Thai Bulletin of Pharmaceutical Sciences

HEALTH LITERACY AND THE USES OF COMPLEMENTARY AND ALTERNATIVE MEDICINES AMONG PATIENTS WITH NON-COMMUNICABLE DISEASES

Chutima Thanapancharoen, Burin T.Sriwong , Waranee Bunchuailua — Mon, 24 Mar 2025 00:00:00 +0700

This study examined the association between health literacy (being able to access, understand, and make decisions using information related to health care) and the use of some complementary and alternative medicines (CAM) among patients with chronic non-communicable diseases (NCDs). A cross-sectional study was conducted among 261 patients receiving care at Nakhon Chai Si District Hospital, Nakhon Pathom Province, Thailand. Questionnaires were used during structured interviews from which the data was collected and analyzed using descriptive statistics and logistic regression. The findings revealed that the majority of patients with NCDs were female (61.7%) whose mean age was 56.3 ± 0.9 years. The most common comorbidities were hyperlipidemia, hypertension, and diabetes. Overall, 65.9% of the participants demonstrated an insufficient understanding of health literacy. Most patients (82.4%) reported using at least one type of CAM, with 48.2% using dietary supplements and 22.7% using herbal medicines. CAM was primarily used for disease management (43.4%), but was discontinued by 45.4% of the users due to adverse effects. Health literacy (OR=4.4, 95% CI 1.1-18.1, p=0.04) and education levels (OR=5.6, 95% CI 1.1-27.9, p=0.04) were significantly associated with CAM use. In conclusion, health literacy is a critical skill that enables NCD patients to make informed decisions in managing their illnesses and with using CAM appropriately. Therefore, enhancing health literacy is essential for ensuring effective, safe, and satisfactory patient care.

EVALUATION OF OPHTHALMIC DRUG REFILL PROJECT IN A HOSPITAL

Rapee Aumsurbcher, Surasit Lochidamnuay — Tue, 25 Feb 2025 00:00:00 +0700

This study evaluated the ophthalmic drug refill project at a hospital for patients with universal health coverage by using the CIPP Model (Context, Input, Process, Product Model) to collect data from 11 hospital officers and 64 patient participants by purposive sampling. Data was collected through interviews with hospital officers from December 2022 to June 2023 and from patient questionnaires from May 2022 to November 2022. The results were analyzed using descriptive statistics and content analysis. The results showed that the drug refill project’s objective is to reduce the hospital’s financial burden on patients’ excessive treatment costs, which are not reimbursed by referral hospitals. Also, support is lacking in regard to a project budget, hospital personnel, a patient database system, troubleshooting guidelines, and an evaluation system. Furthermore, the patient selection criteria was deemed inappropriate and patients expressed dissatisfaction over the inconvenience of traveling. Most hospital personnel agreed that the drug refill project has not been successful in resolving financial problems. Therefore, guidelines and policies for the drug refill project should be established. Furthermore, it will be necessary to develop in-patient support for an online rights verification system, a mail-order drug delivery system, follow-up services for ophthalmic diseases, remote consulting services from pharmacists at no additional cost, and a drug refill service at an accredited pharmacy.

APPLICATION OF CHATGPT AND GOOGLE COLAB TO CREATE AN ALGORITHM FOR GROUPING AND ROUTING OPTIMIZATION FOR DRUGSTORE INSPECTION: A CASE STUDY OF THE PATHUM THANI PROVINCIAL PUBLIC HEALTH OFFICE

Nuttakan Teeratanun, Perayot Pamonsinlapatham — Wed, 05 Mar 2025 00:00:00 +0700

Evaluation of drugstore inspections is a task under the supervision of the Provincial Health Office to ensure the quality and standards of pharmaceutical services. The current route planning initially relies on experienced personnel familiar with the area. Therefore, improving or enhancing the efficiency of this process is a significant challenge. This study aimed to develop a method by creating an algorithm using ChatGPT and calculating it through Google Colab to perform clustering and route optimization. The performance of the current expert route planning method was compared with 3 computer-based algorithms. Once the routes were optimized, they were calculated through Google Maps to study the distance and travel time required to visit all locations. This research is a developmental evaluation, using geographic coordinates of the current drugstores and computing them with 3 algorithms, comparing them to expert route planning. The study found that the expert method, which clustered 145 drugstores into 41 groups, resulted in a total distance of 2,755.01 km and a total time of 4,962 minutes. When comparing this with the three algorithms, they produced 21 clusters with distances of 1,313 km, 1,340 km, and 1,359 km, respectively, with reduced travel times. This led to a reduction of 50% in both distance and time. For the case of route sequencing with experts in 41 groups, using the three algorithms yielded different results within each cluster, but the total distance and time remained relatively consistent. The development and testing of the three algorithms can be used for clustering or finding travel sequences, offering a potential future tool to enhance the efficiency of route planning for the inspection of drugstore locations or other similar evaluations. It may be applied for planning in many regional, district, or country-level areas, making work more efficient.

CARBON DOTS FOR ANTIBACTERIAL PHOTOTHERAPY

Tue, 21 Jan 2025 00:00:00 +0700

Infectious diseases are a significant concern for public health systems in Thailand and worldwide, especially the issue of antibiotic resistance in inhibiting bacterial growth. At present, nanoparticles are being applied as antibacterial agents because they can enhance efficacy through photo-stimulation, are non-damaging to normal cells or tissues, have low toxicity, and do not contribute to drug resistance. Additionally, they help reduce side effects compared to traditional antibiotic treatment methods. Carbon dots are one of the nanoparticles that can be applied as antibacterial agents. They have advantages over other types of nanoparticles, including their unique optical properties, fluorescence characteristics, absorption of light in both ultraviolet and visible ranges, and crucial characteristics for phototherapy. Moreover, they show biocompatibility, low toxicity, water dispersion, ease of synthesis, rapid stability, and capability of functionalization on the surface. This article compiles general information, synthesis methods, mechanisms of bacterial inhibition, and principles of antibacterial activity enhancement by antimicrobial phototherapy of carbon dots.

THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL TECHNOLOGY AND ADVANCEMENTS IN THE PHARMACEUTICAL INDUSTRY 4.0

Phuvamin Suriyaamporn, Warisada Sila-on, Teeratas Kansom, Praneet Opanasopit — Fri, 24 Jan 2025 00:00:00 +0700

Currently, artificial intelligence (AI), which aids in decision making in complex situations, is gaining increasing attention in various fields, particularly in pharmaceutical technology. In numerous research and development endeavors, computational technologies have demonstrated their usefulness in various aspects of pharmaceutical technology. Examples include the discovery of new drugs, personalized drug manufacturing, prediction of drug formulations, studying the interaction of drugs with bacteria, absorption of drugs in the digestive system, and the drug manufacturing process. These AI systems can enhance efficiency, accuracy, manage complex data, and promote the discovery of new methods within minutes using advanced model-building techniques. Furthermore, these AI systems have several advantages compared to traditional statistical decision-making methods, as they can perceive patterns from complex datasets and develop models driven by algorithms using diverse sets of instructions, allowing for appropriate predictions based on defined-feature sets. This article also discusses anticipated future trends of Industry 4.0 (also known as the Fourth Industrial Revolution) in the pharmaceutical industry. Additionally, ethical considerations and legal implications related to incorporating AI in pharmaceutical technology are discussed. Therefore, this article provides a fresh perspective for pharmacists, experts, and others on the current status of utilizing AI and Industry 4.0 in pharmaceutical technology.