Comparing cytochrome P450 pharmacogenetic information available on United States drug labels and European Union Summaries of Product Characteristics

Pharmacogenomic biomarker information on drug labels of the Spanish Agency of Medicines and Sanitary products: evaluation and comparison with other regulatory agencies

This work aimed to analyse the pharmacogenetic information in the Spanish Drug Regulatory Agency (AEMPS) Summary of Products Characteristics (SmPC), evaluating the presence of pharmacogenetic biomarkers, as well as the associated recommendations. A total of 55.4% of the 1891 drug labels reviewed included information on pharmacogenetic biomarker(s). Pharmacogenomic information appears most frequently in the "antineoplastic and immunomodulating agents", "nervous system", and "cardiovascular system" Anatomical Therapeutic Chemical groups. A total of 509 different pharmacogenetic biomarkers were found, of which CYP450 enzymes accounted for almost 34% of the total drug-biomarker associations evaluated. A total of 3679 drug-biomarker pairs were identified, 102 of which were at the 1A level (PharmGKB® classification system), and 33.33% of these drug-pharmacogenetic biomarker pairs were assigned to "actionable PGx", 12.75% to "informative PGx", 4.9% to "testing recommended", and 4.9% to "testing required". The rate of coincidence in the assigned PGx level of recommendation between the AEMPS and regulatory agencies included in the PharmGKB® Drug Label Annotations database (i.e., the FDA, EMA, SWISS Medic, PMDA, and HCSC) ranged from 45% to 65%, being 'actionable level' the most frequent. On the other hand, discrepancies between agencies did not exceed 35%. This study highlights the presence of relevant pharmacogenetic information on Spanish drug labels, which would help avoid interactions, toxicity, or lack of treatment efficacy.

Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends

Physiologically-based pharmacokinetics (PBPK) modeling is a robust tool that supports drug development and the pharmaceutical industry and regulatory authorities. Implementation of predictive systems in the clinics is more than ever a reality, resulting in a surge of interest for PBPK models by clinicians. We aimed to establish a repository of available PBPK models developed to date to predict drug-drug interactions (DDIs) in the different therapeutic areas by integrating intrinsic and extrinsic factors such as genetic polymorphisms of the cytochromes or environmental clues. This work includes peer-reviewed publications and models developed in the literature from October 2017 to January 2021. Information about the software, type of model, size, and population model was extracted for each article. In general, modeling was mainly done for DDI prediction via Simcyp^® software and Full PBPK. Overall, the necessary physiological and physio-pathological parameters, such as weight, BMI, liver or kidney function, relative to the drug absorption, distribution, metabolism, and elimination and to the population studied for model construction was publicly available. Of the 46 articles, 32 sensibly predicted DDI potentials, but only 23% integrated the genetic aspect to the developed models. Marked differences in concentration time profiles and maximum plasma concentration could be explained by the significant precision of the input parameters such as Tissue: plasma partition coefficients, protein abundance, or Ki values. In conclusion, the models show a good correlation between the predicted and observed plasma concentration values. These correlations are all the more pronounced as the model is rich in data representative of the population and the molecule in question. PBPK for DDI prediction is a promising approach in clinical, and harmonization of clearance prediction may be helped by a consensus on selecting the best data to use for PBPK model development.

Variability of Pharmacogenomics Information in Drug Labels Approved by Different Agencies and Its Ethical Implications

AIMS

The aim of this study was to determine if there are discrepancies among various agency-approved labels for the same active ingredient and where the labels approved by the Turkish Medicines and Medical Devices Agency (TMMDA) stand regarding the inclusion of PGx and discuss these ethical implications.

BACKGROUND

The efficacy and safety of drugs can be improved by rational prescription and personalization of medicine for each patient. Pharmacogenomics information (PGx) in drug labels (DL) is one of the important tools for the personalization of medications because genetic differences may affect both drug efficacy and safety. Providing adequate PGx to patients has ethical implications.

OBJECTIVE

To evaluate PGx in the DLs approved by TMMDA and other national agencies provided by the Pharmacogenomics Knowledgebase.

METHODS

DL annotations from the Pharmacogenomics Knowledgebase and DLs approved by the TMMDA were analyzed according to information and action levels, which are "testing required", "testing recommended", "actionable", and "informative".

RESULTS

There are 381 drugs listed in PharmGKB drug label annotations with pharmacogenomics information and 278 of these have biomarkers. A total of 242 (63.5%) drugs are approved and available in Turkey. Of these, 207 (85.5%) contain the same information as in or similar to that in the labels approved by the other agencies. The presence and level of information varied among the DLs approved by different agencies. The inconsistencies may have an important effect on the efficacy and the safety of drugs.

CONCLUSION

These findings suggest a need for the standardization of PGx information globally because it may not only affect the efficacy and safety of medications but also essential ethical rules regarding patient rights by violating not sufficiently sharing all available information.

Pharmacogenetic information in Swiss drug labels - a systematic analysis

Implementation of pharmacogenetics (PGx) and individualization of drug therapy is supposed to obviate adverse drug reactions or therapy failure. Health care professionals (HCPs) use drug labels (DLs) as reliable information about drugs. We analyzed the Swiss DLs to give an overview on the currently available PGx instructions. We screened 4306 DLs applying natural language processing focusing on drug metabolism (pharmacokinetics) and we assigned PGx levels following the classification system of PharmGKB. From 5979 hits, 2564 were classified as PGx-relevant affecting 167 substances. 55% (n = 93) were classified as "actionable PGx". Frequently, PGx information appeared in the pharmacokinetics section and in DLs of the anatomic group "nervous system". Unstandardized wording, appearance of PGx information in different sections and unclear instructions challenge HCPs to identify and interpret PGx information and translate it into practice. HCPs need harmonization and standardization of PGx information in DLs to personalize drug therapies and tailor pharmaceutical care.

Pharmacogenetics in psychiatric care, a call for uptake of available applications

In this narrative, we evaluate the role of pharmacogenetics in psychiatry from a pragmatic clinical perspective and address current barriers of clinical implementation of pharmacogenetics. Pharmacogenetics has been successfully implemented to improve drug therapy in several clinical areas, but not psychiatry. Yet, psychotropics account for more than one-third of the drugs for which pharmacogenetic guidelines are available and drug therapy in mental disorders is suboptimal with insufficient effectiveness and frequent adverse events. The limited application of pharmacogenetics in psychiatry is influenced by several factors; e.g. the complexity of psychotropic drug metabolism, possibly impeding the clinical understanding of the benefits of pharmacogenetics. Also, recommendations for most psychotropics classify pharmacogenetic testing only as (potentially) beneficial, not as essential, possibly because life-threatening adverse events are often not involved in these drug-gene interactions. Implementing pharmacogenetics in psychiatry could improve the current practice of time-consuming switching of therapies causing undue delays associated with worse outcomes. We expect pharmacogenetics in psychiatry to expedite with panel-based genotyping, including clinically relevant variants, which will address the complex enzymatic metabolism of psychotropic drugs. Until then, we stress that available pharmacogenetic testing should be seen as an integrated companion, not a competitor, in current clinical psychiatric care.

Implementation of pharmacogenomics in product information

Aim: The aim of our study was to analyse the level of implementation of pharmacogenomics (PGx) in product information (PI) of medicinal products approved through national procedures in the EU. Materials & methods: In the analysis, we included nationally approved medicinal products in Croatia if guidelines for relevant substances were published. Results: Overall, 265 marketing authorizations were analyzed. The majority of data included in PI was only informative, while the most frequent PGx biomarkers were genes which code CYP P450. Analysis according to the Anatomical Therapeutic Chemical classification revealed that most substances belonged to the nervous system. Conclusion: Although hindrances in implementation are anticipated, PI should be more specific in terms of when the testing is indicated and should include actionable recommendations according to the results of PGx testing.

Pharmacogenomic biomarker information differences between drug labels in the United States and Hungary: implementation from medical practitioner view

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.

Regulatory sciences and translational pharmacogenetics: amitriptyline as a case in point

Regulatory developments and clinical implementation, or the lack thereof, are primary clinchers, in the enduring endeavors to realize the translational quality of pharmacogenetics. Here, we present the case of amitriptyline, an established drug with pharmacogenetic implications. The integration of pharmacogenetic information in the official product literature and throughout the evaluation of safety concerns is considered. In our opinion, apart from emboldening genomic research in drug development and the valid pursuit towards global harmonization in the field, it is rational to look into the applicability of the data we have today.

Development of a tool to assess the completeness of drug information sources for health care professionals: A Delphi study

The aim of this study was to create a standard set of essential drug information items as a tool to assess the completeness of any type of drug information source, regardless of its length, using a Delphi consensus panel of European health care professionals. A compilation of drug-related information items was performed by searching several resources for health care professionals and a final list of 162 items was obtained. Fifty-seven experts in drug information from 23 different European countries were invited to participate in a three-round Delphi technique to obtain consensus on items considered essential and non-essential content of information. Consensus for the first, second, and third rounds was defined as ≥90%, ≥80%, and ≥75% agreement, respectively. Of the 57 experts invited, 32 completed the first round, 27 the second, and 29 the third. Consensus was achieved for 28.3% of the items in the first round, 49.3% in the second, and 58.3% in the third. The final cumulative consensus was 67.7% (n = 126) for items considered essential and 16.1% (n = 30) for items considered non-essential. The final tool obtained to assess the completeness of drug information sources was composed by 126 essential items grouped into 11 sections. This tool allows for the comparison of different information sources for the same medicine and the information content for different medicines in the same source.