Safety and quality of AI chatbots for drug-related inquiries: A real-world comparison with licensed pharmacists.

Introduction: Pharmacists play a pivotal role in ensuring patients are administered safe and effective medications; however, they encounter obstacles such as elevated workloads and a scarcity of qualified professionals. Despite the prospective utility of large language models (LLMs), such as Generative Pre-trained Transformers (GPTs), in addressing pharmaceutical inquiries, their applicability in real-world cases remains unexplored. Objective: To evaluate GPT-based chatbots' accuracy in real-world drug-related inquiries, comparing their performance to licensed pharmacists. Methods: In this cross-sectional study, authors analyzed real-world drug inquiries from a Drug Information Inquiry Database. Two independent pharmacists evaluated the performance of GPT-based chatbots (GPT-3, GPT-3.5, GPT-4) against human pharmacists using accuracy, detail, and risk of harm criteria. Descriptive statistics described inquiry characteristics. Absolute proportion comparative analyses assessed accuracy, detail, and risk of harm. Stratified analyses were performed for different inquiry types. Results: Seventy inquiries were included. Most inquiries were received from physicians (41%) and pharmacists (44%). Inquiries type included dosage/administration (34.2%), drug interaction (12.8%) and pregnancy/lactation (15.7%). Majority of inquires included adults (83%) and female patients (54.3%). GPT-4 had 64.3% completely accurate responses, comparable to human pharmacists. GPT-4 and human pharmacists provided sufficiently detailed responses, with GPT-4 offering additional relevant details. Both GPT-4 and human pharmacists delivered 95% safe responses; however, GPT-4 provided proactive risk mitigation information in 70% of the instances, whereas similar information was included in 25.7% of human pharmacists' responses. Conclusion: Our study showcased GPT-4's potential in addressing drug-related inquiries accurately and safely, comparable to human pharmacists. Current GPT-4-based chatbots could support healthcare professionals and foster global health improvements.

Trends in antidote utilization at a tertiary care hospital in Saudi Arabia: A 6-year retrospective study.

Antidote stocking has been described in several studies from many countries to be problematic and constantly insufficient. During our institution's previous experience with a medication event that resulted from lack of antidote stocking, we initiated a review of all our antidotes and realized the lack of data on utilization in the literature that would help us in planning for our stocks. Therefore, we conducted this retrospective review of antidotes utilized at a large tertiary care hospital over a period of 6 years. The paper describes the types of antidotes and toxins involved, together with important patient characteristics and antidote utilization data that can be useful to other healthcare institutions in planning for their antidote stocks.

The role of drug information centers to improve medication safety in Saudi Arabia - a study from healthcare professionals' perspective.

Background and objective: The primary function of the Drug Information Center (DIC) is to provide drug-related information to healthcare professionals. The purpose of this research was to assess the use of drug information centers by health care the professionals to improve medication safety in Saudi Arabia. Methods: A retrospective study was carried out at King Khalid University Hospital's drug and poison information center (DPIC). During the study period, requests received by drug information specialists were saved in the DPIC questions' bank. Patients' demographic, type of drug information request, caller information, number of references used, medications, class of medication, medication error type and subclass were assessed and analyzed using descriptive analysis. Medication error types were captured based on nature of questions. Results: A total of 243 drug information inquiries were assessed. Most of the inquiries were about adult population (n = 168; 69.1%). Most drug information inquiries were received from pharmacists (n = 117; 48.1%), followed by physicians (n = 94; 38.7%), then nurses (n = 23; 9.5%). Prescribing error were the most type of medication error prevented by drug information specialists (n = 214; 88.1%) followed by dispensing errors (n = 11; 4.5%). Approximately half of the medication errors in this study were near-misses (n = 110; 45.3%), followed by potential near misses (n = 84; 34.6%). Only, (n = 49; 20.2%) were identified as errors. Conclusion: This study highlights the role of drug information specialists in providing evidence-based information and helps in preventing possible medication errors which will enhance the safety of the services provided to the patients.

Optimizing Gentamicin Dosing in Pediatrics Using Monte Carlo Simulations.

Gentamicin is known to have concentration-dependent bactericidal activity, and its nephrotoxic effect is well described. We developed a population pharmacokinetic/pharmacodynamic model to optimize gentamicin dosing in pediatrics. Data were retrospectively collected for pediatric patients 1 month to 12 years of age, admitted to general pediatric wards or intensive care units and received gentamicin for suspected or proven Gram-negative infections at King Saud University Medical City, Riyadh, Saudi Arabia. A total of 306 gentamicin peak and trough concentrations sets from 107 patients were analyzed with mean (±standard deviation) patient age and weight of 4.5 ± 3.5 years and 16.7 ± 10.8 kg, respectively. Gentamicin pharmacokinetics were adequately described with a one compartment system (R = 0.82, bias = 1.75% and precision = 88% for population predictions and R = 0.94, bias = 5% and precision = 29% for individual predictions). The gentamicin pharmacokinetic parameters were as follows: volume of distribution = 8.9 L, total body clearance = 2.8 L/h for a 20-kg patient. Monte Carlo simulations showed that doses of 5-6 mg/kg/dose once daily are adequate only to treat infections with Gram-negative organisms having minimal inhibitory concentration less than 1 µg/mL. While, at minimal inhibitory concentration of 1 µg/mL, higher doses (7-8 mg/kg/dose once daily) are needed to maximize the efficacy of gentamicin. However, at minimal inhibitory concentration of 2 µg/mL, even a 10 mg/kg dose showed poor target attainment (52%). The finding of this study highlights the need to reevaluate the current breakpoints of gentamicin and also to assess the safety of higher doses of gentamicin in pediatrics.

Optimizing Amikacin Dosage in Pediatrics Based on Population Pharmacokinetic/Pharmacodynamic Modeling.

OBJECTIVE: Our objective was to determine the population pharmacokinetic parameters of amikacin in pediatric patients to contribute to the future development of a revised optimum dose and population-specific dosing regimens. METHODS: We performed a retrospective chart review in non-critical pediatric patients (aged 1-12 years) who received amikacin for suspected or proven Gram-negative infection at a university hospital. The population pharmacokinetic models were developed using Monolix 4.4. Pharmacokinetic/pharmacodynamic (PK/PD) simulations were performed to explore the ability of different dosage regimens to achieve the pharmacodynamic targets. RESULTS: The analysis included 134 amikacin plasma concentrations from 67 patients with a mean ± standard deviation age of 4.1 ± 3.9 years and bodyweight of 15 ± 8.4 kg. The patients received an amikacin total daily dose (TDD) of 23 ± 7.3 mg/kg, which resulted in peak and trough concentrations of 20.65 ± 7.6 and 2.4 ± 1.7 mg/l, respectively. The estimated pharmacokinetic parameters for amikacin were 1.2 l/h and 6.5 l for total body clearance (CL) and the volume of distribution (V), respectively. Dosing simulations showed that the standard dosing regimen (15 mg/kg/day) of amikacin achieved the PK/PD target of peak serum concentration (Cpeak)/minimum inhibitory concentration (MIC) ≥ 8 for an MIC of 2 mg/l; higher doses were required to achieve higher MIC values. CONCLUSION: The simulation results indicated that amikacin 20 mg/kg once daily provided a higher probability of target attainment with lower toxicity than dosing three times daily. In addition, combination therapy is recommended for pathogens with an MIC of ≥ 8 mg/l.