Pharmacogenetic information in Swiss drug labels - a systematic analysis.
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ABSTRACT:
SUBMITTER: Jeiziner C
PROVIDER: S-EPMC8292148 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The primary goal of precision medicine is to maximize the benefit-risk relationships for individual patients by delivering the right drug to the right patients at the right dose. To achieve this goal, it has become increasingly important to assess gene-drug interactions (GDIs) in clinical settings. The US Food and Drug Administration (FDA) periodically updates the table of pharmacogenetic/genomic (PGx) biomarkers in drug labeling on their website. As described herein, an effort was made to categorize various PGx biomarkers covered by the FDA-PGx table into certain groups. There were 2 major groups, oncology molecular targets (OMT) and drug-metabolizing enzymes and transporters (DMETs), which constitute ~70% of all biomarkers (~33% and ~35%, respectively). These biomarkers were further classified whether their labeling languages could be actionable in clinical practice. For OMT biomarkers, ~70% of biomarkers are considered actionable in clinical practice as they are critical for the selection of appropriate drugs to individual patients. In contrast, ~30% of DMET biomarkers are considered actionable for the dose adjustments or alternative therapies in specific populations, such as CYP2C19 and CYP2D6 poor metabolizers. In addition, the GDI results related to some of the other OMT and DMET biomarkers are considered to provide valuable information to clinicians. However, clinical GDI results on the other DMET biomarkers can possibly be used more effectively for dose recommendation. As the labels of some drugs already recommend the precise doses in specific populations, it will be desirable to have clear language for dose recommendation of other (or new) drugs if appropriate.
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Project description:Although weight gain is a serious but variable adverse effect of antipsychotics that has genetic underpinnings, a comprehensive meta-analysis of pharmacogenetics of antipsychotic-related weight gain is missing. In this review, random effects meta-analyses were conducted for dominant and recessive models on associations of specific single nucleotide polymorphisms (SNP) with prospectively assessed antipsychotic-related weight or body mass index (BMI) changes (primary outcome), or categorical increases in weight or BMI (?7%; secondary outcome). Published studies, identified via systematic database search (last search: December 31, 2014), plus 3 additional cohorts, including 222 antipsychotic-naïve youth, and 81 and 141 first-episode schizophrenia adults, each with patient-level data at 3 or 4 months treatment, were meta-analyzed. Altogether, 72 articles reporting on 46 non-duplicated samples (n = 6700, mean follow-up = 25.1wk) with 38 SNPs from 20 genes/genomic regions were meta-analyzed (for each meta-analysis, studies = 2-20, n = 81-2082). Eleven SNPs from 8 genes were significantly associated with weight or BMI change, and 4 SNPs from 2 genes were significantly associated with categorical weight or BMI increase. Combined, 13 SNPs from 9 genes (Adrenoceptor Alpha-2A [ADRA2A], Adrenoceptor Beta 3 [ADRB3], Brain-Derived Neurotrophic Factor [BDNF], Dopamine Receptor D2 [DRD2], Guanine Nucleotide Binding Protein [GNB3], 5-Hydroxytryptamine (Serotonin) Receptor 2C [HTR2C], Insulin-induced gene 2 [INSIG2], Melanocortin-4 Receptor [MC4R], and Synaptosomal-associated protein, 25kDa [SNAP25]) were significantly associated with antipsychotic-related weight gain (P-values < .05-.001). SNPs in ADRA2A, DRD2, HTR2C, and MC4R had the largest effect sizes (Hedges' g's = 0.30-0.80, ORs = 1.47-1.96). Less prior antipsychotic exposure (pediatric or first episode patients) and short follow-up (1-2 mo) were associated with larger effect sizes. Individual antipsychotics did not significantly moderate effect sizes. In conclusion, antipsychotic-related weight gain is polygenic and associated with specific genetic variants, especially in genes coding for antipsychotic pharmacodynamic targets.
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Project description:AimsA 23-year-old Caucasian woman, with cystic fibrosis, bilateral lung-transplantation and immunosuppressive therapy with prednisolone, tacrolimus and sirolimus, presented with clinical symptoms of a chronic transplant rejection.MethodsSince constant sufficient blood level of tacrolimus and sirolimus had never been achieved, a genetic analysis was carried out to clarify drug metabolism.ResultsThe genetic analysis for polymorphisms of cytochrome P450 (CYP) 3A4,5,7 revealed no sequence alterations in the CYP 3A4,5,7 gene. Thus, drug intake was scrutinized in detail, disclosing a missing interval between the intake of both immunosuppressive agents. After a correct drug intake the woman's condition ameliorated and the blood levels reached normal range.ConclusionsThis case report highlights the crucial importance of basic medical skills like an accurate and dainty drug anamnesis before high tech approaches were applied.
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Project description:This study aimed to evaluate in the Brazilian population, the genotypes and population frequencies of pharmacogenetic polymorphisms involved in the response to drugs used in treatment of acute lymphoblastic leukemia (ALL), and to compare the data with data from the HapMap populations. There was significant differentiation between most population pairs, but few associations between genetic ancestry and SNPs in the Brazilian population were observed. AMOVA analysis comparing the Brazilian population to all other populations retrieved from HapMap pointed to a genetic proximity with the European population. These associations point to preclusion of the use of genetic ancestry as a proxy for predicting drug response. In this way, any study aiming to correlate genotype with drug response in the Brazilian population should be based on pharmacogenetic SNP genotypes.
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Project description:BackgroundThe FDA Patient-Focused Drug Development Initiative was launched to ensure the incorporation of the patient voice into drug development and evaluation. Since 2017, the FDA must publish a statement outlining patient experience data (PED) considered in the approval of new drugs. This study investigated the presence and role of PED in drug approval and translation into product label claims.MethodsPED reported in approval packages of the 48 drugs approved by FDA's Center for Drug Evaluation and Research in 2019 was identified and categorized. PED in the form of clinical outcome assessments (COAs) was characterized by endpoint positioning and outcome. The product labels were analyzed for PED-related claims.ResultsPED was reported as relevant for 39 of 48 (81.3%) drugs approved in 2019. COAs were the predominant PED type; other PED was identified for only 9 (18.8%) drugs, and none included qualitative or patient preference studies. COAs were the only type of PED for which associated claims were identified in the product labels. 27 out of 48 (56.3%) labels contained one or more efficacy claims based on COAs; of these, patient-reported outcomes were the most prevalent with claims identified in 19 labels (39.6%).ConclusionThere are ample opportunities for incorporating PED beyond COAs to inform drug development and facilitate availability of medicines tailored to patient needs. A higher level of transparency on the role of PED in regulatory decision-making and a clear path to PED-based label claims could incentivize sponsors and enable patient empowerment in treatment decisions.
| S-EPMC8021513 | biostudies-literature
Project description:The safety information on drug labels of a company marketing the same drugs in different countries is sometimes different. The aim of the present study is to understand the differences in the volume and content of safety information on the drug labels from the same manufacturers in three developed countries: the United States of America (USA), the United Kingdom (UK) and Canada. This study involved the calculation of the proportion of total safety information (PSI) and of contraindications (PCI) in comparison to all information on the label and the percentage of boxed warnings (PBW) among the 100 labels studied from each country. The PSI on the labels of different countries is different with USA labels bearing lesser value PSI and UK labels bearing higher value PSI. The qualitative information provided on these drug labels from each country in 'contraindications' sections, 'boxed/serious warnings' and 'overdosage' sections presented differences in the information provided on most of the labels. We have found distinct differences between the safety information available on drug labels in terms of volume and content. We conclude that the safety information for the same products should be standardised across all countries.
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Project description:Voriconazole (VRC) is used as first line antifungal agent against invasive aspergillosis. Model-based approaches might optimize VRC therapy. This study aimed to investigate the predictive performance of pharmacokinetic models of VRC without pharmacogenetic information for their suitability for model-informed precision dosing. Seven PopPK models were selected from a systematic literature review. A total of 66 measured VRC plasma concentrations from 33 critically ill patients was employed for analysis. The second measurement per patient was used to calculate relative Bias (rBias), mean error (ME), relative root mean squared error (rRMSE) and mean absolute error (MAE) (i) only based on patient characteristics and dosing history (a priori) and (ii) integrating the first measured concentration to predict the second concentration (Bayesian forecasting). The a priori rBias/ME and rRMSE/MAE varied substantially between the models, ranging from -15.4 to 124.6%/-0.70 to 8.01 mg/L and from 89.3 to 139.1%/1.45 to 8.11 mg/L, respectively. The integration of the first TDM sample improved the predictive performance of all models, with the model by Chen (85.0%) showing the best predictive performance (rRMSE: 85.0%; rBias: 4.0%). Our study revealed a certain degree of imprecision for all investigated models, so their sole use is not recommendable. Models with a higher performance would be necessary for clinical use.
| S-EPMC9505877 | biostudies-literature
Project description:Pharmacogenomic biomarker availability of Hungarian Summaries of Product Characteristics (SmPC) was assembled and compared with the information in US Food and Drug Administration (FDA) drug labels of the same active substance (July 2019). The level of action of these biomarkers was assessed from The Pharmacogenomics Knowledgebase database. From the identified 264 FDA approved drugs with pharmacogenomic biomarkers in drug label, 195 are available in Hungary. From them, 165 drugs include pharmacogenomic data disposing 222 biomarkers. Most of them are metabolizing enzymes (46%) and pharmacological targets (41%). The most frequent therapeutic area is oncology (37%), followed by infectious diseases (12%) and psychiatry (9%) (p?<?0.00001). Most common biomarkers in Hungarian SmPCs are CYP2D6, CYP2C19, estrogen and progesterone hormone receptor (ESR, PGS). Importantly, US labels present more specific pharmacogenomic subheadings, the level of action has a different prominence, and offer more applicable dose modifications than Hungarians (5% vs 3%). However, Hungarian SmPCs are at 9 oncology drugs stricter than FDA, testing is obligatory before treatment. Out of the biomarkers available in US drug labels, 62 are missing completely from Hungarian SmPCs (p?<?0.00001). Most of these belong to oncology (42%) and in case of 11% of missing biomarkers testing is required before treatment. In conclusion, more factual, clear, clinically relevant pharmacogenomic information in Hungarian SmPCs would reinforce implementation of pharmacogenetics. Underpinning future perspective is to support regulatory stakeholders to enhance inclusion of pharmacogenomic biomarkers into Hungarian drug labels and consequently enhance personalized medicine in Hungary.
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Project description:BackgroundThe indication for prescribing a particular medication, or its reason for use (RFU) is a crucial piece of information for all those involved in the circle of care. Research has shown that sharing RFU information with physicians, pharmacists and patients improves patient safety and patient adherence, however RFU is rarely added on prescriptions by prescribers or on medication labels for patients to reference.MethodsQualitative interviews were conducted with 20 prescribers in Southern Ontario, Canada, to learn prescribers' current attitudes on the addition of RFU on prescriptions and medication labels. A trained interviewer used a semi-structured interview guide for each interview. The interviews explored how the sharing of RFU information would impact prescribers' workflows and practices. Interviews were recorded, transcribed and thematically coded.ResultsThe analysis yielded four main themes: Current Practice, Future Practice, Changing Culture, and Collaboration. Most of the prescribers interviewed do not currently add RFU to prescriptions. Prescribers were open to sharing RFU with colleagues via a regional database but wanted the ability to provide context for the prescribed medication within the system. Many prescribers were wary of the impact of adding RFU on their workflow but felt it could save time by avoiding clarifying questions from pharmacists. Increased interprofessional collaboration, increased patient understanding of prescribed medications, avoiding guesswork when determining indications and decreased misinterpretation regarding RFU were cited by most prescribers as benefits to including RFU information.ConclusionsPrescribers were generally open to sharing RFU and clearly identified the benefits to pharmacists and patients if added. Critically, they also identified benefits to their own practices. These results can be used to guide the implementation of future initiatives to promote the sharing of RFU in healthcare teams.
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Project description:Absence labels promote the absence of a particular ingredient or production practice. Consumers usually perceive organic labels as an umbrella absence label for a variety of ingredients and production practices. Such organic labels often use similar language but are based on different certification requirements. For example, both organic wine and wine made with organic grapes are available to U.S. consumers, but little is known about consumer preferences for such labeled products when information about the certification standards is available. Moreover, while absence labels, which advertise the absence of certain attributes or practices, are prevalent on the market, little is known about how information on conventional production practices impacts consumer behavior. Using an artefactual experiment with 128 adult non-student participants, we investigate consumer demand for conventional wine, organic wine, and wine made with organic grapes when information about production standards is provided to participants with and without details regarding conventional winemaking practices. We find that while both organic labels carry a significant and very similar willingness-to-pay (WTP) premium, information about certification standards and conventional wine making practices can reduce WTP for all wines. Providing information about the two organic certification standards reduces consumer WTP for both absence labeled and conventional wine categories. This effect largely disappears for organic wine, but not wine made with organic grapes, when information about conventional wine-making practices is also provided.
| S-EPMC6594594 | biostudies-literature