with anxiety, major depressive disorder (MDD) and attention-deficit/hyperactivity disorder (ADHD). Methods: The authors examined psychiatric diagnoses, medication histories, CYP450 profiles, SLC6A4, HTR2A, COMT and MTHFR. Results: The authors found no difference in clinical improvement between the two groups. However, the number of medication changes was significantly larger after PGT. The treatment response in MDD and anxiety was not different between the groups, while ADHD treatment response was substantially improved in PGT and correlated with COMT status. Conclusion: PGT had some value with ADHD with doubtful benefit for MDD or anxiety disorders. Accordingly, pediatric indications must be weighed against cost, utility and clinician experience. Limitations included sample size and selection bias.

Evaluation methods and application progress of drug cytotoxicity in vitro / 中国基层医药

Drugs have both therapeutic and toxic side effects. How to quickly determine the toxicity of the test substance is very important for drug development. In vitro cytotoxicity testing compensates for the shortcomings of using animal models for toxicity evaluation. Its role in toxicity evaluation is increasingly important. The development of computer technology and in-depth research in proteomics, genomics, and metabolomics provide a method for in vitro cytotoxicity evaluation towards a faster and more accurate direction. This paper reviews the commonly used cells, evaluation indicators, and detection techniques for in vitro cytotoxicity evaluation, in order to provide some reference for related research.

Physicians' Knowledge, Attitude, and Experience of Pharmacogenomic Testing in China.

(1) Background: As prescribers, physicians play a decisive role in applying and promoting pharmacogenomic (PGx) testing in clinical practices. So far, little is known about physicians' perspectives on PGx testing in China. The aim of this study was to assess physicians' knowledge of, attitude towards, and experience of PGx testing in China. (2) Methods: A 39-question online survey was developed. Participants were physicians recruited through two platforms, MEDLINKER and "Dazhuanjia". (3) Results: A total of 450 respondents completed the survey and 366 questionnaires were eligible for analysis based on the inclusion criteria. Among all included physicians, 275 (75.1%) had heard of PGx testing before. More than half rated their knowledge of PGx testing as "Fair" (61.5%) while 20.0% chose "Excellent" or "Good" and 18.6% chose "Poor" or "Terrible". "Guidelines, consensus, and treatment paths for disease diagnosis and treatment" (72.7%) were the most preferred sources of information about PGx testing. Respondents were confident in their personal capacity to conduct PGx, with an average score of 3.30 ± 0.09 (out of 5.00). Most respondents (75.6%) believed that PGx could "help to improve efficacy and reduce the incidence of adverse reactions". Targeted cancer therapy (score 78.95 ± 1.26 out of 100) was considered the field where PGx testing had its highest value. Lack of professionals and knowledge (n = 186, 67.6%), high costs of testing (n = 170, 61.8%), and lack of hospitals to offer PGx testing (n = 166, 60.4%) were identified as the primary obstacles to increasing the uptake of PGx testing in China. Academic conference (n = 213, 72.4%) was considered the most efficient way for physicians to obtain information about PGx testing. (4) Conclusions: Physicians in China have poor knowledge about PGx testing; nonetheless, they generally had confidence in their capacity to order PGx testing and positive attitudes towards the use of PGx testing in routine clinical practices. Future efforts to promote the uptake of PGx testing should focus on foundational education and practical training.

Public Attitudes toward Pharmacogenomic Testing and Establishing a Statewide Pharmacogenomics Database in the State of Minnesota.

The clinical adoption and implementation of pharmacogenomics (PGx) beyond academic medical centers remains slow, restricting the general population from benefitting from this important component of personalized medicine. As an initial step in the statewide initiative of PGx implementation in Minnesota, we engaged community members and assessed attitudes towards PGx testing and acceptability of establishing a secure statewide PGx database for clinical and research use among Minnesota residents. Data was collected from 808 adult attendees at the 2021 Minnesota State Fair through an electronic survey. Eighty-four percent of respondents felt comfortable getting a PGx test for clinical care. Most respondents trusted health professionals (78.2%) and researchers (73.0%) to keep their PGx data private. The majority expressed their support and interest in participating in a statewide PGx database for clinical and research use (64-72%). Higher acceptability of the statewide PGx database was associated with younger age, higher education, higher health literacy, having health insurance, and prior genetic testing. The study sample representing Minnesota residents expressed high acceptability of receiving PGx testing and willingness to participate in PGx data sharing for clinical and research use. Community support and engagement are needed to advance PGx implementation and research on the state scale.

Clinical Pharmacists' Knowledge of and Attitudes toward Pharmacogenomic Testing in China.

(1) Background: Uptake of pharmacogenomic testing in routine clinical practices is currently slow in China. Pharmacists might play an important role in leveraging care through applying pharmacogenomics, therefore, it is important to better understand clinical pharmacists' knowledge of and attitudes toward pharmacogenomic testing, which has not been well-studied. (2) Methods: A self-administered survey was developed based on previous knowledge of pharmacogenomic testing and its uptake in China. Participants were recruited through the Committee of Pharmaceutical Affairs Management under the Chinese Hospital Association. (3) Results: A total of 1005 clinical pharmacists completed the questionnaire, among whom 996 (99.10%) had heard of pharmacogenomic testing before participation. More than half of respondents (60.0%, n = 597) rated their knowledge of pharmacogenomic testing as "average", while 25% rated it "good" or "excellent". "Guidelines, consensus and treatment paths for disease diagnosis and treatment" (78.7%) were the most preferred sources of information about pharmacogenomic testing. Most respondents (77.0%) believed that pharmacogenomics could "help to improve efficacy and reduce the incidence of adverse reactions". Our participants also believed that patients would benefit most from pharmacogenomic testing through better prediction of individual drug responses and thus informed treatment decisions. The top challenge for the uptake of pharmacogenomic testing was its high cost or lack of insurance coverage (76.7%). (4) Conclusions: Most Chinese clinical pharmacists who participated in our study had a positive attitude toward pharmacogenomic testing, while the knowledge of pharmacogenomic testing was generally self-assessed as average.

Fetal pharmacogenomics: A promising addition to complex neonatal care.

OBJECTIVE: Pharmacogenomics (PGx) characterizes genetic variation in medication response. 85-95% of the population carries actionable PGx variants. No prior studies have demonstrated the application and feasibility of PGx in prenatal testing. We assessed parental desire for PGx findings from fetal exome sequencing (ES), evaluated PGx variants, and reviewed implications for medically complex neonates. METHODS: A prospective cohort undergoing ES for nonimmune hydrops fetalis were offered PGx results as a secondary finding. Seven pharmacogenes with Level A evidence, defined by Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, were tested and reported to patients and referring providers. Medication administration records were reviewed. RESULTS: Most participants (36/40, 90%) desired PGx testing. 32/36 (89%) had potentially actionable PGx diplotypes in six genes: CYP2C19 (20/36, 56%), CYP2C9 (16/36, 44%), CYP2D6 (10/36, 28%), SLCO1B1 (13/36, 36%), TPMT (6/36, 17%), UGT1A1 (4/36, 11%). 12/13 (92%) live births had PGx variants. Neonatal chart review indicated that three medications with CPIC Level A evidence were administered to four neonates. None of the patients received a medication that aligned with an actionable pharmacogenetic variant as defined by Level A CPIC guidance. CONCLUSION: Most participants opted to receive PGx results. 89% had actionable variants, consistent with population estimates. Obtaining fetal PGx data is feasible for medically complex neonates. Further studies are needed for broad clinical application of PGx in fetuses with major congenital abnormalities. Our study demonstrates the potential of PGx as useful preemptive clinical information that could be obtained at the time of fetal exome sequencing for other indications. CLINICALTRIALS: gov Registration: NCT03911531.

Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program.

We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system's list of medications for pharmacogenomic testing. The automated method used YouScript's pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug-drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.

Pharmacogenomic testing: perception of clinical utility, enablers and barriers to adoption in Australian hospitals.

BACKGROUND: Despite healthcare professionals (HCP) endorsing the clinical utility of pharmacogenomics testing, use in clinical practice is limited. AIMS: To assess HCP' perceptions of pharmacogenomic testing and identify barriers to implementation. METHODS: HCP involved in prescribing decisions at three hospitals in Sydney, Australia, were invited to participate. The online survey assessed perceptions of pharmacogenomic testing, including: (i) demographic and practice variables; (ii) use, knowledge and confidence; (iii) perceived benefits; (iv) barriers to implementation; and (v) operational and/or system changes and personnel required to implement on site. RESULTS: HCP were predominantly medical practitioners (75/107) and pharmacists (25/107). HCP perceived pharmacogenomic testing was beneficial to identify reasons for drug intolerance (85/95) and risk of side-effects (86/95). Although testing was considered relevant to their practice (79/100), few HCP (23/100) reported past or intended future use (26/100). Few HCP reported confidence in their ability to identify indications for pharmacogenomic testing (14/107), order tests (19/106) and communicate results with patients (16/107). Lack of clinical practice guidelines (62/79) and knowledge (54/77) were identified as major barriers to implementation of pharmacogenomics. Comprehensive reimbursement for testing and clinical practice guidelines, alongside models-of-care involving multidisciplinary teams and local clinical champions were suggested as strategies to facilitate implementation of pharmacogenomic testing into practice. CONCLUSIONS: Pharmacogenomic testing was considered important to guide drug selection and dosing decisions. However, limited knowledge, low confidence and an absence of guidelines impede the use of pharmacogenomic testing. Establishment of local resources including multidisciplinary models-of-care was suggested to facilitate implementation of pharmacogenomics.

Improved provider preparedness through an 8-part genetics and genomic education program.

PURPOSE: Large-scale genetics education appropriate for general practice providers is a growing priority. We describe the content and impact of a mandatory system-wide program implemented at Sanford Health. METHODS: The Imagenetics Initiative at Sanford Health developed a 2-year genetics education program with quarterly web-based modules that were mandatory for all physicians and advanced practice providers. Scores of 0 to 5 were calculated for each module on the basis of the number of objectives that the participants reported as fulfilled. In addition, the participants completed surveys before starting and after finishing the education program, which included a 7-item measure scored 7 to 28 on the perceived preparedness to practice genetics. RESULTS: Between 2252 and 2822 Sanford Health employees completed each of the 8 quarterly education modules. The ratings were highest for the module about using genomics to improve patient management (mean score = 4.3) and lowest for the module about different types of genetic tests and specialists. The mean perceived preparedness scores increased from 15.7 at pre-education to 19.1 at post-education (P < .001). CONCLUSION: Web-based genetics education was highly effective in increasing health care providers' confidence about using genetics. Both comfort with personal knowledge and confidence regarding access to the system's genomic medicine experts increased significantly. The results demonstrate how scalable approaches can improve provider preparedness.

Understanding the barriers and enablers of pharmacogenomic testing in primary care: a qualitative systematic review with meta-aggregation synthesis.

Introduction: Pharmacogenomic testing can indicate which drugs may have limited therapeutic action or lead to adverse effects, hence guiding rational and safe prescribing. However, in the UK and other countries, there are still significant barriers to implementation of testing in primary care. Objective: This systematic review presents the barriers and enablers to the implementation of pharmacogenomics in primary care setting. Materials & methods: MEDLINE, EMBASE, PsycINFO and CINAHL databases were searched through to July 2020 for studies that reported primary qualitative data of primary care professionals and patient views. Following screening, data extraction and quality assessment, data synthesis was undertaken using meta-aggregation based on the theoretical domain's framework (TDF). Confidence in the synthesized findings relating to credibility and dependability was established using CONQual. Eligible papers were categorized into six TDF domains - knowledge; social and professional roles; behavioral regulation; beliefs and consequences; environmental context and resources; and social influences. Results: From 1669 citations, eighteen eligible studies were identified across seven countries, with a sample size of 504 participants including both primary care professionals and patients. From the data, 15 synthesized statements, all with moderate CONQual rating emerged. These categories range from knowledge, awareness among Primary Care Physicians and patients, professional relationships, negative impact of PGx, belief that PGx can reduce adverse drug reactions, clinical evidence, cost-effectiveness, informatics, reporting issues and social issues. Conclusion: Through use of TDF, fifteen synthesized statements provide policymakers with valuable recommendations for the implementation of pharmacogenomics in primary care. In preparation, policymakers need to consider the introduction of effective educational strategies for both PCPs and patients to raise knowledge, awareness, and engagement. The actual introduction of PGx will require reorganization with decision support tools to aid use of PGx in primary care, with a clear delegation of roles and responsibilities between general professionals and pharmacists supplemented by a local pool of experts. Furthermore, policy makers need to address the cost effectiveness of pharmacogenomics and having appropriate infrastructure supporting testing and interpretation including informatic solutions for utilizing pharmacogenomic results.