ABSTRACT
Background: There is no consistent framework for patient-centric drug product design, despite the common understanding that drug product acceptability and preferences influence adherence and, therefore, drug product effectiveness. The aim of this review was to assess current understanding of patient acceptability and preferences for solid oral dosage form (SODF) drug product attributes, and the potential impact of these attributes on patient behaviors and outcomes. Patients and Methods: A scoping review was conducted. Embase, Ovid MEDLINE®, and PubMed® were searched for full-text articles published between January 2013 and May 2023. Following screening and assessment against predefined inclusion criteria, data were analyzed thematically. Results: Nineteen studies were included. Four overarching domains of drug product attributes were identified and summarized in a framework: appearance, swallowability, palatability, and handling. Each domain was informed by specific drug product attributes: texture, form, size, shape, color, marking, taste, mouthfeel, and smell. The most frequently studied domains were swallowability and appearance, while the most studied attributes were size, shape, and texture. Smell, marking, and mouthfeel were the least studied attributes. Texture intersected all domains, while form, shape, and size intersected appearance, swallowability, and handling. Swallowability and size appeared to be the key domain and attribute, respectively, to consider when designing drug products. Few studies explored the impact of drug product attributes on behaviors and outcomes. Conclusion: While existing studies of drug product attributes have focused on appearance and swallowability, this review highlighted the importance of two less well-understood domains-palatability and handling-in understanding patients' acceptability and preferences for SODF drug products. The framework provides a tool to facilitate patient-centric design of drug products, organizing and categorizing physical drug product attributes into four overarching domains (appearance, swallowability, palatability, and handling), encouraging researchers to comprehensively assess the impact of drug product attributes on patient acceptability, preferences, and outcomes.
Medicines come in a variety of types and forms. These include tablets and capsules. Factors, such as the size and shape of tablets, can affect how people take medicines. However, patients are rarely involved in designing the medicines that they take. In this study, researchers summarized 19 studies published between 2013 and 2023. They wanted to understand how different factors, like size and shape, affect patients' preferences, ability, and willingness to take medicines. Researchers focused on the "physical" aspects of medicines and found 4 common themes: 1) what they look like (appearance), 2) how easy they are to swallow (swallowability), 3) how they taste and feel in the mouth (palatability), and 4) how easy they are to handle (handling). Eight factors were also found: color, markings, shape, size, smell, taste, texture, and how a medicine feels in the mouth (mouthfeel). Most studies focused on what medicines look like and how easy they are to swallow. The factors that researchers mostly looked at were the size, shape, and texture of medicines. The design of medicines can impact patients of different ages, though there may be specific needs for certain groups of patients, including children, older adults, and people with certain diseases. Patient input should become a part of future medicines design to ensure their acceptability.
ABSTRACT
Aging-related transcriptome changes in various regions of the healthy human brain have been explored in previous works, however, a study to develop prediction models for age based on the expression levels of specific panels of transcripts is lacking. Moreover, studies that have assessed sexually dimorphic gene activities in the aging brain have reported discrepant results, suggesting that additional studies would be advantageous. The prefrontal cortex (PFC) region was previously shown to have a particularly large number of significant transcriptome alterations during healthy aging in a study that compared different regions in the human brain. We harmonized neuropathologically normal PFC transcriptome datasets obtained from the Gene Expression Omnibus (GEO) repository, ranging in age from 21 to 105 years, and found a large number of differentially regulated transcripts in the old and elderly, compared to young samples overall, and compared female and male-specific expression alterations. We assessed the genes that were associated with age by employing ontology, pathway, and network analyses. Furthermore, we applied various established (least absolute shrinkage and selection operator (Lasso) and Elastic Net (EN)) and recent (eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM)) machine learning algorithms to develop accurate prediction models for chronological age and validated them. Studies to further validate these models in other large populations and molecular studies to elucidate the potential mechanisms by which the transcripts identified may be related to aging phenotypes would be advantageous.
