Can in vitro/in silico tools improve colonic concentration estimations for oral extended-release formulations? A case study with upadacitinib.

Upadacitinib, classified as a highly soluble drug, is commercially marketed as RINVOQ®, a modified-release formulation incorporating hydroxypropyl methylcellulose as a matrix system to target extended release throughout the gastrointestinal (GI) tract. Our study aimed to explore how drug release will occur throughout the GI tract using a plethora of in vitro and in silico tools. We built a Physiologically-Based Pharmacokinetic (PBPK) model in GastroPlus™ to predict the systemic concentrations of the drug when administered using in vitro dissolution profiles as input to drive luminal dissolution. A series of in vitro dissolution experiments were gathered using the USP Apparatus I, III and IV in presence of biorelevant media, simulating both fasted and fed state conditions. A key outcome from the current study was to establish an in vitro-in vivo correlation (IVIVC) between (i) the dissolution profiles obtained from the USP I, III and IV methods and (ii) the fraction absorbed of drug as deconvoluted from the plasma concentration-time profile of the drug. When linking the fraction dissolved as measured in the USP IV model, a Level A IVIVC was established. Moreover, when using the different dissolution profiles as input for PBPK modeling, it was also observed that predictions for plasma Cmax and AUC were most accurate for USP IV compared to the other models (based on predicted versus observed ratios). Furthermore, the PBPK model has the utility to extract the predicted concentrations at the level of the colon which can be of utmost interest when working with specific in vitro assays.

Poly(D,l-lactide-co-glycolide) particles are metabolised by the gut microbiome and elevate short chain fatty acids.

The production of short chain fatty acids (SCFAs) by the colonic microbiome has numerous benefits for human health, including maintenance of epithelial barrier function, suppression of colitis, and protection against carcinogenesis. Despite the therapeutic potential, there is currently no optimal approach for elevating the colonic microbiome's synthesis of SCFAs. In this study, poly(D,l-lactide-co-glycolide) (PLGA) was investigated for this application, as it was hypothesised that the colonic microbiota would metabolise PLGA to its lactate monomers, which would promote the resident microbiota's synthesis of SCFAs. Two grades of spray dried PLGA, alongside a lactate bolus control, were screened in an advanced model of the human colon, known as the M-SHIME® system. Whilst the high molecular weight (Mw) grade of PLGA was stable in the presence of the microbiota sourced from three healthy humans, the low Mw PLGA (PLGA 2) was found to be metabolised. This microbial degradation led to sustained release of lactate over 48 h and increased concentrations of the SCFAs propionate and butyrate. Further, microbial synthesis of harmful ammonium was significantly reduced compared to untreated controls. Interestingly, both types of PLGA were found to influence the composition of the luminal and mucosal microbiota in a donor-specific manner. An in vitro model of an inflamed colonic epithelium also showed the polymer to affect the expression of pro- and anti-inflammatory markers, such as interleukins 8 and 10. The findings of this study reveal PLGA's sensitivity to enzymatic metabolism in the gut, which could be harnessed for therapeutic elevation of colonic SCFAs.

Do probiotic interventions improve female unexplained infertility? A critical commentary.

Disruption of women's gut and cervicovaginal microbiota has been associated with multiple gynaecological diseases such as endometriosis, polycystic ovary syndrome, non-cyclic pelvic pain and infertility. Female infertility affects 12.6% of women worldwide; its aetiology is complex and multifactorial and can be underpinned by uterine pathologies, systemic diseases and age. In addition, a new perspective has emerged on the role of the gut and vaginal microbiomes in reproductive health. Research shows that the administration of precisely selected probiotics, often in combination with prior antibiotic treatment, may facilitate the restoration of symbiotic microbiota to increase successful conception and assisted reproductive technology outcomes. However, clarity on this issue from fuller research is currently hampered by a lack of consistency and harmonization in clinical studies: various lactobacilli and bifidobacteria species have been delivered through both the oral and vaginal routes, in different dosages, for different treatment durations. This commentary explores the intricate relationship between the microbiota in the cervicovaginal area and gut of women, exploring their potential contribution to infertility. It highlights ongoing research on the use of probiotic formulations in improving pregnancy outcomes, critically examining the divergent findings in these studies, which complicate a conclusive assessment of the efficacy of these interventions.

Electroactive Polymers for On-Demand Drug Release.

Conductive materials have played a significant role in advancing society into the digital era. Such materials are able to harness the power of electricity and are used to control many aspects of daily life. Conductive polymers (CPs) are an emerging group of polymers that possess metal-like conductivity yet retain desirable polymeric features, such as processability, mechanical properties, and biodegradability. Upon receiving an electrical stimulus, CPs can be tailored to achieve a number of responses, such as harvesting energy and stimulating tissue growth. The recent FDA approval of a CP-based material for a medical device has invigorated their research in healthcare. In drug delivery, CPs can act as electrical switches, drug release is achieved at a flick of a switch, thereby providing unprecedented control over drug release. In this review, recent developments in CP as electroactive polymers for voltage-stimuli responsive drug delivery systems are evaluated. The review demonstrates the distinct drug release profiles achieved by electroactive formulations, and both the precision and ease of stimuli response. This level of dynamism promises to yield "smart medicines" and warrants further research. The review concludes by providing an outlook on electroactive formulations in drug delivery and highlighting their integral roles in healthcare IoT.

Drug-induced orthostatic hypotension: Cluster analysis of co-prescription patterns in older people in UK primary care.

PURPOSE: Over 250 medications are reported to cause orthostatic hypotension, associated with serious adverse outcomes in older adults. Studies suggest a harmful cumulative risk of orthostatic hypotension with multiple medication use. However, there is limited evidence on the potential for harm in practice, particularly which drugs is co-prescribed and may increase risk of orthostatic hypotension. METHODS: Retrospective cohort study and cluster analysis using general practice data from IQVIA Medical Research Data (IMRD) in patients aged ≥50 contributing data between 1 January 2018 and 31 December 2018. Thirteen drug groups known to be associated with orthostatic hypotension by mechanism, were analyzed and clusters generated by sex and age-band. RESULTS: A total of 602 713 individuals aged ≥50 with 283 912 (47%) men and 318 801 (53%) women were included. The most prevalent prescriptions that might contribute to orthostatic hypotension were ACE inhibitors, calcium-channel blockers, beta-blockers, selective serotonin reuptake inhibitors and uroselective alpha-blockers. We identified distinct clusters of cardiovascular system (cardiovascular system) drugs in men and women at all ages. cardiovascular system plus psychoactive drug clusters were common in women at all ages, and in men aged ≤70. cardiovascular system plus uroselective alpha-blockers were identified in men aged ≥70. CONCLUSIONS: Distinct clusters of drugs associated with orthostatic hypotension exist in practice, which change over the life course. Our findings highlight potentially harmful drug combinations that may cause cumulative risk of orthostatic hypotension in older people. This may guide clinicians about the potential of synergistic harm and to monitor for orthostatic hypotension if using combinations of cardiovascular system drugs, cardiovascular system plus psychoactive drugs and/or alpha-blockers-particularly in patients aged ≥70 or at high-risk due to comorbidity. Future research should consider quantifying the risk of drug-induced orthostatic hypotension with such drug combinations.

Virtually Possible: Enhancing Quality Control of 3D-Printed Medicines with Machine Vision Trained on Photorealistic Images.

Three-dimensional (3D) printing is an advanced pharmaceutical manufacturing technology, and concerted efforts are underway to establish its applicability to various industries. However, for any technology to achieve widespread adoption, robustness and reliability are critical factors. Machine vision (MV), a subset of artificial intelligence (AI), has emerged as a powerful tool to replace human inspection with unprecedented speed and accuracy. Previous studies have demonstrated the potential of MV in pharmaceutical processes. However, training models using real images proves to be both costly and time consuming. In this study, we present an alternative approach, where synthetic images were used to train models to classify the quality of dosage forms. We generated 200 photorealistic virtual images that replicated 3D-printed dosage forms, where seven machine learning techniques (MLTs) were used to perform image classification. By exploring various MV pipelines, including image resizing and transformation, we achieved remarkable classification accuracies of 80.8%, 74.3%, and 75.5% for capsules, tablets, and films, respectively, for classifying stereolithography (SLA)-printed dosage forms. Additionally, we subjected the MLTs to rigorous stress tests, evaluating their scalability to classify over 3000 images and their ability to handle irrelevant images, where accuracies of 66.5% (capsules), 72.0% (tablets), and 70.9% (films) were obtained. Moreover, model confidence was also measured, and Brier scores ranged from 0.20 to 0.40. Our results demonstrate promising proof of concept that virtual images exhibit great potential for image classification of SLA-printed dosage forms. By using photorealistic virtual images, which are faster and cheaper to generate, we pave the way for accelerated, reliable, and sustainable AI model development to enhance the quality control of 3D-printed medicines.

3D printed infliximab suppositories for rectal biologic delivery.

Infliximab is a monoclonal antibody that plays an important role in the management and treatment of chronic inflammatory bowel diseases (IBD). Due to its macromolecular structure, its delivery through the oral route is challenging, limiting its administration to only via the parenteral route. The rectal route offers an alternative way for administering infliximab, allowing it to be localised at the disease site and circumventing its passage across the alimentary canal and thus, maintaining its integrity and bioactivity. Three-dimensional (3D) printing is an advanced production technology that permits the creation of dose-flexible drug products from digital designs. The current study assessed the feasibility of utilising semi-solid extrusion 3D printing for the fabrication of infliximab-loaded suppositories for the local treatment of IBD. Various printing inks composed of Gelucire® (48/16 or 44/14) mixed with coconut oil and/or purified water were investigated. It was shown that following reconstitution in water, the infliximab solution can be directly incorporated into the printing ink of Gelucire® 48/16 and can withstand the extrusion process, resulting in well-defined suppositories. Since water content and temperature are critical for safeguarding infliximab's potency, the effect of changing the composition of the printing inks and printing parameters on infliximab's biologic efficiency was evaluated by measuring its binding capacity (i.e., the amount of infliximab that actively binds to its antigen to exert an effect). Despite drug loading assays showing that infliximab remains intact following printing, it was found that the incorporation of water in isolation results in only ∼65% binding capacity. However, when oil is added to the mixture, infliximab's binding capacity increases up to ∼85%. These promising results demonstrate that 3D printing has the potential to be exploited as a novel platform for fabricating dosage forms containing biopharmaceuticals, avoiding patients' compliance issues observed with injectables and addressing their unmet needs.

Models of care and the role of clinical pharmacists in UK primary care for older adults: A scoping review protocol.

INTRODUCTION: There has been global investment of new ways of working to support workforce pressures, including investment in clinical pharmacists working in primary care by the NHS in the England. Clinical pharmacists are well suited to support older adults who have multiple long-term conditions and are on multiple medications. It is important to establish an evidence base for the role of clinical pharmacists in supporting older adults in primary care, to inform strategic and research priorities. The aim of this scoping review is to identify, map and describe existing research and policy/guidance on the role of clinical pharmacists in primary care supporting older adults, and the models of care they provide. METHODS AND ANALYSIS: A scoping review guided by the Joanne Briggs Institute methodology for scoping reviews, using a three-step strategy. We will search Medline, CINAHL, Scopus, EMBASE, Web of Science, PSYCHInfo, and Cochrane for English language articles, from 2015 -present day. Grey literature will be searched using Grey Matters guidelines, the Index of Grey Literature and Alternative Sources and Resources, and Google keyword searching. References of all included sources will be hand searched to identify further resources. Using the Population, Concept and Context framework for inclusion and exclusion criteria, articles will be independently screened by two reviewers. The inclusion and exclusion criteria will be refined after we become familiar with the search results, following the iterative nature of a scoping review. Data will be extracted using a data extraction tool using Microsoft Excel and presented using a narrative synthesis approach. ETHICS AND DISSEMINATION: Ethical approval is not required for this review. Review findings will be disseminated in academic conferences and used to inform subsequent qualitative research. Findings will be published and shared with relevant local and national organisations.

Transscleral Delivery of Dexamethasone-Loaded Microparticles Using a Dissolving Microneedle Array.

Microneedles (MNs) have attracted considerable interest as a means of ocular drug delivery, a challenging delivery route due to the limitations imposed by the various biological barriers associated with this organ. In this study, a novel ocular drug delivery system was developed by formulating a dissolvable MN array containing dexamethasone-loaded PLGA microparticles for scleral drug deposition. The microparticles serve as a drug reservoir for controlled transscleral delivery. The MNs displayed sufficient mechanical strength to penetrate the porcine sclera. Dexamethasone (Dex) scleral permeation was significantly higher than in topically instilled dosage forms. The MN system was able to distribute the drug through the ocular globe, with 19.2% of the administered Dex detected in the vitreous humour. Additionally, images of the sectioned sclera confirmed the diffusion of fluorescent-labelled microparticles within the scleral matrix. The system therefore represents a potential approach for minimally invasive Dex delivery to the posterior of the eye, which lends itself to self-administration and hence high patient convenience.

3D printed multi-drug-loaded suppositories for acute severe ulcerative colitis.

Acute severe ulcerative colitis (ASUC) is a growing health burden that often requires treatment with multiple therapeutic agents. As inflammation is localised in the rectum and colon, local drug delivery using suppositories could improve therapeutic outcomes. Three-dimensional (3D) printing is a novel manufacturing tool that permits the combination of multiple drugs in personalised dosage forms, created based on each patient's disease condition. This study, for the first time, demonstrates the feasibility of producing 3D printed suppositories with two anti-inflammatory agents, budesonide and tofacitinib citrate, for the treatment of ASUC. As both drugs are poorly water-soluble, the suppositories' ability to self-emulsify was exploited to improve their performance. The suppositories were fabricated via semi-solid extrusion (SSE) 3D printing and contained tofacitinib citrate and budesonide in varying doses (10 or 5 mg; 4 or 2 mg, respectively). The suppositories displayed similar dissolution and disintegration behaviours irrespective of their drug content, demonstrating the flexibility of the technology. Overall, this study demonstrates the feasibility of using SSE 3D printing to create multi-drug suppositories for the treatment of ASUC, with the possibility of titrating the drug doses based on the disease progression.

Prandial state and biological sex modulate clinically relevant efflux transporters to different extents in Wistar and Sprague Dawley rats.

P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), and multidrug resistance-associated protein 2 (MRP2) are clinically relevant efflux transporters implicated in the oral absorption of many food and drug substrates. Here, we hypothesised that food intake could influence protein and mRNA intestinal expression of P-gp/abcb1a, BCRP/abcg2, and MRP2/abcc2 differently in male and female Wistar and Sprague Dawley rats. To test this hypothesis, we used enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (PCR) to quantify the protein and mRNA intestinal expression of these transporters, respectively. Our study found food and sex differences in P-gp expression, whereby in the fed state P-gp expression decreased in male Wistar rats, but P-gp expression increased in females. In the fed state, BCRP expression increased in both male and female Wistar rats, compared with the fasted state. In contrast, no sex differences or food effect differences were seen in Sprague Dawley rats for P-gp and BCRP expression. On the other hand, in the fed state, MRP2 expression was higher in male and female Wistar and Sprague Dawley rats when compared with the fasted state. Sex differences were also observed in the fasted state. Overall, significant strain differences were reported for P-gp, BCRP and MRP2 expression. Strong to moderate positive linear correlations were found between ELISA and PCR quantification methods. ELISA may be more useful than PCR as it reports protein expression as opposed to transcript expression. Researchers must consider the influence of sex, strain and feeding status in preclinical studies of P-gp, BCRP and MRP2 drug substrates.

Machine learning using multi-modal data predicts the production of selective laser sintered 3D printed drug products.

Three-dimensional (3D) printing is drastically redefining medicine production, offering digital precision and personalized design opportunities. One emerging 3D printing technology is selective laser sintering (SLS), which is garnering attention for its high precision, and compatibility with a wide range of pharmaceutical materials, including low-solubility compounds. However, the full potential of SLS for medicines is yet to be realized, requiring expertise and considerable time-consuming and resource-intensive trial-and-error research. Machine learning (ML), a subset of artificial intelligence, is an in silico tool that is accomplishing remarkable breakthroughs in several sectors for its ability to make highly accurate predictions. Therefore, the present study harnessed ML to predict the printability of SLS formulations. Using a dataset of 170 formulations from 78 materials, ML models were developed from inputs that included the formulation composition and characterization data retrieved from Fourier-transformed infrared spectroscopy (FT-IR), X-ray powder diffraction (XRPD) and differential scanning calorimetry (DSC). Multiple ML models were explored, including supervised and unsupervised approaches. The results revealed that ML can achieve high accuracies, by using the formulation composition leading to a maximum F1 score of 81.9%. Using the FT-IR, XRPD and DSC data as inputs resulted in an F1 score of 84.2%, 81.3%, and 80.1%, respectively. A subsequent ML pipeline was built to combine the predictions from FT-IR, XRPD and DSC into one consensus model, where the F1 score was found to further increase to 88.9%. Therefore, it was determined for the first time that ML predictions of 3D printability benefit from multi-modal data, combining numeric, spectral, thermogram and diffraction data. The study lays the groundwork for leveraging existing characterization data for developing high-performing computational models to accelerate formulation development.

Inkjet drug printing onto contact lenses: Deposition optimisation and non-invasive dose verification.

Inkjet printing has the potential to advance the treatment of eye diseases by printing drugs on demand onto contact lenses for localised delivery and personalised dosing, while near-infrared (NIR) spectroscopy can further be used as a quality control method for quantifying the drug but has yet to be demonstrated with contact lenses. In this study, a glaucoma therapy drug, timolol maleate, was successfully printed onto contact lenses using a modified commercial inkjet printer. The drug-loaded ink prepared for the printer was designed to match the properties of commercial ink, whilst having maximal drug loading and avoiding ocular inflammation. This setup demonstrated personalised drug dosing by printing multiple passes. Light transmittance was found to be unaffected by drug loading on the contact lens. A novel dissolution model was built, and in vitro dissolution studies showed drug release over at least 3 h, significantly longer than eye drops. NIR was used as an external validation method to accurately quantify the drug dose. Overall, the combination of inkjet printing and NIR represent a novel method for point-of-care personalisation and quantification of drug-loaded contact lenses.

Advancing oral delivery of biologics: Machine learning predicts peptide stability in the gastrointestinal tract.

The oral delivery of peptide therapeutics could facilitate precision treatment of numerous gastrointestinal (GI) and systemic diseases with simple administration for patients. However, the vast majority of licensed peptide drugs are currently administered parenterally due to prohibitive peptide instability in the GI tract. As such, the development of GI-stable peptides is receiving considerable investment. This study provides researchers with the first tool to predict the GI stability of peptide therapeutics based solely on the amino acid sequence. Both unsupervised and supervised machine learning techniques were trained on literature-extracted data describing peptide stability in simulated gastric and small intestinal fluid (SGF and SIF). Based on 109 peptide incubations, classification models for SGF and SIF were developed. The best models utilized k-Nearest Neighbor (for SGF) and XGBoost (for SIF) algorithms, with accuracies of 75.1% (SGF) and 69.3% (SIF), and f1 scores of 84.5% (SGF) and 73.4% (SIF) under 5-fold cross-validation. Feature importance analysis demonstrated that peptides' lipophilicity, rigidity, and size were key determinants of stability. These models are now available to those working on the development of oral peptide therapeutics.

Colonic drug delivery: Formulating the next generation of colon-targeted therapeutics.

Colonic drug delivery can facilitate access to unique therapeutic targets and has the potential to enhance drug bioavailability whilst reducing off-target effects. Delivering drugs to the colon requires considered formulation development, as both oral and rectal dosage forms can encounter challenges if the colon's distinct physiological environment is not appreciated. As the therapeutic opportunities surrounding colonic drug delivery multiply, the success of novel pharmaceuticals lies in their design. This review provides a modern insight into the key parameters determining the effective design and development of colon-targeted medicines. Influential physiological features governing the release, dissolution, stability, and absorption of drugs in the colon are first discussed, followed by an overview of the most reliable colon-targeted formulation strategies. Finally, the most appropriate in vitro, in vivo, and in silico preclinical investigations are presented, with the goal of inspiring strategic development of new colon-targeted therapeutics.

Incidence of postural hypotension recorded in UK general practice: an electronic health records study.

BACKGROUND: Postural hypotension is a common condition associated with adverse outcomes in older adults. General practice plays an important role in identification of the condition. AIM: To examine the incidence of postural hypotension between 2008 and 2018 in general practice and how trends vary by age, sex, year, and social deprivation. DESIGN AND SETTING: Retrospective cohort study using electronic health records from the IQVIA Medical Research Data (IMRD) between 2008 and 2018. METHOD: Patients were included if they were aged ≥50 years. Incident postural hypotension was identified as a new (first) recording of a postural hypotension code. Recording of incident postural hypotension was estimated per 10 000 person-years at risk (PYAR) according to age, sex, year, and social deprivation. Incident rate ratios were estimated by multivariable Poisson regression. RESULTS: Of 2 911 260 patients, 24 973 had an electronic record indicating a new diagnosis of postural hypotension between 2008 and 2018. This was equivalent to 17.9 cases per 10 000 PYAR in males (95% confidence interval [CI] = 17.6 to 18.2) and 16.2 cases per 10 000 PYAR in females (95% CI = 15.9 to 16.5). A significant age-sex interaction was identified. Recorded postural hypotension rate increased with age and social deprivation, and reduced between 2008 and 2018. The rate was higher in males compared with females, particularly in older age groups (>80 years). CONCLUSION: To the authors' knowledge, this is the first study to quantify incident recorded postural hypotension in general practice. The rate is lower than expected compared with studies in screened older populations. Potential barriers to identification include underreporting, underdetection owing to lack of time and/or poorly standardised methods of measurement, and poor coding. Future research should investigate current practice and approaches for increased detection such as education, practical methods of screening, and standardised measurement of postural blood pressure.

Scent-delivery devices as a digital healthcare tool for olfactory training: A pilot focus group study in Parkinson's disease patients.

Parkinson's disease (PD) patients display a combination of motor and non-motor symptoms. The most common non-motor symptom is scent (olfactory) impairment, occurring at least four years prior to motor symptom onset. Recent and growing interest in digital healthcare technology used in PD has resulted in more technologies developed for motor rather than non-motor symptoms. Human-computer interaction (HCI), which uses computer technology to explore human activity and work, could be combined with digital healthcare technologies to better understand and support olfaction via scent training - leading to the development of a scent-delivery device (SDD). In this pilot study, three PD patients were invited to an online focus group to explore the association between PD and olfaction, understand HCI and sensory technologies and were demonstrated a new multichannel SDD with an associated mobile app. Participants had a preconceived link, a result of personal experience, between olfactory impairment and PD. Participants felt that healthcare professionals did not take olfactory dysfunction concerns seriously prior to PD diagnosis. Two were not comfortable with sharing scent loss experiences with others. Participants expected the multichannel SDD to be small, portable and easy-to-use, with customisable cartridges to deliver chosen scents and the mobile app to create a sense of community. None of the participants regularly performed scent training but would consider doing so if some scent function could be regained. Standardised digital SDDs for regular healthcare check-ups may facilitate improvement in olfactory senses in PD patients and potential earlier PD diagnosis, allowing earlier therapeutic and symptomatic PD management.

Multimodal Diagnosis for Pulmonary Embolism from EHR Data and CT Images.

Pulmonary Embolism (PE) is a severe medical condition that can pose a significant risk to life. Traditional deep learning methods for PE diagnosis are based on Computed Tomography (CT) images and do not consider the patient's clinical context. To make full use of patient's clinical information, this article presents a multimodal fusion model ingesting Electronic Health Record (EHR) data and CT images for PE diagnosis. The proposed model is based on multilayer perception and convolutional neural networks. To remove the invalid information in the EHR data, the multidimensional scaling algorithm is performed for feature dimension reduction. The EHR data and CT images of 600 patients are used for experiments. The experiment results show that the proposed models outperform existing methods and the multimodal fusion model shows better performance than the single-input model.

Medical and pharmacy students' perspectives of remote synchronous interprofessional education sessions.

BACKGROUND: Interprofessional education (IPE) at university level is an essential component of undergraduate healthcare curricula, as well as being a requirement of many associated regulatory bodies. In this study, the perception of pharmacy and medical students' of remote IPE was evaluated. METHODS: A series of IPE sessions took place via Zoom and students' feedback was collected after each session. Both qualitative and quantitative data were collected and analysed. RESULTS: 72% (23/32) of medical students strongly agreed that the sessions had helped to improve their appreciation of the role of pharmacists, whereas 37% (22/59) of pharmacy students strongly agreed, reporting a median response of 'somewhat agreeing', that their appreciation of the role of general practitioners had improved. This difference was found to be statistically significant (p = 0.0143). Amongst students who responded, 55% (53/97) identified remote teaching as their preferred mode of delivery for an IPE session. CONCLUSIONS: The survey demonstrated that the students valued the development of their prescribing skills as well as the ancillary skills gained, such as communication and teamwork. Remote IPE can be a practical means of improving medical and pharmacy students' understanding of each other's professional roles, as well as improving the skills required for prescribing.