Esofagitis disecante supeEsofagitis disecante superficial: dos casos de una misma entidad poco frecuente / Esophagitis dissecans superficialis: two cases of the same rare entity

La esofagitis disecante superficial (EDS) es una entidad infrecuente que se caracteriza endoscópicamente por el desprendimiento de las capas superficiales del epitelio esofágico e, histológicamente, por el aspecto bitonal del epitelio escamoso esofágico secundario a la necrosis de los estratos más superficiales. La etiología es desconocida, aunque se ha asociado con la ingesta de determinados fármacos, enfermedades autoinmunes, estasis esofágica y procedimientos endoscópicos. Presentamos dos casos: uno de ellos acontece en una mujer tras un episodio de disfagia abrupta y el segundo en un varón con comorbilidades y clínica de dolor epigástrico. La EDS es una patología que hay que considerar en su adecuado contexto clínico y endoscópico, ya que su curso es autolimitado en comparación con otras entidades de evolución tórpida o que precisan un tratamiento específico. (AU)

Esophagitis dissecans superficialis (EDS) is a rare disease characterized by sloughing of the superficial esophageal mucosa and, histologically, by the bitonal appearance of the squamous epithelium secondary to necrosis of the most superficial layers. Etiology is uncertain, however, it has been associated with some medications, autoimmune diseases, esophageal stasis and endoscopic procedures. Here, two cases are presented, one of them which appeared in a woman after an episode of dysphagia and another one which occurred to a man with comorbidities and epigastric pain. This entity should be considered due to its self-limiting clinical course, compared to other entities with a more torpid evolution or that require more specific treatment. (AU)

Emerging opportunities of using large language models for translation between drug molecules and indications.

A drug molecule is a substance that changes an organism's mental or physical state. Every approved drug has an indication, which refers to the therapeutic use of that drug for treating a particular medical condition. While the Large Language Model (LLM), a generative Artificial Intelligence (AI) technique, has recently demonstrated effectiveness in translating between molecules and their textual descriptions, there remains a gap in research regarding their application in facilitating the translation between drug molecules and indications (which describes the disease, condition or symptoms for which the drug is used), or vice versa. Addressing this challenge could greatly benefit the drug discovery process. The capability of generating a drug from a given indication would allow for the discovery of drugs targeting specific diseases or targets and ultimately provide patients with better treatments. In this paper, we first propose a new task, the translation between drug molecules and corresponding indications, and then test existing LLMs on this new task. Specifically, we consider nine variations of the T5 LLM and evaluate them on two public datasets obtained from ChEMBL and DrugBank. Our experiments show the early results of using LLMs for this task and provide a perspective on the state-of-the-art. We also emphasize the current limitations and discuss future work that has the potential to improve the performance on this task. The creation of molecules from indications, or vice versa, will allow for more efficient targeting of diseases and significantly reduce the cost of drug discovery, with the potential to revolutionize the field of drug discovery in the era of generative AI.

Insights into Inhalation Drug Disposition: The Roles of Pulmonary Drug-Metabolizing Enzymes and Transporters.

The past five decades have witnessed remarkable advancements in the field of inhaled medicines targeting the lungs for respiratory disease treatment. As a non-invasive drug delivery route, inhalation therapy offers numerous benefits to respiratory patients, including rapid and targeted exposure at specific sites, quick onset of action, bypassing first-pass metabolism, and beyond. Understanding the characteristics of pulmonary drug transporters and metabolizing enzymes is crucial for comprehending efficient drug exposure and clearance processes within the lungs. These processes are intricately linked to both local and systemic pharmacokinetics and pharmacodynamics of drugs. This review aims to provide a comprehensive overview of the literature on lung transporters and metabolizing enzymes while exploring their roles in exogenous and endogenous substance disposition. Additionally, we identify and discuss the principal challenges in this area of research, providing a foundation for future investigations aimed at optimizing inhaled drug administration. Moving forward, it is imperative that future research endeavors to focus on refining and validating in vitro and ex vivo models to more accurately mimic the human respiratory system. Such advancements will enhance our understanding of drug processing in different pathological states and facilitate the discovery of novel approaches for investigating lung-specific drug transporters and metabolizing enzymes. This deeper insight will be crucial in developing more effective and targeted therapies for respiratory diseases, ultimately leading to improved patient outcomes.

Advances in Nanotechnology for Enhancing the Solubility and Bioavailability of Poorly Soluble Drugs.

This manuscript offers a comprehensive overview of nanotechnology's impact on the solubility and bioavailability of poorly soluble drugs, with a focus on BCS Class II and IV drugs. We explore various nanoscale drug delivery systems (NDDSs), including lipid-based, polymer-based, nanoemulsions, nanogels, and inorganic carriers. These systems offer improved drug efficacy, targeting, and reduced side effects. Emphasizing the crucial role of nanoparticle size and surface modifications, the review discusses the advancements in NDDSs for enhanced therapeutic outcomes. Challenges such as production cost and safety are acknowledged, yet the potential of NDDSs in transforming drug delivery methods is highlighted. This contribution underscores the importance of nanotechnology in pharmaceutical engineering, suggesting it as a significant advancement for medical applications and patient care.

Impact of Obesity on Hepatic Drug Clearance: What are the Influential Variables?

Drug clearance in obese subjects varies widely among different drugs and across subjects with different severity of obesity. This study investigates correlations between plasma clearance (CLp) and drug- and patient-related characteristics in obese subjects, and evaluates the systematic accuracy of common weight-based dosing methods. A physiologically-based pharmacokinetic (PBPK) modeling approach that uses recent information on obesity-related changes in physiology was used to simulate CLp for a normal-weight subject (body mass index [BMI] = 20) and subjects with various severities of obesity (BMI 25-60) for hypothetical hepatically cleared drugs with a wide range of properties. Influential variables for CLp change were investigated. For each drug and obese subject, the exponent that yields perfect allometric scaling of CLp from normal-weight subjects was assessed. Among all variables, BMI and relative changes in enzyme activity resulting from obesity proved highly correlated with obesity-related CLp changes. Drugs bound to α1-acid glycoprotein (AAG) had lower CLp changes compared to drugs bound to human serum albumin (HSA). Lower extraction ratios (ER) corresponded to higher CLp changes compared to higher ER. The allometric exponent for perfect scaling ranged from -3.84 to 3.34 illustrating that none of the scaling methods performed well in all situations. While all three dosing methods are generally systematically accurate for drugs with unchanged or up to 50% increased enzyme activity in subjects with a BMI below 30 kg/m2, in any of the other cases, information on the different drug properties and severity of obesity is required to select an appropriate dosing method for individuals with obesity.

Quality by Design Perspective for Designing Foam-based Formulation: Current State of Art.

Foam-based delivery systems contain one or more active ingredients and dispersed solid or liquid components that transform into gaseous form when the valve is actuated. Foams are an attractive and effective delivery approach for medical, cosmetic, and pharmaceutical uses. The foams-based delivery systems are gaining attention due to ease of application as they allow direct application onto the affected area of skin without using any applicator or finger, hence increasing the compliance and satisfaction of the patients. In order to develop foam-based delivery systems with desired qualities, it is vital to understand which type of material and process parameters impact the quality features of foams and which methodologies may be utilized to investigate foams. For this purpose, Quality-by-Design (QbD) approach is used. It aids in achieving quality-based development during the development process by employing the QbD concept. The critical material attributes (CMAs) and critical process parameters (CPPs) were discovered through the first risk assessment to ensure the requisite critical quality attributes (CQAs). During the initial risk assessment, the high-risk CQAs were identified, which affect the foam characteristics. In this review, the authors discussed the various CMAs, CPPs, CQAs, and risk factors associated in order to develop an ideal foam-based formulation with desired characteristics.

Unused, expired pharmaceuticals and their disposal practices among the general public in Burdur-Türkiye: a cross-sectional study.

BACKGROUND: Unused pharmaceuticals are currently a public health problem. This study aimed to identify unused pharmaceuticals, research practices about the disposal methods, classify the medicines according to Anatomical Therapeutic Chemical codes (ATC) and, to determine the number of unused medicines. METHODS: The study was designed as a cross-sectional study. Data were collected between April and August 2023 in Burdur-Türkiye by non-probability sampling technique (convenience method). Pharmaceuticals were classified according to ATC. Statistical Package for Social Science SPSS (V.24) package program was used for data analysis. RESULTS: A total of 1120 people, 1005 in the first sample group and 115 in the second sample group, participated in the study. Findings of first sample group: A total of 4097 boxes of unused pharmaceuticals (4.7 ± 4.3 boxes/per capita) were detected. It was found that pharmaceuticals were stored in areas such as kitchens (59.1%) and refrigerators (38.6%), the reason for keeping them was reuse (41%), and the disposal practice was household garbage (81%). Paracetamol (648 boxes), Other cold preparation (303 boxes), Dexketoprofen (239 boxes), Diclofenac (218 boxes), Amoxicillin and beta-lactamase inhibitor (190 boxes) were found to be the most frequently unused pharmaceuticals. Using the unused medicines at home without consulting a physician was 94.1% (self-medication). Findings of second sample group: Of the 6189 dosage forms in 265 boxes pharmaceutical, 3132(50.6%) dosage forms were used and 3057(49.4%) were found to be unused. CONCLUSION: There is a significant amount and number of unused medicines in households, and self-medication is common. Medicines are not properly disposed of and some of them expire. Public information is needed. A "drug take-back system" for unused medicines can be useful in solving this problem.

Selective detection of azelnidipine in pharmaceuticals via carbon dot mediated spectrofluorimetric method: A green approach.

A spectrofluorimetric method using fluorescent carbon dots (CDs) was developed for the selective detection of azelnidipine (AZEL) pharmaceutical in the presence of other drugs. In this study, N-doped CDs (N-CDs) were synthesized through a single-step hydrothermal process, using citric acid and urea as precursor materials. The prepared N-CDs showed a highly intense blue fluorescence emission at 447 nm, with a photoluminescence quantum yield of ~21.15% and a fluorescence lifetime of 0.47 ns. The N-CDs showed selective fluorescence quenching in the presence of all three antihypertensive drugs, which was used as a successful detection platform for the analysis of AZEL. The photophysical properties, UV-vis light absorbance, fluorescence emission, and lifetime measurements support the interaction between N-CDs and AZEL, leading to fluorescence quenching of N-CDs as a result of ground-state complex formation followed by a static fluorescence quenching phenomenon. The detection platform showed linearity in the range 10-200 µg/ml (R2 = 0.9837). The developed method was effectively utilized for the quantitative analysis of AZEL in commercially available pharmaceutical tablets, yielding results that closely align with those obtained from the standard method (UV spectroscopy). With a score of 0.76 on the 'Analytical GREEnness (AGREE)' scale, the developed analytical method, incorporating 12 distinct green analytical chemistry components, stands out as an important technique for estimating AZEL.

In-depth Mechanism, Challenges, and Opportunities of Delivering Therapeutics in Brain Using Intranasal Route.

Central nervous system-related disorders have become a continuing threat to human life and the current statistic indicates an increasing trend of such disorders worldwide. The primary therapeutic challenge, despite the availability of therapies for these disorders, is to sustain the drug's effective concentration in the brain while limiting its accumulation in non-targeted areas. This is attributed to the presence of the blood-brain barrier and first-pass metabolism which limits the transportation of drugs to the brain irrespective of popular and conventional routes of drug administration. Therefore, there is a demand to practice alternative routes for predictable drug delivery using advanced drug delivery carriers to overcome the said obstacles. Recent research attracted attention to intranasal-to-brain drug delivery for promising targeting therapeutics in the brain. This review emphasizes the mechanisms to deliver therapeutics via different pathways for nose-to-brain drug delivery with recent advancements in delivery and formulation aspects. Concurrently, for the benefit of future studies, the difficulties in administering medications by intranasal pathway have also been highlighted.

A sustainable sensitive spectrofluorimetric approach for the determination of the multipotent protein lactoferrin in different pharmaceuticals and infant milk formula: Compliance with greenness metrics.

The current study presents the first spectrofluorimetric approach for the estimation of lactoferrin, depending on the measurement of its native fluorescence at 337 nm after excitation at 230 nm, without the need for any hazardous chemicals or reagents. It was found that the fluorescence intensity versus concentration calibration plot was linear over the concentration range of 0.1-10.0 µg/mL with quantitation and detection limits of 0.082 and 0.027 µg/mL, respectively. The method was accordingly validated according to the ICH recommendations. The developed method was applied for the estimation of lactoferrin in different dosage forms, including capsules and sachets with high percent recoveries (97.84-102.53) and low %RSD values (<1.95). Lactoferrin is one of the key nutrients in milk powder and a significant nutritional fortifier. In order to assess the quality of milk powder, it is essential to rapidly and accurately quantify the lactoferrin content of the product. Therefore, the presented study was successfully applied for the selective estimation of lactoferrin in milk powder with acceptable percent recoveries (96.45-104.92) and %RSD values (≤3.607). Finally, the green profile of the method was estimated using two assessment tools: Green Analytical Procedure Index (GAPI) and Analytical GREEnness (AGREE), which demonstrated its excellent greenness.

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.

For the occurrence of PPCPs from source to tap: A novel approach modified in terms of sample preservation and SPE cartridge to monitor PPCPs in our water supply.

BACKGROUND: The ongoing infusion of pharmaceutical and personal care products (PPCPs) into ecosystems sustains a perpetual life cycle and leads to multi-generational exposures. Limited understanding of their environmental impact and their intrinsic ability to induce physiological effect in humans, even at low doses, pose great risks to human health. Few scholarly works have conducted systematic research into the occurrence of PPCPs within potable water systems. Concurrently, the associated monitoring techniques have not been comprehensively examined with regards to the specific nature of drinking water, namely whether the significant presence of disinfectants may influence the detection of PPCPs. RESULTS: A modified approach in terms of detailed investigation of sample preservation and optimization of an in-lab fabricated solid phase extraction (SPE) cartridge filled with DVB-VP and PS-DVB sorbent was proposed. Favorable methodological parameters were achieved, with correlation coefficients spanning from 0.9866 to 0.9998. The LODs of the PPCPs fluctuated from 0.001 to 2 µg L-1, while the LOQs varied from 0.002 to 5 µg L-1. The analysis of spiked samples disclosed a methodological precision of 2.31-9.86 % and a recovery of 52.4-119 %. We utilized the established method for analyzing 14 water samples of three categories (source water, finished water and tap water) from five centralized water supply plants. A total of 24 categories encompassing 72 PPCPs were detected, with the concentrations of PPCPs manifested a marked decrease from source water to finished water and finally to tap water. SIGNIFICANCE: Our research meticulously examined the enhancement and purification effects of widely used commercial SPE cartridges and suggested the use of in-lab fabricated SPE cartridges packed with DVB-VP and PS-DVB adsorbents. We also conducted a systematic evaluation of the need to incorporate ascorbic acid and sodium thiosulfate as preservatives for PPCP measurement, in consideration of the unique characteristics of drinking water matrices, specifically, the significant concentration levels of disinfectants. Furthermore, the proposed method was effectively employed to study the presence of PPCPs in source water, finished water, and tap water collected from centralized water supply plants.

Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each Tissue.

Artificial intelligence is expected to help identify excellent candidates in drug discovery. However, we face a lack of data, as it is time-consuming and expensive to acquire raw data perfectly for many compounds. Hence, we tried to develop a novel quantitative structure-activity relationship (QSAR) method to predict a parameter more precisely from an incomplete data set via optimizing data handling by making use of predicted explanatory variables. As a case study we focused on the tissue-to-plasma partition coefficient (Kp), which is an important parameter for understanding drug distribution in tissues and building the physiologically based pharmacokinetic model and is a representative of small and sparse data sets. In this study, we predicted the Kp values of 119 compounds in nine tissues (adipose, brain, gut, heart, kidney, liver, lung, muscle, and skin), although some of these were not available. To fill the missing values in Kp for each tissue, first we predicted those Kp values by the nonmissing data set using a random forest (RF) model with in vitro parameters (log P, fu, Drug Class, and fi) like a classical prediction by a QSAR model. Next, to predict the tissue-specific Kp values in a test data set, we constructed a second RF model with not only in vitro parameters but also the Kp values of other tissues (i.e., other than target tissues) predicted by the first RF model as explanatory variables. Furthermore, we tested all possible combinations of explanatory variables and selected the model with the highest predictability from the test data set as the final model. The evaluation of Kp prediction accuracy based on the root-mean-square error and R2 value revealed that the proposed models outperformed other machine learning methods such as the conventional RF and message-passing neural networks. Significant improvements were observed in the Kp values of adipose tissue, brain, kidney, liver, and skin. These improvements indicated that the Kp information on other tissues can be used to predict the same for a specific tissue. Additionally, we found a novel relationship between each tissue by evaluating all combinations of explanatory variables. In conclusion, we developed a novel RF model to predict Kp values. We hope that this method will be applied to various problems in the field of experimental biology which often contains missing values in the near future.

Revisiting drug-protein interaction prediction: a novel global-local perspective.

MOTIVATION: Accurate inference of potential drug-protein interactions (DPIs) aids in understanding drug mechanisms and developing novel treatments. Existing deep learning models, however, struggle with accurate node representation in DPI prediction, limiting their performance. RESULTS: We propose a new computational framework that integrates global and local features of nodes in the drug-protein bipartite graph for efficient DPI inference. Initially, we employ pre-trained models to acquire fundamental knowledge of drugs and proteins and to determine their initial features. Subsequently, the MinHash and HyperLogLog algorithms are utilized to estimate the similarity and set cardinality between drug and protein subgraphs, serving as their local features. Then, an energy-constrained diffusion mechanism is integrated into the transformer architecture, capturing interdependencies between nodes in the drug-protein bipartite graph and extracting their global features. Finally, we fuse the local and global features of nodes and employ multilayer perceptrons to predict the likelihood of potential DPIs. A comprehensive and precise node representation guarantees efficient prediction of unknown DPIs by the model. Various experiments validate the accuracy and reliability of our model, with molecular docking results revealing its capability to identify potential DPIs not present in existing databases. This approach is expected to offer valuable insights for furthering drug repurposing and personalized medicine research. AVAILABILITY AND IMPLEMENTATION: Our code and data are accessible at: https://github.com/ZZCrazy00/DPI.

3D printing processes in precise drug delivery for personalized medicine.

With the advent of personalized medicine, the drug delivery system will be changed significantly. The development of personalized medicine needs the support of many technologies, among which three-dimensional printing (3DP) technology is a novel formulation-preparing process that creates 3D objects by depositing printing materials layer-by-layer based on the computer-aided design method. Compared with traditional pharmaceutical processes, 3DP produces complex drug combinations, personalized dosage, and flexible shape and structure of dosage forms (DFs) on demand. In the future, personalized 3DP drugs may supplement and even replace their traditional counterpart. We systematically introduce the applications of 3DP technologies in the pharmaceutical industry and summarize the virtues and shortcomings of each technique. The release behaviors and control mechanisms of the pharmaceutical DFs with desired structures are also analyzed. Finally, the benefits, challenges, and prospects of 3DP technology to the pharmaceutical industry are discussed.

The fate of pharmaceuticals and personal care products (PPCPs) in sewer sediments:Adsorption triggering resistance gene proliferation.

In recent years, large quantities of pharmaceuticals and personal care products (PPCPs) have been discharged into sewers, while the mechanisms of PPCPs enrichment in sewer sediments have rarely been revealed. In this study, three PPCPs (tetracycline, sulfamethoxazole, and triclocarban) were added consecutively over a 90-day experimental period to reveal the mechanisms of PPCPs enrichment and the transmission of resistance genes in sewer sediments. The results showed that tetracycline (TC) and triclocarban (TCC) have higher adsorption concentration in sediments compared to sulfamethoxazole (SMX). The absolute abundance of Tets and suls genes increased in sediments under PPCPs pressure. The increase in secretion of extracellular polymeric substances (EPS) and the loosening of the structure exposed a large number of hydrophobic functional groups, which promoted the adsorption of PPCPs. The absolute abundance of antibiotic resistance genes (ARGs), EPS and the content of PPCPs in sediments exhibited significant correlations. The enrichment of PPCPs in sediments was attributed to the accumulation of EPS, which led to the proliferation of ARGs. These findings contributed to further understanding of the fate of PPCPs in sewer sediments and opened a new perspective for consideration of controlling the proliferation of resistance genes.

Towards Greener and More Cost-efficient Biosynthesis of Pharmaceuticals and Fragrance Molecules.

Enzymes are natural catalysts which are gaining momentum in chemical synthesis due to their exquisiteselectivity and their biodegradability. However, the cost-efficiency and the sustainability of the overall biocatalytic process must be enhanced to unlock completely the potential of enzymes for industrial applications. To reach this goal, enzyme immobilization and the integration into continuous flow reactors have been the cornerstone of our research. We showed key examples of the advantages of those tools for the biosynthesis of antivirals, anticancer drugs, and valuable fragrance molecules. By combining new strategies to immobilize biocatalysts, innovative bioengineering approaches, and process development, the performance of the reactions could be boosted up to 100-fold.

Green electrospun Janus membrane of polyether block amide (PEBA) doped with hierarchical magnesium hydrogen phosphate for the removal of pharmaceuticals and personal care products.

It has been a challenge to prepared polyether block amide (PEBA) fibrous membrane via solution electrospinning. The only few reported methods though involved hazardous solvents and surfactants which were against the principle of green chemistry. In this work, uniform fibrous membrane of PEBA was successfully fabricated by solution electrospinning with a bio-based solvent dihydrolevoglucosenone (Cyrene). To further improve the mechanical strength and adsorption performance of the PEBA membrane, a hierarchical magnesium hydrogen phosphate (MgHPO4·1.2H2O, MHP) was synthesized to blend evenly into the PEBA matrix. A Janus MHP/PEBA membrane with one side of hydrophobic surface and the other side of hydrophilic surface was subsequently prepared, which exhibited fast adsorption, high capacity, good selectivity and reusability towards ibuprofen, acetaminophen, carbamazepine and triclosan. In addition, the Janus membrane showed high removal efficiency of the above contaminants in secondary wastewater effluent with good long term stability. It demonstrated that this Janus MHP/PEBA membrane had a good potential in practical wastewater treatment.

Expert survey on real-world data utilization and real-world evidence generation for regulatory decision-making in drug lifecycle in Korea.

As the importance of utilizing real-world data (RWD)/real-world evidence (RWE) for supporting regulatory scientific decision-making continues to grow, experiences and inputs from experts become crucial for developing a systematic and practice-oriented plan for the use of fit-for-purpose RWD/RWE. This study aimed to survey relevant experts from government agencies, industries, and academia to identify prerequisites for the drug life cycle in Korea. The questionnaire comprised the following: (A) the definition and categories of RWD/RWE, (B) the suitability and feasibility of using RWD/RWE at each authorization stage by the types of RWD, and (C) the challenges and solutions for the use of RWD/RWE. A total of 46 respondents completed the online survey, with 89.1% of them having prior experience with RWD/RWE usage. A majority of respondents agreed that RWD can be obtained from various sources. Among these sources, the registry was the most suitable source. It is suitable to compensate for the limitations of randomized control trials and ensure quality in data collection. Though there was consensus among the respondents for the use of RWD/RWE in post-marketing surveillance, the use of such data in new drug application (NDA) was disagreeable. Respondents considered it necessary to write a protocol in advance for RWD collection and RWE generation, for all RWD types. In conclusion, this study examined the perceptions of experts for RWD/RWE use at each approval stage of drugs. The results suggest that guidelines for the fit-for-purpose use of RWD/RWE should be developed via careful deliberation among experts in the future.