This case report describes of a pharmacokinetic drug–drug interaction between crizotinib, a tyrosine kinase inhibitor, and sofosbuvir/velpatasvir, a direct-acting antiviral drug, leading to cardiac toxicity. A 75-year-old man, with no cardiovascular history but a diagnosis of metastatic non-small cell lung cancer with MET exon-14 deletion and hepatitis C virus infection genotype 1A, received both crizotinib and sofosbuvir/velpatasvir. Crizotinib was well tolerated, but 1 week after sofosbuvir/velpatasvir initiation, the patient experienced bilateral lower-limb edema and class III NYHA dyspnea. We assumed that increased exposure to crizotinib could account for this cardiac toxicity. Drug causality was probable according to the Naranjo scale. We hypothesized a reciprocal interaction between crizotinib and velpatasvir, mediated by both cytochrome 3A4 (CYP3A4) and P-glycoprotein (P-gp). Clinicians should be aware of the risk of drug–drug interactions between direct-acting antiviral agents that inhibit CYP3A4 (glecaprevir) and/or P-gp (voxilaprevir) and anticancer tyrosine kinase inhibitors that are mostly CYP3A4 and/or P-gp substrates (gefitinib, afatinib, erlotinib, crizotinib, ceritinib, lorlatinib, brigatinib, capmatinib etc.).

Establishing dose response relationships in targeted patients is foundational in the development of therapeutic drugs including gene therapy products. Enlightened by interspecies normalization of plasma drug concentration-time curves using Dedrick plot, the author of this manuscript first demonstrated the feasibility of normalizing dose-response relationship of adeno-associated virus (AAV)-mediated hemophilia gene therapy products in multiple species to a species-invariant scale. Preclinical dose-response relationships of eight AAV vectors were normalized using an exponent of 0.25 and applied to first-in-human (FIH) dose prediction. The performance of this dose-response normalization approach for FIH dose prediction was compared to that of direct body weight-based dose conversion and allometric scaling approaches. The study results suggested that in addition to hemophilia dogs and non-human primates, inclusion of larger animal models (e.g., swine and cattle) in preclinical dose-finding studies of AAV vectors might improve the performance of interspecies dose-response normalization approach. Furthermore, it was found that AAV capsid-specific T cell responses in hemophilia patients might cause underprediction of FIH dose while novel bioengineered capsids with a high transduction efficiency specifically in human hepatocytes might cause overprediction of FIH dose. These factors should be considered when dose-response is extrapolated from preclinical species to patients.

Aim Pharmacokinetics have historically been assessed using drug concentration data obtained via blood draws and bench-top analysis. The cumbersome nature of these typically constrains studies to at most a dozen concentration measurements per dosing event. This, in turn, limits our statistical power in the detection of hours-scale, time-varying physiological processes. Given recent advent of in-vivo electrochemical aptamer-based (EAB) sensors, however, we can now obtain hundreds of concentration measurements per administration. Our aim in this paper is to assess the ability of these time-dense datasets to describe time-varying pharmacokinetic models with good statistical significance. Methods Here we use seconds-resolved measurements of plasma tobramycin concentrations in rats to statistically compare traditional one- and two-compartmental pharmacokinetic models to new models in which the proportional relationship between a drug’s plasma concentration and its elimination rate varies in response to changing kidney function. Results We find that a modified one-compartment model in which the proportionality between the plasma concentration of tobramycin and its elimination rate falls reciprocally with time either meets or is preferred over the standard two-compartment pharmacokinetic model for half of the datasets characterized. When we reduce the impact of the drug’s rapid distribution phase on the model, this one-compartment, time-varying model is statistically preferred over or tied with the standard two-compartment model for 80% of our datasets. Conclusions Our results highlight both the impact that simple physiological changes (such as varying kidney function) can have on drug pharmacokinetics and the ability of high-time-resolution EAB sensor measurements to identify such impacts.

The COVID-19 pandemic has disrupted seeking and delivery of healthcare. Different Australian jurisdictions implemented different COVID-19 restrictions. We used Australian national pharmacy dispensing data to conduct interrupted time series analyses to examine the incidence and prevalence of opioid dispensing in different jurisdictions. Following nationwide COVID-19 restrictions, the opioid incidence dropped by -0.40 [-0.50, -0.31], -0.33 [-0.46, -0.21] and -0.21 [-0.37, -0.04] /1000 people/week and prevalence dropped by -0.85 [-1.39, -0.31], -0.54 [-1.01, -0.07] and -0.62 [-0.99, -0.25] /1000 people/week in Victoria, New South Wales and other jurisdictions, respectively. Incidence and prevalence increased by 0.29 [0.13, 0.44] and 0.72 [0.11, 1.33] /1000 people/week, respectively in Victoria post-lockdown; no significant changes were observed in other jurisdictions. No significant changes were observed in the initiation of long-term opioid use in any jurisdictions. More stringent restrictions coincided with more pronounced reductions in overall opioid initiation, but initiation of long-term opioid use did not change.

RP7214 is a potent and selective inhibitor of human mitochondrial enzyme dihydroorotate dehydrogenase (DHODH). This paper describes the results from a Phase 1 study that evaluated safety and pharmacokinetics of single and multiple ascending doses (SAD and MAD) and the food effect of RP7214 in healthy subjects. Target engagement of DHODH was also evaluated. A randomized, double-blind, placebo-controlled trial of single-dose (100, 200, and 400 mg QD) and multiple doses (200 and 400 mg BID for 7 days) followed by food effect at a single dose of 200 mg was conducted. A total of 18 healthy volunteers (HVs) (6 subjects in each of three cohorts) in the SAD part, 12 (6 subjects each in two cohorts) in the MAD part, and 12 in the food effect study were enrolled. RP7214 was well tolerated at all dose levels. None of the subjects reported any RP7214-related adverse events. RP7214 showed dose-proportional pharmacokinetics after single and multiple dosing. Steady-state concentrations were reached within about 3–6 days. The mean plasma half-life of RP724 at steady-state was approximately 13h. RP7214 showed accumulation on multiple dosing.. Food did not impact the absorption of RP7214. RP7214 showed dose-dependent inhibition of DHODH as measured by analyzing accumulating DHO levels, confirming target engagement. The rapid absorption and high systemic exposure of RP724 with a favorable safety profile shows the potential for the development of RP7214 in SARS-CoV-2 infection and acute myeloid leukemia. (NCT04680429). Keywords: RP7214, dihydroorotate dehydrogenase, SAD, MAD, HV

Aim: To summarise the effectiveness of organisational interventions on appropriate opioid use for non-cancer pain upon hospital discharge. Methods: A systematic search was conducted on six electronic databases by two independent reviewers. We included original research articles reporting on quantitative outcomes of organisational interventions targeting appropriate opioid use on hospital discharge. Quality assessment was performed by two independent reviewers. The protocol for this review was prospectively registered on PROSPERO (ID: CRD42020156104). Results: Out of 173 full texts assessed for eligibility, 43 were included in this review. The majority of studies had a moderate to serious risk of bias (33 out of 43). Most of the studies implemented a multifaceted organisational intervention (16 studies). Other interventions included guideline implementation, prescriber education and default opioid prescribing quantity changes in electronic medical records. Multiple studies found that the dissemination of patient-specific and procedure-specific guidelines reduced the quantity of opioids prescribed by 44-57%. Prescriber education provided with feedback was implemented in four studies and resulted in a 33-44% decrease in prescribing rates. Lowering the default quantities in the electronic medical records produced a 40% decrease in opioids prescribed in one study. Conclusion: Guideline implementation, prescriber education and default opioid prescribing quantity changes all appear effective in improving the appropriate use of opioids on hospital discharge. However, the extent of reduction of opioid prescribing upon hospital discharge after the implementation of multifaceted intervention strategies appears similar to that of simpler interventions which require fewer resources.

Background: Dexmedetomidine could be an ideal adjuvant to propofol during gastrointestinal endoscopy because it provides both analgesia and sedation without respiratory depression. This study investigates the effect of different doses of dexmedetomidine on the median effective concentration of propofol during gastrointestinal endoscopy. Methods: 90 adult patients were randomly assigned to Group Control , Group DEX0.5 (0.5 μg/kg dexmedetomidine), or Group DEX1.0 (1.0 μg/kg dexmedetomidine) . Anaesthesia during endoscopy was implemented by plasma target-controlled infusion (TCI) of propofol with different doses of dexmedetomidine. TCI concentration of the first patient for each group was 2.5 μg/ml and the consecutive adjacent concentration gradient was 0.5 μg/mL. EC50 of TCI propofol for gastrointestinal endoscopy was determined by using the modified Dixon’s up-and-down method. Cardiovascular variables were also measured. Results: EC50 of TCI propofol and 95% confidence interval (CI) for gastrointestinal endoscopy were, 3.77 (3.48-4.09), 2.51 (2.27-2.78) and 2.10 (1.90-2.33) μg/mL in Group Control, Group DEX0.5 and Group DEX1.0. The average percent change from baseline in HR was 2.8 (8.9), -7.4 (7.7) and -10.5 (8.8) (P＜0.001), and the average percent change from baseline in MAP was -10.6 [-24.7; 3.5], -9.5 [-29.2; 11.4] and -4.0 [-27.3; 15.5] (P = 0.034) in Group Control, Group DEX0.5 and Group DEX1.0, respectively. Conclusions: Dexmedetomidine reduced the EC50 of TCI propofol. A 0.5-1 μg/kg dexmedetomidine caused a decrease in HR without bradycardia. The decrease in dosage of propofol with increasing doses of dexmedetomidine caused more stable MAP. Dexmedetomidine is an ideal adjuvant drug to propofol during gastrointestinal endoscopy.

Guillain- Barre Syndrome (GBS), an autoimmune neurological disease of peripheral nerves has been causally associated with COVID-19 vaccination in adults. However, no such report has been published so far in children. We describe a 13-year old female child who presented to emergency department with complaints of bilateral upper limb, lower limb and truncal weakness over three days following first dose of recombinant protein subunit COVID-19 vaccine (Corbevax). Clinical examination and nerve conduction studies showed pure motor axonal polyneuropathy with absent compound muscle action potential (CMAP) in all sampled nerves of upper and lower limbs which was consistent with the diagnosis of GBS after ruling out possible alternative aetiologies. A temporal association between first dose of protein subunit COVID-19 vaccine administered a day prior and symptom onset was noted. The causality assessment using World Health Organization (WHO) tool for adverse event following immunization (AEFI) assessment indicated vaccine-product related reaction categorized as A1. Patient’s clinical condition improved after seven sessions of plasmapheresis. The purpose of this report is to create awareness among the health care professionals about COVID-19 vaccine induced GBS in children as early diagnosis and management can be critical in avoiding complications and improving patient outcomes.

“Pharmacovigilance is the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medication-related problem”, according to the WHO. With the increasing volume of legislation, pharmacovigilance systems have shifted from reactive (responding to emerging risks), to planned, active, risk-proportionate approaches operating throughout the lifecycle of medicines. Whilst medicines are beneficial to society, adverse reactions represent a significant cause of concern. They are a major cause of failed regulatory authorizations, and withdrawal from the marketplace post-approval. Evaluation of real-world data plays an increasingly important role in pharmacovigilance. There is great interest on the part of the regulators, MAHs, academia and patients in optimizing the use of safety data. Innovative approaches, including pharmacogenetics and passive measures (sensors), will lead to increased complexity in data collation and evaluation, and inevitably to an increase in the volume of case reports. There is a multiplicity of regulations and guidelines on how to manage these data, with an inherent lack of harmonization. We summarize the current characterization of safety data types, sources, and the classification of these data. Using this benchmark, we discuss the future requirements of an effective pharmacovigilance ecosystem, keeping the principle of parsimony in mind.

Aim. To describe the trends in anti-infective use during pregnancy between 2010 and 2019 and determine whether they were prescribed according to drug fetal safety international classification systems. Methods. We conducted a population-based, nationwide study using the French national health data system including all pregnancies ended between 2010 and 2019. Anti-infective were considered according to their pharmacological group and potential harmful risk using the Australian and Swedish classification systems. Prevalence rate was estimated annually and by trimester. Average annual percent change (AAPC) and 95% confidence intervals (CI) were calculated using Joinpoint regression. Results. Among 7,571,035 pregnancies, 3,027,031 (40.0%) received ≥ 1 antibacterial. This proportion decreased significantly from 41.5% in 2010 to 36.1% in 2019 (AAPC=-1.7%, [95%CI, -2.5% to -1.0%]). Conversely, use of antiviral agents increased during the 10 years’ study period for anti-HSV agents (AAPC=4.4%, [3.7%-5.2%]), influenza agents (AAPC=25.4%, [6.2%-48.1%]), and for HIV-antiretroviral agents (HIV-ART) (AAPC=1.3%, [0.6%-2.0%]). Use of influenza vaccine increased from 0.2% in 2010 to 4.2% in 2019 (AAPC=49.7%, [95%CI, 39.3% to 60.9%]). Among all pregnancies, 0.9% had been exposed to a potentially harmful anti-infective agent increasing from 0.7% in 2010 to 1.2% in 2019 (AAPC=6.4%, [4.4%-8.5 %]). Conclusion. Based on more than 7 million pregnancies identified from French nationwide data, this study showed that antibacterials are frequently prescribed during pregnancy although their use has decreased over the past ten years. Our results suggest that anti-infective are generally prescribed in accordance with recommendations, with however a potential for improvement in influenza vaccination.

Background: Multiple myeloma accounts for over 15% of hematological malignancies. In attempt to tackle this malady, the FDA approved four drugs in 2015 which has propagated further development of new anti-multiple myeloma since. However, the health safety of these new agents is still ill-defined. The aim of this study is to delineate the cardiovascular adverse events of these drugs. Methods: We searched the cardiac adverse events of the newly approved FDA drugs since 2015 using the U.S. Food and Drug Administration Adverse Events Reporting System database (FAERS). We calculated the reporting odds ratio (ROR) with 95% confidence for four drugs that have the highest incidence of cardiovascular adverse events. Results: Among the medications that have approved for MM Between 2015-2020, four novel drugs showed the highest incidence of cardiotoxicity. ROR (95% CI) for atrial fibrillation due to elotuzumab, Ixazomib, daratumumab, and panobinostat compared to other FAERS drugs was 5.8 (4.4-7.7), 1.9 (1.5-2.3), 4.8 (4.2-5.6), and 5.7 (4.1-8.1), respectively. The ROR (95% CI) for cardiac failure was 8.2 (6.4-10.5), 4.7 (4.1-5.4), 5.8 (4.9-6.7), and 5.6 (3.8-8.1) and ROR (95% CI) for coronary disease was 2.7 (1.9-3.9), 2.7 (2.3-3.2), 2.3 (1.9-2.8), and 4.6 (3.2-6.6) due to elotuzumab, Ixazomib, daratumumab, and panobinostat versus all other drugs in FAERS. Conclusions: Our results demonstrated that the newly approved antimyeloma therapy (elotuzumab, Ixazomib, daratumumab, panobinostat) are significantly associated previously unknow cardiotoxicity. These results warrant further studies and highlight the importance of considering the cardiac history of patients with multiple myeloma when utilizing these novel agents.

Fluvoxamine for COVID-19 outpatients: for the time being, we might prefer to curb our optimismVladimir TrkuljaRunning head : Fluvoxamin and COVID-19 outpatientsKey words : fluvoxamine, COVID-19, outpatients, hospitalizationsVladimir Trkulja, MD, PhDDepartment of PharmacologyZagreb University School of MedicineŠalata 1110000 Zagreb, Croatiae-mail: vladimir.trkulja@mef.hrNumber of words: 613Number of figures/tables: 1To the Editor,A rather elaborate pharmacodynmics rationale 1 and sound pharmacokinetic reasoning 2 support the use of fluvoxamin in early phases of the COVID-19 disease. Two recent meta-analyses, 3, 4 both based on the same three randomized placebo-controlled trials, emphasized the benefit of early fluvoxamine treatment in non-vaccinated adult symptomatic mild COVID-19 outpatients in terms of a reduced risk of disease deterioration over subsequent days. In the first of the meta-analyzed trials, Stop COVID 15, primary outcome was hospitalization or incident hypoxemia needing oxygen treatment within 15 days. The trial was rather small, particularly for a binary outcome (fluvoxamine 2x100 to 3x100 mg/day over 15 days, n=80; placebo n=72) and recorded only 6 events (all with placebo) 5. Stop COVID 2 6followed the same design/outcome, and was stopped at an advanced stage for operational reasons but did not indicate any benefit [incidence 11/272 (4.0%) fluvoxamin vs. 12/275 (4.4%) placebo)]. The meta-analytical pooled estimates 3, 4 were dominated by the results of the TOGETHER trial 7 (fluvoxamine 2x100 mg/day, 10 days) that reported a marked relative reduction in the risk of the primary outcome (emergency room stay of at least 6 hours or hospitalization; over 28 days): 79/741 (11.0%) vs. 119/756 (16.0%), RR=0.69 (95% CrI 0.53-0.90) 7. By far the most events were hospitalizations, but no clear-cut benefit was obvious in this respect [75/741 (10.0%) vs. 97/756 (13.0%), OR=0.77 (0.55-1.05)7]. The meta-analysis by Lee et al.3 focused on hospitalizations and reported a 25% relative risk reduction by a frequentist method (RR=0.75, 95%CI 0.58-0.97), while the Bayesian analysis (weakly informative neutral prior) indicated somewhat more uncertainty (RR=0.78, 95%CrI 0.58-1.08; 81.6% probability of RR ≤0.90) 3. Guo et al.4 employed only frequentist pooling to indicate a marked benefit regarding “study-defined outcomes” (RR=0.69 95%CI 0.54-0.88) and somewhat more uncertainty regarding “hospitalizations” (RR=0.79, 95%CI 0.60-1.03) 4. In the meantime, a report was pubslihed of a randomized placebo-controlled trial conducted in 2020 in Korean outpatients (∼10 days of fluvoxamine 2x100 mg/day)8. It was stopped early for operational reasons8, and the primary outcome (as in Stop COVID trials) was observed in 2/26 treated and 2/26 placebo patients8. Figure 1 depicts meta-analysis of “study-defined primary outcomes” and of “hospitalizations” that uses the same frequentist and Bayesian methodology as used by Lee et al.3 except that (i) it includes the Korean data8 and (ii) employs Hartung-Knapp-Sidik-Jonkman correction shown to yield the least biased confidence interval coverage with small number of trials considerably varying in size9: (a) uncertainty about the benefit regarding “study-defined outcomes” (Figure 1A) is indicated by both the frequentist and Bayesian intervals extending to >1.0 and prediction intervals extending well >1.0. Probability of at least 10% relative risk reduction is 90.0%; (b) uncertainty about the benefit regarding “hospitalizations” (Figure 1B) is even more obvious, with estimate intervals exceding >1.10 (and further extended predictions intervals), with only 73.8% probability of at least 10% relative risk reduction. If one were to disregard two small trials with a few events (and, hence, fragile estimates that could have been by chance, at least in part) 5, 8, for the time being one would be looking at Stop COVID 2 and TOGETHER trial. This means 86/1013 hospitalization events with fluvoxamine vs. 109/1031 events with placebo, and a considerable uncertainty about any practically relevant effect: (i) frequentist RR=0.803 (95%CI 0.422-1.530); (ii) Bayesian RR=0.840 (95%CrI 0.613-1.170) and only 67.4% probablity of at least 10% relative risk reduction. Hopefully, the on-going trials (depicted in ref. 3) will resolve this uncertainty, but presently we might prefer to be cautios rather than overtly optimistic about the actual extent of benefit conveyed by early fluvoxamine treatment in COVID-19 outpatients.

Background: Clinical trial simulations and pharmacometric modeling of biomarker profiles for under-represented groups are challenging because the underlying studies frequently do not have sufficient participants from these groups. Objectives: To investigate generative adversarial networks (GANs), an artificial intelligence (AI) technology that enables realistic simulations of complex patterns, for modeling clinical biomarker profiles of under-represented groups. Methods: GANs consist of generator and discriminator neural networks that operate in tandem. GAN architectures were developed for modeling univariate and joint distributions of a panel of 16 diabetes-relevant biomarkers from the National Health and Nutrition Examination Survey (NHANES), which contains laboratory and clinical biomarker data from a population-based sample of individuals of all ages, racial groups, and ethnicities. Conditional GANs were used to model biomarker profiles for race/ethnicity categories. GAN performance was assessed by comparing GAN outputs to test data. Results: The biomarkers exhibited non-normal distributions and varied in their bivariate correlation patterns. Univariate distributions were modeled with generator and discriminator neural networks consisting of two dense layers with rectified linear unit-activation. The distributions of GAN-generated biomarkers were similar to the test data distributions. The joint distributions of the biomarker panel in the GAN-generated data were dispersed and overlapped with the joint distribution of the test data as assessed by three multi-dimensional projection methods. Conditional GANs satisfactorily modeled the joint distribution of the biomarker panel in the Black, Hispanic, White, and “Other” race/ethnicity categories. Conclusions: GAN are a promising AI approach for generating virtual patient data with realistic biomarker distributions for under-represented race/ethnicity groups.

Aim There is still only little knowledge about alterations of blood concentrations of psychotropic drugs during pregnancy, the transfer of psychotropic drugs into breast-milk and the effects on exposed children. Methods We investigated changes in concentrations of psychopharmacological medication during pregnancy and lactation in serum and breast milk at different time points in a naturalistic sample of 60 mothers and observed the development of the exposed children in the first 12 months. Results We found a decrease in serum concentrations from the first to the second trimester of amitriptyline, duloxetine, escitalopram, quetiapine and sertraline. Citalopram stayed rather stable during pregnancy, sertraline levels interestingly increased again from the second to the third trimester. Highest concentration-by-dose-ratios in breast milk were found for venlafaxine as well as lamotrigine, lowest for quetiapine and clomipramine. Similarly, clomipramine and quetiapine showed lowest milk/serum-penetration-ratios. Regarding the birth outcome measures in children we found no significant differences between in utero exposed compared to non-exposed new-borns. There were no significant differences in the development in the first 12 months. Conclusion Psychotropic medication in the peripartum needs a balancing of risks and benefits and a continuous therapeutic drug monitoring (TDM) can be a guidance for clinicians to monitor drug alteration patterns, which are likely to occur due to physiological pregnancy-associated changes in pharmacokinetics. Accordingly, TDM can optimize a medication in pregnancy and lactation with the lowest but effective dose.

Aim To evaluate the number and nature of reported congenital malformations (CMs) after intrauterine exposure to non-tumour necrosis factor inhibitors (non-TNFis) compared to certolizumab pegol (CZP) Material and methods A retrospective comparative study was conducted in the EudraVigilance (EV) database. EV is a pharmacovigilance database, which can be used for detecting safety signals and generating hypotheses on possible relations between drugs and adverse events. A supposedly safe biologic (CZP) was considered as the reference group. Pregnancy-reports of non-TNFis and CZP were extracted. Odds ratios (ORs) for CMs were calculated for each non-TNFi, versus CZP (quantitative assessment). Then, CM patterns were compared to CZP in consultation with a clinical geneticist (qualitative assessment). Results ORs were not statistically significant except for belimumab and vedolizumab (similar in magnitude). Although qualitative analyses did not show any specific patterns for belimumab but three cases of corpus callosum agenesis (CCA) were identified for vedolizumab (versus null in CZP and other investigated non-TNFis). Two of the CCA cases were associated with other neurological CMs (one cerebral ventriculomegaly with microcephaly and one polymicrogyria). This may indicate that these CCAs are related to undiagnosed genetic alterations or are associated with the underlying maternal disease, although a definite relationship with vedolizumab exposure cannot be ruled out. Conclusion No special safety signal was identified regarding the occurrence of CMs after exposure to non-TNFis, except for vedolizumab. Based on available information, no firm conclusions can be made regarding observed CCAs in the vedolizumab group (it warrants further research)

Aim: Although there is a high risk of gastrointestinal (GI) bleeding in the elderly, few studies have quantified the impact of risk factors on GI complications in elderly nonsteroidal anti-inflammatory drug (NSAID) users. This study aimed to develop and validate a risk prediction score to identify high-risk elderly patients using NSAID for severe GI complications. Methods: We used the following two Korean claims datasets: customized data with an enrollment period 2016–2017 for model development, and the sample data in 2019 for external validation. We conducted a nested case-control study for model development and validation. NSAID users were identified as the elderly (≥ 65 years) who received NSAIDs for more than 30 days. Patients who experienced serious GI complications, defined as hospitalizations or emergency department visits, were diagnosed with GI bleeding or perforation. We derived a model using logistic regression and cross-validation. Results: In the external validation cohort, we identified 372 cases from 254,551 patients. We identified 8,176 cases and 81,760 controls with a 1:10 matched follow-up period in the derivation cohort. In the external validation cohort, we identified 372 cases from 254,551 patients. The risk predictors were high-dose NSAIDs, NSAID type, complicated GI ulcer history, male sex, concomitant gastroprotective agents, relevant co-medications, severe renal disease, and cirrhosis. Area under the receiver operating characteristic curves was 0.77 (95% confidence interval, 0.75–0.80) in the external validation dataset. Conclusion: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.

Aim: Older adults are particularly affected by medication-related harm (MRH) during transitions of care. There are no clinical tools predicting those at highest risk of MRH post-hospital discharge. The PRIME study (prospective study to develop a model to stratify the risk of MRH in hospitalized patients) developed and internally validated a risk-prediction tool (RPT) that provides a percentage score of MRH in adults over 65 in the eight-weeks following hospital discharge. This qualitative study aimed to explore the views of hospital pharmacists around enablers and barriers to clinical implementation of the PRIME-RPT. Methods: Ten hospital pharmacists: (band 6 (n=3); band 7 (n=2); band 8 (n=5)) participated in semi-structured interviews at the Royal Sussex County Hospital (Brighton, UK). The pharmacists were presented with five case-vignettes each with a calculated PRIME-RPT score to help guide discussion. Case-vignettes were designed to be representative of common clinical encounters. Data were thematically analysed using a ‘framework’ approach. Results: Seven themes emerged in relation to the PRIME-RPT: 1. providing a medicine-prioritisation aide; 2. acting as a deprescribing alert; 3. facilitating a holistic review of patient’s medication management; 4. simplifying communication of MRH to patients and the multidisciplinary team; 5. streamlining community follow-up and integration of risk discussion into clinical practice; 6. identifying barriers for the RPTs integration in clinical practice and 7. acknowledging its limitations. Conclusion: Hospital pharmacists found the PRIME-RPT beneficial in identifying older patients at high-risk of MRH following hospital discharge, facilitating prioritising interventions to those at highest risk while still acknowledging its limitations.

Aim: Guidelines establish a framework for how therapeutics and vaccines are developed, assessed and approved. They influence which innovations are likely to be approved in the EU, and by that, they have an impact on the pipeline decisions taken by the research-based industry. This study analyses the level of acceptance for changes suggested by stakeholders within the authoring groups at the EMA. Methods: We looked at 87 guidelines from EMA Working Parties (WPs) launched for consultation between 2013-2017. Acceptance of stakeholder proposals and the time between the end of consultation and guideline adoption were studied as well as the openness of different Working Parties to accept changes. Results: Adoption of a guideline after the close of public consultation took at least 4 months, with average 12-16 months. The number of accepted and rejected comments were nearly equal across the stakeholders, with government having slightly higher chance for acceptance. Academia and NGOs had generally higher chances to have their comments accepted for general and indication-level guidelines. Government and individual companies had highest acceptance for molecule-level guidelines and trade associations for indication-level guidelines. The EMA WPs working with emerging technologies were more open to accept proposed changes. Conclusion: This pattern of progress in regulatory science at EMA demonstrates the essential and interrelated role of academia, industry, government and civil society – described as the quadruple helix model - to promote establishment of a strong innovation ecosystem in Europe. Further integration and utilisation of competences of each stakeholder is necessary for guideline development.