Label Accuracy of Legal Oral Cannabis Oil Products in Ontario, Canada.

This case series compares amounts of tetrahydrocannabinol and cannabidiol reported on product labels vs levels found in laboratory testing in legal oral cannabis oil products in Ontario, Canada.

Re-discover the value of protein binding assessments in hepatic and renal impairment studies and its contributions in drug labels and dose decisions.

One of the key pharmacokinetic properties of most small molecule drugs is their ability to bind to serum proteins. Unbound or free drug is responsible for pharmacological activity while the balance between free and bound drug can impact drug distribution, elimination, and other safety parameters. In the hepatic impairment (HI) and renal impairment (RI) clinical studies, unbound drug concentration is often assessed; however, the relevance and impact of the protein binding (PB) results is largely limited. We analyzed published clinical safety and pharmacokinetic studies in subjects with HI or RI with PB assessment up to October 2022 and summarized the contribution of PB results on their label dose recommendations. Among drugs with HI publication, 32% (17/53) associated product labels include PB results in HI section. Of these, the majority (9/17, 53%) recommend dose adjustments consistent with observed PB change. Among drugs with RI publication, 27% (12/44) of associated product labels include PB results in RI section with the majority (7/12, 58%) recommending no dose adjustment, consistent with the reported absence of PB change. PB results were found to be consistent with a tailored dose recommendation in 53% and 58% of the approved labels for HI and RI section, respectively. We further discussed the interpretation challenges of PB results, explored treatment decision factors including total drug concentration, exposure-response relationships, and safety considerations in these case examples. Collectively, comprehending the alterations in free drug levels in HI and RI informs treatment decision through a risk-based approach.

Text summarization with ChatGPT for drug labeling documents.

Text summarization is crucial in scientific research, drug discovery and development, regulatory review, and more. This task demands domain expertise, language proficiency, semantic prowess, and conceptual skill. The recent advent of large language models (LLMs), such as ChatGPT, offers unprecedented opportunities to automate this process. We compared ChatGPT-generated summaries with those produced by human experts using FDA drug labeling documents. The labeling contains summaries of key labeling sections, making them an ideal human benchmark to evaluate ChatGPT's summarization capabilities. Analyzing >14000 summaries, we observed that ChatGPT-generated summaries closely resembled those generated by human experts. Importantly, ChatGPT exhibited even greater similarity when summarizing drug safety information. These findings highlight ChatGPT's potential to accelerate work in critical areas, including drug safety.

Removing penicillin allergy label in a hospitalized adolescent with a remote penicillin and recent cephalosporin allergy.

Background: ß-Lactam antibiotics are widely used with increased utilization in hospitalized patients. Of this population, as high as 10-20% report an allergy to ß-lactam antibiotics but <5% are at risk of developing clinically significant immunoglobulin E- or T-lymphocyte-mediated reactions. Most of the time, these reported allergies are present during an illness with no previous inquiry of their validity, which makes investigation and possible removal of this allergy label a challenge. Methods: We report a 16-year-old boy who presented with 1 week of night sweats, chills, headaches, and fatigue, followed by 1 day of fever and right knee swelling and who was diagnosed with septic bursitis. Due to concern of a penicillin allergy label, the patient was started on a cefepime infusion. Five minutes into the infusion, the patient reported puffy eyes and itchy throat, followed by a witnessed cascading flat nonpruritic erythematous rash from head to shoulders. This rash went away in 3 minutes after stopping the infusion and the patient being given 50 mg of intravenous diphenhydramine and 10 mg of oral dexamethasone. He was subsequently diagnosed with a cefepime allergy. Results: Allergy/immunology was the speciality consulted, and, by using a screening questionnaire, the patient's reported penicillin allergy was determined to be low risk. Subsequent 1-step oral challenge was the key to providing the patient with the necessary antibiotic course to resolve his infection. Conclusion: Multiple reported antibiotic allergies lead to poor antibiotic stewardship that causes impactful health and financial burden on the patient and health-care system. It is thus important to have an evidence-based systematic approach to de-label penicillin antibiotic allergy labels to reduce these potential harms.

Postmarket safety communications on drugs approved in Japan: A 25-year analysis.

Drug safety communications (DSCs) are essential tools for communicating important postmarket serious drug safety information to healthcare professionals and patients. Previous studies characterized DSCs issued by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA); however, knowledge about the activities of the Pharmaceuticals and Medical Devices Agency (PMDA)/the Ministry of Health, Labor and Welfare (MHLW) is limited. This study characterized DSCs by the PMDA/MHLW in comparison with previously reported DSCs by the FDA and the EMA. We retrospectively analyzed 37 DSCs of 41 adverse drug reactions (ADRs) for 33 drugs in Japan from 1997 to 2022. Most DSCs were related to non-oncology drugs (30/37, 81.1%), and the median (interquartile range) time from approval to DSC issuance was 19 (10-51) months. Notably, the regulatory review reports and the latest labels before DSC issuance did not describe 16/28 (57.1%) and 12/37 (32.4%) of the ADRs related to DSCs, respectively. Most DSCs resulted in label revisions (36/37, 97.3%) and seven drugs were eventually withdrawn. Some DSC characteristics are similar among the PMDA/MHLW, the FDA, and the EMA; however, the number, contents, and range of new safety issues addressed by DSCs differ among the three jurisdictions. Our study emphasized the importance of continuous efforts to gather postmarket drug safety information because substantial ADRs that led to DSCs were recognized after approval and were associated with critical label revisions and withdrawals. Future studies are required to address global challenges for regulatory harmonization of safety-related regulatory actions.

FDA Issues Warning About 'Gas Station Heroin'.

The highly addictive dietary supplement mimics opioid effects.

A framework enabling LLMs into regulatory environment for transparency and trustworthiness and its application to drug labeling document.

Regulatory agencies consistently deal with extensive document reviews, ranging from product submissions to both internal and external communications. Large Language Models (LLMs) like ChatGPT can be invaluable tools for these tasks, however present several challenges, particularly the proprietary information, combining customized function with specific review needs, and transparency and explainability of the model's output. Hence, a localized and customized solution is imperative. To tackle these challenges, we formulated a framework named askFDALabel on FDA drug labeling documents that is a crucial resource in the FDA drug review process. AskFDALabel operates within a secure IT environment and comprises two key modules: a semantic search and a Q&A/text-generation module. The Module S built on word embeddings to enable comprehensive semantic queries within labeling documents. The Module T utilizes a tuned LLM to generate responses based on references from Module S. As the result, our framework enabled small LLMs to perform comparably to ChatGPT with as a computationally inexpensive solution for regulatory application. To conclude, through AskFDALabel, we have showcased a pathway that harnesses LLMs to support agency operations within a secure environment, offering tailored functions for the needs of regulatory research.

Learning with an evolving medicine label: how artificial intelligence-based medication recommendation systems must adapt to changing medication labels.

INTRODUCTION: Artificial intelligence or machine learning (AI/ML) based systems can help personalize prescribing decisions for individual patients. The recommendations of these clinical decision support systems must relate to the "label" of the medicines involved. The label of a medicine is an approved guide that indicates how to prescribe the drug in a safe and effective manner. AREAS COVERED: The label for a medicine may evolve as new information on drug safety and effectiveness emerges, leading to the addition or removal of warnings, drug-drug interactions, or to permit new indications. However, the speed at which these updates are made to these AI/ML recommendation systems may be delayed and could influence the safety of prescribing decisions. This article explores the need to keep AI/ML tools 'in sync' with any label changes. Additionally, challenges relating to medicine availability and geographical suitability are discussed. EXPERT OPINION: These considerations highlight the important role that pharmacoepidemiologists and drug safety professionals must play within the monitoring and use of these tools. Furthermore, these issues highlight the guiding role that regulators need to have in planning and oversight of these tools.

Artificial intelligence or machine learning (AI/ML) based systems that guide the prescription of medications have the potential to vastly improve patient care, but these tools should only provide recommendations that are in line with the label of a medicine. With a constantly evolving medication label, this is likely to be a challenge, and this also has implications for the off-label use of medicines.

Penicillin allergy reassessment for treatment improvement: A dental office tool to support appropriate penicillin allergy labeling.

BACKGROUND: Dental appointments offer an opportunity to evaluate a documented penicillin (PCN) allergy and determine whether the patient might be a candidate for medical reassessment of their allergy. The authors gathered feedback on the Penicillin Allergy Reassessment for Treatment Improvement (PARTI) tool, designed to enhance dentist-patient communications regarding PCN allergies. METHODS: From January 2022 through May 2023, the authors conducted a mixed-methods study, collecting focus group data from patients with PCN allergies and surveying health care workers (HCWs) regarding the PARTI tool. Feedback focused on reassessment procedures, patient-centered allergy information, and medical records updates. Thematic analysis was used for focus group data. RESULTS: The study included 15 patients in focus groups and 50 HCW survey respondents representing diverse US regions. Patient demographic characteristics included varied races, the mean age was 52 years, and most of the patients were female (53.3%). Most patients had health care interactions within the preceding year, at which 86.6% of patients were asked about drug allergies. HCW respondents primarily consisted of pharmacists (30%) and dentists, dental hygienists, and dental assistants (28%). Feedback on the PARTI tool was constructive, with both patients and HCWs recognizing its potential benefits and providing insights for improvement. Many HCWs (68%) highlighted the importance of step 3 of the PARTI tool, that is, the section on PCN allergy testing. Feedback from participants was incorporated into the final PARTI tool. CONCLUSIONS: Patient and HCW feedback on the PARTI tool was used to finalize a tool for the dental office to provide to patients who are candidates for PCN allergy reassessment. The feedback will also be used to inform an upcoming pilot study in US dental offices, focused on the process for PCN allergy reassessment and health record documentation. PRACTICAL IMPLICATIONS: Deploying the PARTI tool in dental offices is pivotal, as mislabeling patients with PCN allergies could have severe consequences, such as hindering the prescription of lifesaving antibiotics for conditions like endocarditis, in the future. This implementation not only enhances communication between dentists and patients, but it is also crucial for ensuring improved patient safety and maintaining accurate medical records among health care settings.

Patient information leaflets and package inserts of ibuprofen provided in the UK and Thailand: a comparative assessment.

OBJECTIVES: Written medicine information (WMI) is important for ensuring patients understand and use their medicines optimally, but relatively little research has assessed the quality of available WMI. This study assessed the quality of WMI using a sample of leaflets for ibuprofen in the UK and Thailand. METHODS: Leaflets were obtained by purchasing a product from retail outlets or community pharmacies, 18 from each country. In the UK, these were patient information leaflets (PILs); in Thailand, they were package inserts PIs not specifically designed for patients. Leaflets were assessed for content, layout, and readability using standard methods and compared to relevant guidelines. KEY FINDINGS: The UK PILs were uniform and conformed to EU regulatory requirements for content, whereas Thai PIs varied considerably, many failing to include important information required by Thai regulations. Several forms of Thai PIs were found, including some very short leaflets, containing minimal information. The readability of both was rated as poor, all used small font size and had less than desirable white space. Fewer Thai PIs than UK PILs met the Keystone Criteria for ibuprofen. CONCLUSIONS: The extent of variation in format and content of Thai WMI could potentially cause confusion and reduce willingness to read it. PILs, conforming to Thai regulatory guidelines, should be provided with medicines instead. Leaflets in both countries would benefit from improved readability and layout.

Authorized or Off-Label Use? A Structured Analysis of Summaries of Product Characteristics with Regard to Authorization in Pediatrics.

PURPOSE: The Summary of Product Characteristics (SmPC) is required to provide unambiguous information on the authorized use of a medicinal product. Therefore, we performed a structured analysis of the information provided for pediatric patients in current SmPCs. METHODS: In the German SmPC of the medicinal products of 452 active substances, we analyzed for each of the listed indications whether information on pediatric use was available in Sects. 4.1-4.4 of the SmPC and, if so, whether it was unambiguous. Information was considered unambiguous if it indicated an exact age- or weight-related specification. The analysis also considered the type of marketing authorization and the date of marketing authorization, either before or after the Pediatric Regulation 2007 came into force. RESULTS: Among the 30,354 identified indications in 8464 SmPCs, unambiguous information was found for 72.4% (21,974/30,354) of the indications. Of these, 45.4% (9967/21,974) disclosed a contraindication for the entire population under 18 years of age. The proportion of unambiguous information was higher for medicinal products with centralized marketing authorization (86.5% [1449/1676]) than for those with a national one (71.6% [20,525/28,678]; p < 0.001). A higher proportion of unambiguous information was found for the marketing authorization period 2007-2021 compared with 1996-2006 (1996-2006: 63.8% [7466/11,694]; 2007-2021: 82.1% [12,349/15,040]; p < 0.001). CONCLUSION: For about a quarter of all indications, no or only ambiguous information was available for pediatric patients. The measures initiated in recent years to increase pediatric-specific information in SmPCs should be intensified in order to improve drug safety in children and adolescents.