Structured Medication Reviews (SMRs) are intended to help deliver the NHSLong Term Plan for medicines optimisation in people living with multiplelong-term conditions and polypharmacy. It is challenging to gather theinformation needed for these reviews due to poor integration of healthrecords across providers and there is little guidance on how to identifythose patients most urgently requiring review.To extract information from scattered clinical records on how health andmedications change over time, apply interpretable artificial intelligence(AI) approaches to predict risks of poor outcomes and overlay thisinformation on care records to inform SMRs. We will pilot this approach inprimary care prescribing audit and feedback systems, and co-design futuremedicines optimisation decision support systems.DynAIRx will target potentially problematic polypharmacy in three keymultimorbidity groups, namely, people with (a) mental and physical healthproblems, (b) four or more long-term conditions taking ten or more drugs and(c) older age and frailty. Structured clinical data will be drawn fromintegrated care records covering an ∼11m population supplemented with Natural Language Processing(NLP) of unstructured clinical text. AI systems will be trained to identifypatterns of conditions, medications, tests, and clinical contacts precedingadverse events in order to identify individuals who might benefit most froman SMR.By implementing and evaluating an AI-augmented visualisation of care recordsin an existing prescribing audit and feedback system we will create alearning system for medicines optimisation, co-designed throughout withend-users and patients. DynAIRx) projectaddresses problematic polypharmacy in multimorbidity (co-existence of ≥2 long-termconditions). The aim is to improve holistic care in multimorbidity by supportingmedicines optimisation, in alignment with the UK National Health Service (NHS) LongTerm Plan and 2021 National Overprescribing Review.2The Artificial Intelligence (AI) for dynamic prescribing optimisation and careintegration in multimorbidity , DynAIRx will bringthe predictive information and longitudinal care summaries together with guidelinesin new visualisations to support medicines optimisation. This combined informationwill be piloted in prescribing audit and feedback systems that clinicians are usingin research and clinical practice.6As a population we are living longer, driven by medical advances improving survivalat all ages.9 identified variousdeprescribing interventions, with barriers to implementation leading to inconsistenteffectiveness. Primary-care-embedded development of audit and feedback shows promisefor improving prescribing, with success depending on how feedback isdelivered.10 Previously, such systems have been limited by data supply.The roll-out of integrated/shared care records is now providing the data forpatient-centred and locality context sensitive ‘learning systems’.11 DynAIRx willdevelop and implement statistically principled AI approaches to systematicallyidentify problematic polypharmacy in major multimorbidity groups. In order to beeffective, AI-augmented feedback to clinicians must be co-produced with clinicalstakeholders and reviewed iteratively. Therefore, early engagement with cliniciansin the form of a needs analysis will enable:1. Understanding of the requirements of thoseinvolved in SMRs (including patients).2.Defining the barriers and facilitators to implementation of AI-guidedSMRs.3. Iterative refinement of theproposed prescribing feedback to clinicians.Despite the need for deprescribing support, evidence of how to do it systematicallyis lacking. Three Cochrane reviewsThe overall aim of DynAIRx is to develop new, easy to use, AI tools that supportgeneral practitioners (GPs) and pharmacists to find patients living withmultimorbidity  who might be offered abetter combination of medicines.1. People with mental and physical health problems, inwhom the prescribing for mental health improvement can lead to adversephysical health consequences.2. Peoplewith complex multimorbidity in the form of four or more long-term healthconditions taking ten or more drugs.3.Older people with frailty as a subgroup of people with multimorbidity atespecially high risk of adverse outcomes.The project will focus on three groups of people at high risk of rapidly worseninghealth from multimorbidity:1. Investigate how SMRs are currentlyundertaken and what barriers those undertaking them (and the patients inreceipt of them) experience.2. Seek theopinions of key stakeholders involved in the SMR process about the waysin which AI approaches can be used to improve the process and identifywhat their requirements are for prescriber feedbacksystems.3. Identify potentialbarriers/facilitators to uptake and utilisation of AI-augmented SMRs andaudit and feedback dashboards forclinicians.4. Curate structured clinicaldata from integrated records  from a variety of NHS Integrated Care Systems covering ∼11mpopulation, adding more structured data from Natural Language Processing(NLP) of psychiatric narratives inMerseyside.5. Use AI approaches andstatistical methods to identify patterns and clusters of conditions,medications, tests, and clinical contacts preceding adverse eventsacross three target groups then build the patterns into biostatisticalcausal inference and prediction of (clustered) clinicaloutcomes.6. Develop visualisation methods forlongitudinal summaries of multi-provider care records overlain with risktrajectories, combined with key features from AI-learnedpatterns/structures and clinicalguidelines.7. Co-design a prototype tool,through iterative review and refinement of feedback systems –participating clinicians, who undertake SMRs will participate in“think-aloud” studies of the protype tool and identify positive andnegative features of the tool which will allow the iterative improvementof the prototype (co-developed with patient and publicrepresentatives).8. Refine the laterprototypes through user-group feedback and, through two workshops, toexplore further the perceived strengths and weaknesses and thus theimplementability of the system.The objectives of the DynAIRx project are to:DynAIRx involves a combination of qualitative stakeholder engagement , large-scale health informatics and co-development/iterative analysis  to harness linked data across primary, secondary and social care to createvisualisations of patient journeys, risk-prediction estimates and prescribingdashboards to support SMRs. DynAIRx will harness the emerging integrated recordsmandated for NHS Integrated Care Systems to coordinate services across providers.Through statistically robust approaches, it will predict avoidable multimorbidityand harm resulting from medications.The DynAIRx qualitative studies will explore the perceptions of key stakeholderson how SMRs are currently being undertaken and what the barriers andfacilitators are to making them effective and efficient. The research adopts adescriptive and exploratory methodology, and is based on qualitative data fromparticipants regarding their current and retrospective experiences of SMRs. ThisinThe qualitative studies will also explore the opinions of key stakeholders on theprototype prescribing audit & feedback tools that are developed to supportSMRs, informed by analysis of patient journeys and AI-assisted integration ofcare records. This will be undertaken through one-to-one think-aloud studies andmixed-participant workshops.Key stakeholder participants involved in the qualitative work include generalpractitioners, pharmacists, secondary care physicians, patients withmultimorbidity and policy makers. Key stakeholder groups are defined in 1. What are the barriers and facilitators to theuptake and utilisation of an AI-augmented prescribing support systemfor SMRs from the perspective of primary and secondary careclinicians, pharmacists, patients, and commissioners/managersinvolved in SMR services?2. What arethe features that would make such a resource acceptable andusable?Research questions of DynAIRx Qualitative–Needs analysis and requirementsengineeringSemi-structured one-to-one interviews will be undertaken with a broad range ofrepresentatives from Primary Care Networks, GPs, pharmacists (primary care andchief), clinical pharmacologists, practice managers and patients to understandtheir priorities for such reviews and potential barriers/facilitators toimplementation.Semi-structured interviews will allow us to elicit participant personal feelings,opinions, and experiences, and help the researchers to gain insights intobarriers and facilitators to future uptake of the proposed systems.Semi-structured interviews will be followed by broader focus group discussion (1-2groups) across the 5 stakeholder groups (4-8 participants per focus group). Thetotal number of participants will depend on the themes that emerge and therequirement for further exploration. Focus group interview guides will beco-developed to address the key research questions, enhanced by themes that emergefrom the initial one-to-one interviews.Prescribers’ requirements for support with SMRs will be identified across the keygroups. This will include insight into data-driven medication reviews, includingwhat clinicians consider high-risk vs high-volume prescribing. Work will also focuson clinical uncertainty. For example, exploring prescriber needs in high-risksituations, such as severe mental illness, where stopping an antipsychotic may notbe viable, yet the dose could be adjusted to a safer level, or an alternative drugwith lower cardiovascular risk could be prescribed. Discussions will explore howmedications might be best prioritised for older people living with frailty, andpeople with complex multimorbidity, including using the The National Institute forHealth and Care Excellence (NICE) Database of Treatment Effects and ScottishPolypharmacy Guidance.Task-based workshops/focus groups may be supported by ongoing, semi-structuredqualitative interviews with stakeholders, including Clinical Commissioning GroupLeads and Chief Pharmacists, alongside patients and carers across our key groups.All workshops/interviews will be audio-recorded, with participant consent, andtranscribed for thematic analysis.Semi-structured interviews (∼10-20 participants across 5 stakeholder groups) andfocus groups (1-2 per stakeholder group involving 4-8 participants) will beundertaken via video conference (or telephone for one-to-one interviews). The groupsare deliberately small to engage effectively and allow for open discussion and toobtain the views of a broad range of practitioners nationally to examine the currentscope of practice. Participants will contribute their expertise from community,primary and secondary care practice.Patient and carer representatives:a. Multiple (4 or more) long term healthconditions.b. Co-existingmental and physical healthproblems.c. Prescribed ≥10regular medications.d.Frailty.1. Individuals with (or carer for someone with) any of the followingcriteria:2. Age 18 or over.Health care/management professionals:1. Working inhealth care setting where review of prescription medications is aregular part of the clinicalworkload.a. Generalpractice.b. Secondary care.c. Clinicalcommissioning of services or management of clinicalservices (practicemanagers).d. Pharmacist.2. Working in key stakeholdergroups including any of:Health care or management professionals :Patient and carer representatives:• Unable to give informed consent to participate.• History of hearing or speech impairment to a degree that wouldrender normal conversation impossible via video interview and thisis their only option; however, all participants who have suchimpairments who wish to participate would be offered the option of aface-to-face meeting, along with necessary adjustments, to ensureinclusivity.• Unable to communicate in English.Health care professionals:• Not involved with prescribing• Outpatient clinics forlong-term conditions.• Via socialmedia  email to the qualitativeteam.• Via networking at events.12 The researchteam will be provided with restricted details  of CARE75+ participants who meet the eligibilitycriteria by the CARE75+ study team. Only CARE75+ participants whohave already given consent to be approached for future researchstudies, including provision of this restricted data, will beapproached. Study information will be mailed to the potentialparticipant by the research team, who will subsequently contact thepotential participant to discuss the study and whether they areinterested in beinginvolved.•Sampling the CARE75+ cohort participants with frailty, at theUniversity of Leeds. Frail participants are defined using either thephenotype model, or as having mild/moderate/severe frailty using theelectronic Frailty Index.•Charities including Age UK and Mind. Working in partnership with thecharity, patient information sheets will be sent to charities fordistribution through their networks.•Mental health directorate expert patient reference groups andpatient liaison group to engage serviceusers.Patient and carer participants will be recruited via a variety of networksincluding:• Individual one-on-one semi-structured interviewswill be conducted over telephone or video conferencing with 1-2members per key stakeholder group .• Demographic  and professional information will be collected fromHealth Care Professionals (HCPs)  prior to startingthe interview.Supplementary Appendix1).• Prompt questions asper interview guide  will be co-created with experts byexperience  focused around key areas of interestincluding:• What data do prescribers/practices need toundertake effective Structured Medication Reviewsefficiently?• How are StructuredMedication Reviews currently being undertaken, by whom,where, andhow long do they take?• What kind ofdigital tools and supports will be mostuseful?• What do participants considerthe top priority target medication challenges relating to keymultimorbidity groups ?• What are likelybarriers/facilitators to uptake and utilisation and sustained use ofAI(-augmented) tools?An interview guide  to contain approximately 4-8 participants.• Demographicinformation will be collected prior to the focus group fromparticipants.• Minimal informationwill be collected from HCPs , years trained, grade  prior tostarting the focus group.Supplementary Appendix2).• Theco-produced topic guide will be followed to structure the focusgroup .1. What combinations of diseases, medications, investigations andclinical contacts are associated with the greatest degree of adverseoutcomes in patients with high risk of harm ?2. Can patient journeys over time and across care providers beadequately visualised in the context of clinical guidelines and beenriched with causal inference methods?3. Can a learning system be created that incorporates the needs ofprescribers and patients alongside the key high-risk trajectoryindicators?Datasets will be created within Trusted Research Environments (TREs), makingclean data available for further analysis. A federated approach to clinical datawill enable access to structured data from across Cheshire & Merseyside, GreaterManchester, and Yorkshire & Humber, covering a population of ∼11m fromexisting regional shared care record systems, which provides research access andprescriber audit and feedback.Core research datasets will be curated and maintained from these integratedgeneral practice, hospital, and social care records, where available. Accredited(ISO27001/NHS DSPT) cloud-based TREs support the software, tools, compute, andgovernance for research access. These federated data sources will feed a minimumcore dataset (MCD) for evaluation and deployment – including coded datafromgeneral practices as well as Secondary Uses Service data from hospitals andstructured community and mental health datasets, where available.13 and AVERT .14 The data include over four billion annotations over 12years in a large mental health and community provider trust, plus inputs fromother regions. To extract (de)prescribing events, related drugs and contextsacross narratives will be identified. This involves named entity recognition fordetecting drug name or label variations; context extraction, such as treating anadverse effect of another drug; and entity mapping across time and/or sources,including extraction of time references for tracking prescribing journeys. Thesedata can then be linked and validated against the routinely collected andintegrated care record data.The MCDs will be extended, where available, with information extracted from, andtracked across, clinical narratives using NLP-contextualised language modelssuch as BERT. This builds upon existing healthcare NLP applications andannotated datasets, such as WEB-RADR (extracting events related to adverse drugreactions)A data catalogue will be maintained. A federated and open-source approach will betaken to data analyses – sharing all code via a GitHub public repository.The structured data that have been curated and processed will be analysed todiscover clusters of multimorbidity and polypharmacy with high apparentprescribing harm in the key multimorbidity groups. Machine learning andstatistical methods will be used to develop prediction models for adverseoutcomes, and to estimate which patients may benefit most from a structuredmedication review.Adverse outcomes may include events such as falls in older people with frailty;strokes in people with severe mental illness, diabetes, and hypertension; andhospitalisation for adverse drug reactions or emergency/unplannedhospitalisations. Patterns indicating adverse outcomes or sentinel events suchas prescribing cascades will be extracted from the curated data. Patienthistories will be modelled as temporal graphs capturing clinical events in their timeline, and extracted using 3Dconvolutional neural networks. This will exploit recent advances in video andtime-series classification to discover temporal patterns and not just sequencesof events . The output will be a time-seriesof clinical feature vectors, which can be used to predict outcomes or to defineclusters of typical patient trajectories. Soft, temporal clustering algorithmswill be used to track a patient’s membership of each cluster over their recordedhistory. For instance, they may move gradually from a low-risk cluster to acluster with high risk of hospitalisation. The identified patterns/clusters willbe visualised and user feedback  usedto refine the AI .The distilled patterns/clusters will be used to generate hypotheses, followed bydevelopment of explainable information. To reduce the risk of posing spuriousassociations  as causal relationships, an expertpanel will be called upon for potential reference. Where available, causalestimates will be derived from randomised controlled trials, or other robustexternal sources such as Mendelian randomisation studies. When required, causalestimates may be derived from the data in-hand using g-methods.Visualisation and expert clinical and evidence-based reasoning are key in 1)informing the construction of graphical models to represent causal relationshipsbetween variables, and 2) weighing the plausibility of identified putativecausal relationships. Where a causal relationship is in doubt, it will beexamined within the key stakeholder groups . The models also forma strong basis for future work to identify anticipated benefits (effect sizes)of potential interventions such as deprescribing at an individual patient level.In principle, such tools can be used to support clinicians performing medicationreviews , as risks of multiple outcomes can beevaluated and discussed under different intervention strategies.Particular attention will be paid to explainability of AI, focusing on featureimportance, rule extraction and consistency in individual risk predictionbetween AI models with comparable population-level performance. In contrast to‘black box’ AI approaches to prediction, the methods utilised here are anchoredin causal inference, explicitly handling causality. Causal queries are used togenerate predictions under hypothetical interventions, which naturally ensuresmodel explainability. Explainability and temporality are also embedded in theclustering approaches , and the visual summaries . Data sparsity is explicitly represented as uncertaintywithin directed acyclic graphs prompting requests for further data orexperimentation. Counterfactual causal reasoning will be used to identify andminimise possible biases and unfairness in our models.15 This methodology will consider how risk predictionsvary between clinical sites .Bias due to confounding factors  anddata quality will be mitigated via a systematic bias assessment as part of thestatistical learning and clustering for multimorbidity prediction. Theconsistency of AI results in individual predictions for models with comparablepopulation performance will be evaluated and the effects of hyperparametersexplored; models with acceptable hyperparameters can yield varying individualpredictions.Creating visual summaries has four stages. First, implementing functionality toextract and aggregate prescribing/disease events at cohort/patient andlongitudinal/cross-sectional/overall granularities using curated data. This willprovide a stable application programming interface (API) to connect care recordsystems to DynAIRx prescriber dashboards, in order to detail the ‘chronicles ofevents’ identified by the key stakeholder groups in DynAIRx qualitative.17; and 2) the QualDash engine,already deployed in cardiology and paediatric intensive care .18Second, exploring alternative approaches for presenting interactive visual summariesof prescribing and disease events. Standard single-screen dashboards will provide abaseline but are unlikely to satisfy GP/pharmacist’s requirements. Exploringdashboard designs from two approaches better suited to multifactor, temporallycomplex data: 1) dashboard networks, where dozens of types of events of interest aresummarised in a miniature dashboard, which are connected in a network to portraytemporal changes between patients/cohortsStage 3 will compare the pros and cons of the alternative approaches withGP/pharmacist end-users, selecting and then implementing the best approach . This stage will incorporate data generated bystatistical learning and clustering to provide visual summaries and drill-down ofpatient histories in the context of patient clusters, trajectories, drug-druginteractions and clinical guidelines. It will also provide customisablefunctionality needed to present the patient event summaries in the context offeature spaces from the statistical learning output, which will be invaluable for:(a) identifying features that distinguish one step from the next in patients’journeys, and clusters of patients from each other, and (b) gaining clinical inputabout the explainability of the models.The final stage, evaluation, includes the development of a user guide and quick starttutorial, and hands-on evaluation with GPs/pharmacists performing StructuredMedication Review scenarios .Translation of research findings into daily clinical practice is a major challenge.There is considerable need for clinical decisions to be based on the best availableevidence, but often this evidence is not available  andguidelines are only generic and usually relate to single conditions. It also needsto be balanced against clinician and patient/carer choice and preference,affordability according to local formularies, and congruence about goals andmanagement plans between professionals and patients/carers to enhance sharedagreement about treatment regimes.19 This approach involves iterative phases including dataanalytics (data to knowledge), feedback to clinicians (knowledge to performance) andimplementation of quality improvement activities by the clinicians (performance todata). The cycle of the Learning Healthcare System starts again by evaluating theeffectiveness of these quality improvement activities. The analytics phase includesa detailed data analysis of the opportunities and challenges in current clinicalpractice and the local site . The results of the analysis would enable identification of carepathways and conditions ripe for focused targeting for improvement. The second phaseinvolves review by the clinicians of these results and decide which have sufficientcredibility to generate recommendations for change, ideally customized to its ownspecific circumstances. The third phase involves implementation of theserecommendations by clinicians. Cluster trials have reported that data feedback canbe effective in optimising prescribing.20 The effectiveness of datafeedback has been found to depend on content and how the feedback is providedincluding visualisations.10 Feedback on simplistic targets may lack effectiveness  areongoing. AI approaches found that medication patterns were strongly associated withADR-related hospital admission (Odds Ratios [OR] of 7) and emergency admission (ORsof 3). Analyses of multiple drug-drug interactions with antibiotics  are providing information on relative as well asexcess absolute risks. Analyses of medication reviews in polypharmacy patients foundlimited changes in prescribing in before-after analyses, highlighting the need forbetter evidence and support. Techniques such as random forest and gradient boostingmethods will be used in this project to identify challenges and higher rates ofadverse outcomes in medicine combinations used by our study populations. This willbe followed by practice and peer comparisonsA recent BRIT2 clinical pharmacist (CP) workshop examined analytics-based input tosupport Structured Medication Reviews (SMR) for polypharmacy patients. CPs wereinterested in analytics which indicate the clinical risk of BNF drug-druginteractions, identify problematic prescribing patterns in the community , and target medication reviews towardhigh-risk patients. CPs felt that they were currently overloaded with informationand popups as existing systems did not fit with the way they work. They were veryclear that any tool would need to be very well targeted, user-friendly and have goodexplainability, which is very important as CPs must rationalise medication changeswith other clinicians and patients and cannot ‘just trust the data’.25 Participating clinicians, who undertake Structured MedicationReviews in Liverpool, Manchester, Leeds and Bradford, will receive novel reports tosupport reflective practice concerning their patients with notable multimorbidityand polypharmacy issues in our key areas of study. The reports will extend the BRIT2platform.11 BRIT2 includes general practices in northern England. Technicalspecifications have been agreed for embedding/enhancing BRIT2 in the GraphnetIntegrated Care Record System as part of the CIPHA expansion programme, whichcurrently covers North West England and parts of the Midlands and South England.Data will be analysed in the TREs and the results fed back to practices viapractice-specific dashboards.Prescribing dashboards to support SMRs will be co-developed with key stakeholdergroups and deployed in an existing prescribing audit and feedback used byGPs.Patterns of conditions, medications, tests, and clinical contacts antecedent to themultimorbidity events uncovered and the novel visualisations created will beincorporated into prescriber dashboards. DynAIRx qualitative engagement will helpshape this content into forms that clinicians and practices find useful. Variabilityin multimorbidity-related prescribing across practices/prescribers will be studiedas part of this. This will build on BRIT2 which is currently analysing large cohortsof elderly patients with national primary care data extracts . These results will be used for benchmarking underexisting ethics approvals. Each practice population of multimorbid patients will bematched by propensity for adverse outcomes, morbidity cluster and data quality. Thismatching helps show where a practice deviates from its peers. As part of DynAIRxqualitative engagement, clinicians will be able to comment on dashboards, providingfeedback to researchers on the acceptance of the results. The applicability ofsocial-norm, practice/prescriber-level feedback to medicines optimisation inmultimorbidity will be studied with key stakeholders, with particular considerationof the scale achievable at low cost through AI.Analyses for each iteration of feedback will be prioritised by users . A particular focus will be quantification of the absolute risks ofinteractions and, where possible, presence of effect modifiers (such as level ofpolypharmacy).At least two cycles of updating practice-tailored dashboards will be applied . The effects of the feedback will be studied within statisticallearning and clustering for multimorbidity prediction using interrupted time seriesmodels and recurrent neural nets.Research questions of DynAIRx Qualitative Phase 2 – Prototype iterativeanalysis1. What are the strengths and weaknesses of the AI-augmented prototypedashboard and prescriber reports?2. What improvements could be made to ensure the AI-augmented processachieves maximal clinical utility?Two rounds of one-to-one ‘think-aloud’ studies on prototype systems will beundertaken with a small group of clinicians to understand perceived strengthsand weaknesses of the prototypes and to iteratively refine them. Participantswill be asked to comment on components of the systems, with prompts andquestions to elaborate responses. Participants will be encouraged to suggestimprovements and explain what they like/dislike, which aspects are (not)intuitive, and how they envisage using such systems in real-life. Findings willbe shared immediately with dashboard developers to refine prototypes ahead ofthe next think-aloud study.• Eachthink-aloud study will consist of one participant, and will takeapproximately 2 hours.• Approximately4-6 studies will occur per iteration of theresource.• Participants will be given abrief task sheet for them to work through utilising aspects of theonline resource/dashboard, taking approximately 2hours.• Participants will be asked to talkthrough what they are doing as they are completing the tasksheet.• Following this, participantswill be asked to provide any general thoughts or feedback from theirinteraction.• Think-aloud studies willbe audiotaped and transcribed to ensure no feedback ismissed.Approximately 10 think-aloud studies are planned across a variety of potentialusers. They will be recorded and transcribed and the transcripts thematicallyanalysed. Data relating to implementation will be conceptualised through aNormalization Process Theory (NPT) lens. Comments will be noted to be eitherpositive, where the user liked or identified with what they saw, or negativewhere the user disliked or disagreed with what they saw, or where the usersuggested improved content, presentation, or interaction.Stakeholders will also critique each major new version of the system in twoworkshop events – one for each development iteration. Emerging findings will beshared with the health data analysts, ensuring that statistical learning andvisualisation are informed by clinician, commissioner and patient insights.Following the development of the final DynAIRx prototypes, we shall present themto the wider group for feedback to enable further discussion of perceivedstrengths and weaknesses and to address future implementability.We will audio record and transcribe the sessions and thematically analysetranscriptions as described earlier. Comments will be noted to be eitherpositive, where the user liked or identified with what they saw, or negativewhere the user disliked or disagreed with what they saw, or where the usersuggested improved content, presentation, or interaction.Think-aloud studies and workshops will be organised face to face, ideally in thepractitioner's own place of work where possible and practical to obtain the mostreal-world usage data. However, these could also be undertaken remotely if feltappropriate, for example, if pandemic restrictions were to be re-introduced orat the preference of participants. Both primary and secondary care practice willbe covered.The recording of the interviews will be transcribed and anonymised . The digital recordings will beheld securely at the University of Liverpool or University of Glasgow, withsecure file transfers to/from the transcription company. Once the transcriptsare checked against the audio files, those audio files will be deleted.The socio-demographic information, including information on HCP roles, of theinterview and focus group/workshop and think aloud study participants will beentered into a spreadsheet and then exported into NVivo software to create casenodes. Tables will be constructed summarising the socio-demographic and roledata. The case nodes will facilitate the comparability of themes within andbetween groups and across the different study contexts.27All semi-structured interviews, focus groups, think-aloud studies and task groupswill be audio-recorded and transcribed verbatim to form the data for analysis.Transcripts will be read and re-read and a thematic analysis will be undertakenusing Braun and Clarke's six step framework for thematic analysis which combineselements of deduction and induction whereby some themes are expected to be foundin the data based on the literature or the theoretical framework  and others appear by themselves duringanalysis.28 This approach essentiallyinvolves an exploration of the data to identify patterns, themes and/ortheoretical constructs. This involves detailed reading of the transcripts andidentifying all key issues, concepts and themes, drawing on a priori issueswhile being alert to new ideas raised by the participants.The six steps are: familiarization, coding, generating themes, reviewing themes,defining and naming themes, and writing up29 NPT has been widely usedto consider how individuals and groups understand, integrate, and sustaindigital or new ways of working (e.g. SMRs) into everyday practice, and hasenhanced (understanding of) implementation processes.30This work will help us understand stakeholder priorities for SMRs and potentialbarriers/facilitators to implementation. Once themes are finalised, they will bemapped onto the constructs of NPT: coherence (sense making); cognitiveparticipation (engagement work); collective action ;and reflexive monitoring , where appropriate. The data will not beforced to fit the constructs of NPT. NPT will instead be used as a theoreticallens with which to interrogate the findings.Data analysis will be carried out by the DynAIRx clinical researchers and thepost-doctoral research assistants (PDRAs). Coding clinics will be undertaken torefine the themes identified and ensure consistency of coding across the team. Acommon analytical framework will be developed to ensure consistency in analysisacross the various study locations. The analytical framework would be flexibleand iterative and continuously refined as the analysis evolves. NVivo softwarewill be employed to organise the data, and help manage the data analysisprocess. All the DynAIRx clinical researchers will be trained in how to use thesoftware. Data analysis will be undertaken in parallel with data collection.This will help the researcher determine whether saturation has been reached onany of the research questions and to identify gaps for further datacollection.Any quotations used in any reports will be anonymised.The study has been approved by the Newcastle North Tyneside Research Ethics Committee(REC reference:22/NE/0088). No safety concerns were identified. Study findings willbe presented at public meetings, national and international conferences andpublished in peer-reviewed journals.DynAIRx will provide patient benefit by: a) targeting medication reviews/optimisationto those most at risk from harm due to problematic polypharmacy and most likely tobenefit from SMR; b) reducing the risks of drug-related harms; c) freeing upclinician time for patient interaction through automated data collection forstructured medication reviews; and d) providing a clear, visual summary of diseasetrajectories to inform clinician/patient discussion.1. Evaluation ofkey challenges and opportunities around medicine optimisation in generalpractices2. A pipeline of structured andunstructured care data into multimorbidity (AI)research.3. An AI framework for identifyingthose most at risk of problematic polypharmacy and for discoveringdisease trajectories that should trigger high prioritySMRs.4. Novel visualisations of patientjourneys enhancing medication reviews.5.Integration of outputs 1 – 4 to produce a clinically useful learninghealthcare system, co-developed by the end users and supporting thedelivery of SMRs by GPs and pharmacists and be accessible topatients/carers.Key outputs from DynAIRx  we will build multimorbidity decision support onDynAIRx visualisations and outcome predictions, for use in consultations.Click here for additional data file.Supplemental Material for The DynAIRx Project Protocol: Artificial Intelligencefor dynamic prescribing optimisation and care integration in multimorbidity byLauren E Walker, Aseel S Abuzour, Danushka Bollegala, Andrew Clegg, Mark Gabbay,Alan Griffiths, Cecil Kullu, Gary Leeming, Frances S Mair, Simon Maskell, SamuelRelton, Roy A Ruddle, Eduard Shantsila, Matthew Sperrin, Tjeerd Van Staa, AlanWoodall and Iain Buchan in Journal of Multimorbidity and Comorbidity


Recurrent cervical cancer has a grim prognosis with 5-year survival <5%. Current treatment options are limited; standards of care such as palliative chemotherapy and surgical resection often provide a small survival advantage. To date, only one targeted agent has FDA approval for the treatment of recurrent cervical cancer. We present the case of a novel application of olaparib, a poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitor, as single-agent therapy for recurrent metastatic clear cell cervical cancer in a patient with a somatic BRCA2 mutation. The patient had excellent response to therapy with stable disease without evidence of progression until 14 months of therapy, at which time she was switched to an alternative regimen. Recurrent cervical cancer of any histologic type poses a grim prognosis. Women diagnosed with recurrent disease have a 5-year survival of <5% . DecisioClassically associated with in utero diethylstilbestrol (DES) exposure, clear cell adenocarcinoma of the cervix remains a rare subtype of cervical cancer. Treatment regimens are similar to other adenocarcinomas of the cervix, as response to treatment and prognosis between subtypes is comparable .We describe a clinical case of a patient with recurrent, metastatic, clear cell cervical adenocarcinoma who was treated with single-agent olaparib, a PARP-inhibitor, with robust and durable response to therapy.∗) c.5217_5223delTTTAAGT mutation, which is a nonsense mutation changing tyrosine to a stop codon within coding exon 10. This variant has been identified as a germline variant; the patient declined genetic counseling and germline genetic testing [The patient is a 48-year-old G1P1 patient who presented to an academic gynecologic oncology practice as a referral for abnormal uterine bleeding and was ultimately diagnosed with stage IIB clear cell adenocarcinoma of the cervix based on a 7 × 7 × 2 cm invasive carcinoma with involvement of the upper 1/3 of the vagina and parametrial invasion. Imaging including CT and PET/MRI was without evidence of lymphadenopathy or distant spread. Due to her diagnosis of stage IIB cervical cancer, she was referred to radiation oncology for counseling on concurrent chemoradiation. Tumor genomics via Next Generation Sequencing were performed at time of initial referral demonstrating BRCA2 p.(Y1739 testing . She undShe then attended surveillance visits, with no evidence of disease, until presenting to the emergency department with a second saddle pulmonary embolism after self-discontinuation of DOAC one year prior. Imaging performed at that time demonstrated numerous new solid and cystic metastatic lesions in the abdomen and pelvis with lesions along the liver capsule and peritoneum. Ultrasound-guided biopsy demonstrated carcinoma consistent with metastasis from the patient's known primary cancer. Progression-free survival time to first recurrence was 18 months.Discussion regarding options for treatment of recurrent cervical clear cell carcinoma included traditional systemic chemotherapy regimens as well as consideration of previous tumor genomics result that demonstrated a somatic BRCA2 mutation. Upon discussion with the patient regarding results of molecular testing, along with recommendations from our institution's precision medicine molecular tumor board, we decided to initiate therapy with twice daily oral olaparib. The medication was approved by her insurance with the somatic BRCA2 mutation data and documented recommendation from the institutional molecular tumor board. Repeat CT scan prior to initiation of PARP-inhibitor demonstrated continued enlargement of numerous masses within the abdomen and pelvis consistent with worsening disease.After 3 months of treatment with single agent olaparib, repeat CTAP demonstrated interval decrease in tumor burden. Six- and 9-month surveillance visit imaging demonstrated continued interval decreases in tumor size and burden. Her dose was decreased at 9 months of treatment due to decreased GFR according to FDA package insert. At her 12-month surveillance visit, exam, and imaging was consistent with stable disease without evidence of interval progression . ResponsThe patient continued on olaparib for 14 months, at which time she developed symptoms concerning for progression which was confirmed on imaging. She was counseled on options and was transitioned to systemic chemotherapy with cisplatin, paclitaxel, and bevacizumab.Recurrent cervical cancer of any histologic type is associated with a 5-year survival of <5% . TreatmeCarboplatin-paclitaxel has become the standard of care for patients with high risk for nonresponse to cisplatin , 2. The Investigations into alternative options have revealed promising targets, with several studies attempting to capitalize on mutations in cervical cancer tumors. The Keynote-028 and Keynote-158 trials demonstrated durable, well-tolerated response to pembrolizumab, an immune checkpoint inhibitor which binds to PD-L1 in patients with PD-L1 positive tumors –9. PembrAside from the above-mentioned therapies, few options exist for treatment of distant metastatic cervical cancer. Several other antiangiogenic agents have been studied for treatment of cervical cancer, including sunitinib, pazopanib, lapatinib, and cediranib. While initial studies of these molecules have been promising, with some demonstrating improved progression-free survival, to date no other antiangiogenic molecule has been shown to meaningfully impact outcomes via improved overall survival , 9.Olaparib is a PARP-inhibitor, a class of drugs which targets the DNA repair mechanism present in tumor cells, blocking the ability to fix DNA single-strand breaks leading to a greater degree of DNA double-strand breaks. In patients with BRCA mutations who thus have a homologous recombination repair deficiency, these double-strand breaks lead to a greater degree of cell death which is more pronounced in the molecularly deranged malignant cells. PARP-inhibitors have been utilized in multiple cancers and patients with germline and/or somatic BRCA mutations as a method to remove the tumor's back-up method of DNA repair. The utilization of PARP-inhibitors for treatment of recurrent or metastatic cervical cancer has theoretical plausibility. Several studies have demonstrated increased rate of BRCA mutations in cervical cancer tumors , 13. An Two trials have evaluated treatment of recurrent or metastatic cervical cancer with the PARP-inhibitor veliparib, in combination with other therapies already in use for treatment of cervical cancer , 15, 16.To the authors' knowledge, no trial has been initiated evaluating use of olaparib in the treatment of recurrent or metastatic cervical cancer. Additionally, existing trials and case reports have not investigated single-agent PARP-inhibitor therapy. This case report documents durable response to single-agent PARP-inhibitor therapy with olaparib in a patient with recurrent cervical cancer with distant metastases. The patient had significant partial response to therapy with some lesions responding completely and others with a more modest response; recurrence developed at 14 months after initiation of treatment.Recurrent cervical cancer with distant metastases has limited treatment options with an extremely poor prognosis, with overall survival for these patients estimated at 1-1.5 years , 9. DespBiological plausibility exists for treating recurrent cervical cancers with gene-specific or targeted therapies. As documented above, multiple studies are currently underway evaluating targeted therapies alone or in combination with current standard of care treatments. Future studies should investigate the utility of olaparib in the treatment of recurrent cervical cancer, both alone and as a combination therapy. As the patient in this case report has a diagnosis of clear cell adenocarcinoma of the cervix, further studies should evaluate efficacy of PARP-inhibitors in patients with squamous cell or other subtypes of cervical cancer. Further evaluation of cost effectiveness of routine vs. selective analysis of cervical cancer tumors via tumor genomics with Next Generation Sequencing may be beneficial. Evaluation of cervical cancer tumors with tumor genomics may offer insights for predicting potential response to targeted agents, as review of the literature demonstrates that many tumors may exhibit potentially targetable mutations.In this patient with a distant recurrence of clear cell cervical adenocarcinoma with a somatic BRCA2 mutation, treatment with single-agent olaparib resulted in a durable response of 14 months with limited toxicity. While several other studies have demonstrated biological plausibility of treatment of recurrent cervical cancer with PARP-inhibitors, to the author's knowledge this is the first case report documenting in vivo success with single-agent olaparib and response to olaparib in this patient has outlasted currently available data from trials evaluating other PARP-inhibitors in the treatment of cervical cancer.


The following case report is an overview of an unusual presentation of bilateral axillo-brachial artery occlusion following messenger ribonucleic acid (mRNA) vaccination against severe acute respiratory coronavirus 2 (COVID-19). A 64-year-old female presented with symptoms initially consistent with polymyalgia rheumatica five weeks following the first booster of the Pfizer-BioNTech COVID-19 vaccine. She was successfully treated with prednisone therapy; however, despite the normalization of inflammatory markers, she later presented with bilaterally occluded axillo-brachial arteries. She successfully underwent endovascular management for the treatment of her symptoms. To our knowledge, this is the first case report of chronically occluded bilateral axillo-brachial artery disease following mRNA vaccination for COVID-19 successfully treated with endovascular therapy. The unusual pathogenesis of upper extremity arterial disease is reviewed and a review of endovascular treatment options is presented. A literature review of the types of vasculitis seen following mRNA COVID-19 vaccination is also presented. The following case is an overview of an unusual presentation of bilateral axillo-brachial artery occlusion following the messenger ribonucleic acid (mRNA) vaccine against severe acute respiratory coronavirus 2 COVID-19). Upper extremity occlusive vascular disease and, in particular, axillo-brachial artery stenosis is uncommonly encountered in patients [9. Upper The patient is a 64-year-old female with an unremarkable past medical history who began to develop upper extremity weakness and bilateral bicep muscle tenderness occurring five weeks following the first booster with the Pfizer-BioNTech  mRNA vaccine against COVID-19. She initially noticed right arm weakness while driving her vehicle which progressed to involve the left arm within one week. She subsequently developed fatigue, anorexia, hair loss, weight loss, and weakness. She had some jaw discomfort with mastication. She also complained of coolness on the dorsum of her hands. She denied any fever. Neurologic evaluation including the brain and cervical MRI along with nerve conduction studies was unremarkable. She was subsequently seen by the Rheumatology team and was noted to have a significantly elevated sedimentation rate (50 mm/hour) as well as C-reactive protein levels (104 mg/L). Creatinine kinase levels were noted to be normal. Temporal artery ultrasound imaging showed no suggestion of temporal artery arteritis. On examination, she was noted to have bilateral weak pulses in her upper extremities with an inability to record blood pressure with an automatic cuff. She underwent initial evaluation with upper extremity arterial ultrasound studies which showed diminished flow velocities involving bilateral brachial, radial, and ulnar arteries without focal stenosis appreciated although the monophonic waveforms seen on the ultrasound were highly suggestive of proximal high-grade stenosis. In addition, some of the views of her left axillary artery were notable for abnormal intimal media thickening . Her presentation was felt to be most consistent with polymyalgia rheumatica (PMR) with possible arteritis. She was placed on prednisone 20 mg daily with significant improvement of symptoms within one week with normalization of inflammatory markers. She was weaned off of steroids seven months following her presentation with continued normalization of inflammatory markers.Given persistent bilateral weak pulses and the inability to measure automated brachial blood pressures, she was referred to cardiology. The examination was notable for 1+ radial, ulnar, and brachial pulses. She underwent a CT angiography of the thoracic aorta and great vessels which was unremarkable. Distal subclavian and axillary arteries were not well seen. Given persistent coolness to the dorsum of the hands and some hand tingling, the patient elected to undergo an invasive evaluation of upper extremity vasculature. Angiogram was performed which revealed occlusion of bilateral axillary and brachial arteries with collateralization Figures .She was monitored clinically; however, given persistent symptoms, her case was discussed with the vascular team and an initial endovascular revascularization approach was recommended.Initially, revascularization of the left brachial artery was planned. Access was obtained from the left radial artery as well as the right common femoral artery utilizing ultrasound guidance. Heparin was used as an anti-thrombotic agent. The left subclavian artery was engaged with a 6-French Judkins right 4 guide catheter  and brought in proximity to the occlusion with the aide of a 0.035-inch wire. Subsequently, the proximal occlusion was traversed from a retrograde approach with a Trailblazer catheter  in conjunction with a knuckled Terumo glidewire . Subsequently, a Mongo 0.014 inch Asahi wire  was utilized to complete the crossing of the lesion; however, the Trailblazer could not be traversed more proximally. At this point, a balloon angioplasty was performed with Trek 1.2 × 12 mm as well as 2.5 × 30 mm balloons . Subsequently, the lesion was easily wired in an antegrade fashion. A 4 × 100 mm AngiogSculpt balloon  was used for angioplasty which led to excellent flow into the arm with no hemodynamic gradient seen across the stenosis . Post-angioplasty, there were good angiographic results without significant gradient across the diseased segment  is an uncommon presentation in patients with upper extremity arterial disease, with innominate and subclavian stenosis being more common entities largely attributable to atherosclerosis . The disNumerous modalities have been utilized for the treatment of brachial artery stenosis. Treatments ranging from standard balloon techniques in addition to stenting with bare metal stents, angioplasty with drug-eluting balloons, atherectomy as well as surgical revascularization have been reported in the literature -12. No dThe association of vasculitis with COVID-19 mRNA vaccination has been described. Case reports have included cases of immunoglobulin A vasculitis, lymphocytic vasculitis, anti-neutrophilic cytoplasmic autoantibody-associated vasculitis, leukocytoclastic vasculitis, urticarial vasculitis, and immune complex vasculitis -15.In early 2022, several case reports of large vessel and GCA developing after mRNA COVID-19 vaccination were published with multiple authors demonstrating the utility of fluorodeoxyglucose-positron emission tomography in conjunction with computed tomography imaging for diagnosis -24.Interestingly, some centers have reported an increased incidence of GCA during the COVID-19 pandemic . FurtherThere has been some concern that mRNA vaccination can disrupt endothelial function, with a study demonstrating decreased brachial artery flow-mediated vasodilatation following the second dose of the mRNA vaccine .It is, however, encouraging that a global pharmacovigilance study to investigate the risk of GCA and PMR following mRNA vaccination for COVID-19 did not demonstrate an increased reporting of these diseases when compared to reporting for side effects following vaccination for influenza in a World Health Organization global individual case safety report database .This case report illustrates that techniques developed for the endovascular treatment for chronic occlusion of lower extremity vasculature can also be utilized to revascularize chronic occlusion of upper extremity vessels. These endovascular options allow patients an effective treatment strategy for improved quality of life without significant morbidity. A review of the literature suggests that endovascular treatment options provide favorable long-term outcomes for patients. Emerging case reports suggest that there is a possibility of an association between the mRNA vaccine against COVID-19 and large vessel vasculitis. Case reports need to be followed to determine whether these associations are merely seen by chance in patients who were likely to show a phenotype of vasculitis regardless of being vaccinated against SARS-CoV-2. The possibility that vaccination could be potentiating an underlying mechanism for large vessel vasculitis in patients with an underlying susceptibility to this disease needs to be investigated.The possibility of upper extremity occlusive disease should be considered in patients who present with unusual upper extremity symptoms following COVID-19 or vaccination against COVID-19. Endovascular options allowed this patient to undergo revascularization without significant morbidity. If restenosis develops in this patient, further endovascular options include angioplasty with drug-eluting balloons versus utilization of stenting or surgery. In the short term, the patient remains free of vascular complaints.


Nail changes are a well-known phenomenon in T-cell lymphoma but have not been reported as widely in B-cell lymphomas and Hodgkin lymphomas. We describe a patient with a history of diffuse large B-cell lymphoma in a background of nodular lymphocyte predominant Hodgkin lymphoma treated eight years prior who developed new nail changes that were noted on a routine surveillance visit. He had developed symptoms of painful fingertips that became white and required him to wear gloves even in warm weather, suggestive of Raynaud phenomenon. Due to a suspicion of a paraneoplastic phenomenon, a positron emission tomography-computed tomography was obtained, which showed fluorodeoxyglucose avid uptake involving the spleen and retroperitoneal, para-aortic, and right inguinal lymph nodes. Right inguinal lymph node biopsy was non-diagnostic and a splenectomy was performed. Pathology evaluation of the spleen revealed recurrent nodular lymphocyte-predominant Hodgkin lymphoma. Treatment was initiated with rituximab-based systemic therapy. The Beau lines grew out eventually with normal new nail growth and there was an improvement in Raynaud phenomenon after systemic treatment. Dystrophic nail changes are a well-known phenomenon described in T-cell lymphomas. Nail changes including discoloration, crumbling, onycholysis, Beau lines, ridging, pitting, thinning, etc., have been described in T-cell lymphomas , 2. RepoBeau lines are horizontal ridges and indentations that develop on nails. They are indicative of a systemic insult that disrupts nail growth when they appear on multiple nails, such as sickness or chemotherapy. Beau lines are known to appear secondary to Raynaud phenomenon , 4. RaynWe report a case of Raynaud phenomenon and appearance of Beau lines as an unusual clue to systemic lymphoma recurrence.A 68-year-old man had initially presented eight years prior to the current evaluation with worsening reflux symptoms and weight loss. A computed tomography scan of the abdomen and pelvis showed adenopathy in the mesentery, upper abdomen, and retroperitoneum including moderate splenomegaly around 14 cm with numerous ill-defined splenic lesions suspicious for lymphoma. A peri-gastric lymph node excisional biopsy revealed areas of typical nodular lymphocyte predominant Hodgkin lymphoma admixed with areas of diffuse large B-cell lymphoma in a T-cell/histiocyte-rich background. He was treated with six cycles of rituximab, cyclophosphamide, adriamycin, vincristine, and prednisone and achieved complete remission.His current presentation stemmed from his report at a routine surveillance visit of having developed new symptoms of painful fingertips that became white along with nail changes that appeared gradually over the preceding year. He reported needing to wear gloves even at room temperature to keep them warm. His nails revealed evidence of Beau lines with horizontal indentations Figure . AutoimmPathologic evaluation of the spleen revealed recurrent nodular lymphocyte-predominant Hodgkin lymphoma Figures , 3.Nail changes occasionally are a window into the systemic health of the human body. Among the numerous nail changes that are reflective of systemic disease, Beau lines are well described. Beau lines are horizontal indentations and ridges that denote nail plate effects of systemic insults at the time of initial nail formation, such as severe systemic illness, trauma or toxin exposure such as chemotherapy . Beau liThe pathophysiology of Raynaud phenomena is not well understood in the setting of malignancies. Impaired microvasculature, reduced production of vasodilators, and exaggerated response to vasoconstrictors have been postulated . Such vaThe new occurrence of Raynaud phenomenon or Beau lines should raise suspicion of a systemic process. In our patient, since he had a previous history of lymphoma, there was an immediate evaluation for evidence of disease recurrence. However, in a patient without a prior history of malignancy, a high index of suspicion for an evolving systemic disease is necessary to investigate secondary Raynaud phenomenon before embarking solely on symptomatic therapy.Our patient was treated for recurrent nodular lymphocyte-predominant Hodgkin lymphoma with rituximab with a good response. The Beau lines grew out eventually with normal new nail growth by six months after treatment Figure . There wIn conclusion, the appearance of new dystrophic nail changes should raise suspicion of systemic disease. Beau lines can result from Raynaud phenomenon, which can be a paraneoplastic manifestation of lymphoma and an early sign of recurrent lymphoma.


Biophys. J.2021, 120, 276633773963Brader et al. ]. We extend those findings by considering the effect of encapsulationon mRNA thermal unfolding with the observation that encapsulationin LNPs increases mRNA unfolding temperatures.Preservation of theintegrity of macromolecular higher-order structureis a tenet central to achieving biologic drug and vaccine productstability toward manufacturing, distribution, storage, handling, andadministration. Given that mRNA lipid nanoparticles (mRNA-LNPs) areheld together by an intricate ensemble of weak forces, there are someintriguing parallels to biologic drugs, at least at first glance.However, mRNA vaccines are not without unique formulation and stabilizationchallenges derived from the instability of unmodified mRNA and itslimited history as a drug or vaccine. Since certain learning gainedfrom biologic drug development may be applicable for the improvementof mRNA vaccines, we present a perspective on parallels and contrastsbetween the emerging role of higher-order structure pertaining tomRNA-LNPs compared to pharmaceutical proteins. In a recent publication,the location of mRNA encapsulated within lipid nanoparticles was identified,revealing new insights into the LNP structure, nanoheterogeneity,and microenvironment of the encapsulated mRNA molecules [ The goal of achieving more robust vaccine products connectsdirectly to the understanding of the underlying molecular interactionsand ultimately translating this knowledge into rational formulationdesign strategies.10 These connectionshave been well-developed for therapeutic proteins; however, for mRNAvaccines, structural details of the conformational state and physicochemicalenvironment of the mRNA within the lipid nanoparticle (LNP) formulationare only beginning to emerge. The central drug delivery challengeof mRNA is more formidable than for proteins because the mRNA moleculemust be delivered intracellularly whereas pharmaceutical proteinsremain limited to druggable targets outside the cell. An additionto this challenge is the intrinsic rapid biodegradability of mRNA.Although this is a favorable attribute from a safety and pharmacokineticperspective,11 unfortunately, it also conferssusceptibility to degradation in vitro. A more detailed understandingof the pathways specifically relevant to mRNA pharmaceutical instabilityis currently emerging.12 Similarly, althoughlipid nanoparticles have been studied as drug carriers for about 30years,13 the first approved product usingthis technology occurred only recently with ONPATTRO (patisiran) in2018.14The spectacular adventof mRNA vaccines as a rapid response tothe COVID-19 pandemic has ushered in a new front line in vaccinology.These vaccines combine the informational sophistication of the mRNAmolecule with the physicochemical architecture of lipid nanoparticlesto create a tunable drug delivery platform with great potential forbroadly versatile medical applications.15 This milestone waswell preceded by the crystal structure of pig insulin in 196916 with an elegant description of the underlyingfactors governing correct protein folding well-articulated by theearly 1970s.17 A pathway to improved proteinpharmaceuticals then unfolded (no pun intended), leveraging regulatoryprecedent and an understanding of the underlying structure and foldingto create improved sequences conferring greater pharmaceutical stabilityand/or improved therapeutic properties.18 The approval of Humalog in 1996 provided a striking example of thelatter, showing how even a subtle amino acid sequence modificationcould be engineered to dramatically alter insulin pharmacokineticsvia a physicochemical mechanism,20 thereby addressinga therapeutic need. These biomedical milestones stand on the shouldersof historic advancements in recombinant DNA technology, protein engineering,and structural biology at atomic resolution serving to emphasize thatthe route to better biomedical products is based firmly on understandingthe fundamental interrelationships among higher-order structure, biologicalactivity, and biomedical implementation, aka the molecular pharmaceutics.To create perspective, itis intriguing to consider the currentstate of mRNA biomedical technology relative to therapeutic proteinbiotechnology and the advances made preceding and following FDA’sapproval of the first recombinant DNA drug product, human insulin(Humulin), in 1982.21 Historically, structural studies of RNA in the 1960s were part ofa frenzy to understand their function in decoding genetic information.The ensuing discovery of catalytic RNA in the early 1980s was a majormilestone in RNA science with the recognition that its 3-dimensionalstructure is intrinsically related to its function.23 Up until that time, X-ray crystallographic studies of RNA had focusedpredominantly on transfer-RNA (due in part to limitations of preparativemethodologies for adequate quantities of other RNA types) and thenribosomal-RNA motivated by the fascination with its central role inprotein biosynthesis.24 Early therapeuticproteins were more convenient to study. As relatively stable, naturallyoccurring molecules, they could be isolated from animal or human tissuesin large quantities. For example, insulin could be purified in gramquantities and had been used therapeutically since the 1920s. Large-scaleglobal production was achieved within a few years of its discovery,and commendably, advanced pharmaceutical formulations had been developedby the 1930s.25 The biomedical potentialof insulin and the full knowledge of its 3-dimensional structure hadthus been thoroughly established well before its launch as the firstbiosynthetic human protein drug in 1982. In fact, structurally, biochemically,medically, and pharmaceutically, insulin was one of the most thoroughlystudied protein molecules in history by that time.mRNA was discovered in 1961, and an indicationof its biomedicalpotential was demonstrated in 1990 when protein production was shownfrom reporter gene mRNAs injected into mice.30 Indeed, it is amusing to note that as late as themid 1990s RNA scientists practically lamented the reverence that proteinscientists held toward the delicacy of higher-order structure,31 apparently reflecting the more contemporaryappreciation of RNA folding. mRNAs are large molecules : three nucleotide units codefor each amino acid of the protein for which they encode, and eachnucleotide has a mass of about 330 Da versus the average amino acidmass of 110 Da. The incorporation of ribose sugars into RNA as opposedto deoxyribose sugars for DNA makes RNA more suitable for its short-livedpurpose in vivo,32 whereas DNA (the informationstorage molecule) is highly stable to the extent of boasting an impressive521-year half-life.33 Chemical modificationsto the mRNA molecule including cap structures and modified nucleosideshave played a key role in overcoming challenges of immunogenicity,achieving prolonged stability and potent, accurate protein expressionin vivo.34 These advancements have been central toenabling exogenous mRNA delivery; however, the achievement of theideal target product profiles for mRNA vaccines and therapeutics willrequire further innovative approaches.In contrastto proteins, the concept of mRNA as a drug or vaccineis relatively recent, one that faced formidable drug delivery challengesand was not preceded by a long history of applicable pharmaceuticalsciences research. A 3-dimensional structure of our mRNA moleculeis not available, and an understanding of the interrelationships amonghigher-order structure, protein translational efficiency, and chemicalstability is only beginning to emerge.mRNA is a single strandedmolecule that can form double strandedstructures by folding over on itself, forming hairpin stem-loops andpseudoknots stabilized by the intramolecular hydrogen bonds formedthrough complementary pairing of contiguous bases. These secondarystructures fold into 3-dimensional tertiary structures as illustratedin 35 or, in the parlance of the pharmaceutical scientist, expectedto be highly formulation dependent. Although Ca2+ and Mg2+ play important roles in the stabilization of RNA foldingin vivo by participating in the ionic microenvironment as diffuseions or directly bound at high affinity sites, divalent cations alsopromote cleavage of RNA.37 Large RNA moleculesin solution are generally considered to be more extended and diffusethan globular proteins but still adopt diversely complex sequence-dependenthigher-order structures.38 While much progresshas been made in the prediction of the secondary structure from thesequence, the proverbial “rugged energy landscape” makesthe prediction of the tertiary structure a formidable problem, especiallyfor the very large mRNA molecule.39 Bothproteins and RNA exhibit secondary and tertiary structures dependenton the primary sequence; however, protein higher-order structuresare driven primarily by the burial of the hydrophobic side chainswhereas RNA folding is a hierarchical process driven predominantlyby base stacking, hydrogen bonding, and electrostatic stabilization.40 Although there is a superficial parallel betweenprotein- and RNA-higher-order structures, the analogy breaks downupon deeper consideration of structure–function interrelationships.For mRNA specifically, Crick’s classic metaphor of mRNA asan audio tape running through the reading head of a tape recorderemphasizes the significance of the primary sequence as the centralbasis of its function, carrying the genetic code from DNA to ribosomesthat unwind the folded mRNA molecule to decode the message. In contrast,it was the 3-dimensional folded structure of proteins that historicallyheld such fascination and is most associated with launching the fieldof structural biology. It follows that the preservation of the integrityof a therapeutic protein’s folded structure has always beensynonymous with achieving good pharmaceutical stability, whereas fundamentaldetails of how mRNA folding relates to its biological activity arestill emerging.30RNA is a polyanion with complex conformational and chargeinteractionbehaviors in solution. The negative charges on the chain repel eachother causing the RNA molecules to stretch out in solution. However,this stretching lowers the conformational entropy so that the moleculearrives at an optimum between minimizing the repulsive potential oflike charges by stretching out as much as possible while keeping theentropy sufficiently positive. In the presence of an electrolyte,the charges will be shielded, and the molecule will relax electrostaticallyand shrink in size. Consequently, the folding of RNA into stable tertiarystructures is extremely sensitive to counterions41 Incontrast, large RNA molecules are highly dynamic and are characterizedby extensive conformational heterogeneity with poorly differentiatedmolecular surfaces that offer few tertiary contacts to favor latticeformation. The very large size of mRNA molecules further compoundsthe difficulty of achieving a well-ordered crystal lattice, as evidentfrom the description by Gopal et al. of the long RNA molecule in solutionas “a statistical object whose properties are derived froman ensemble of possible structures”.42 Although many RNA structures have been reported in the structuralbiology literature and open databases, these predominantly correspondto comparatively short sequences, tRNA, and/or RNA in complexes withproteins.43 In contrast, many therapeuticproteins, including monoclonal antibodies, have X-ray crystal structuresdefining their 3-dimensional structures. Prospects for mRNA structureswith atomic level precision are poor because, in practice, NMR andX-ray crystallographic methods are restricted to relatively smallsequences (<≈200 nucleotides).44The comparisonof the crystallization behavior highlights the physicochemicaldifferences. The crystallization process is a form of molecular recognition,making its manifestation a visible outcome of the underlying structuraland interfacial phenomena. In a comparison of proteins with RNA molecules,the differing chemical nature of the repeating units in these twotypes of biopolymers results in quite different propensities for molecularordering and crystallization. Many pharmaceutical proteins crystallizewell because the molecular characteristics and solution conditionsthat favor crystallization also favor pharmaceutical integrity andstability . Indeed, their crystallization conditions can provideuseful clues for the identification of optimal pharmaceutical formulationconditions because the crystallization process is sensitive to multiplepharmaceutical quality attributes.46 Engineering the lipidstructure47 and particle surface has thusbeen pursued as a strategy to enhance cellular uptake and endosomalescape49 while specific nanostructural features ofthe LNP, such as nonlamellar lipid phases, have also been suggestedto affect delivery efficiency.50 LNP interfacialinteractions with the cell membrane initiate the internalization ofthe mRNA; then, inside the cell, the more acidic environment protonatesthe ionizable lipid, reversing the electrostatic interactions to releasethe RNA cargo for translation and subsequent protein expression. Thisis of course an oversimplified description, and the reader is directedto some excellent recent reviews that address these intracellularaspects in more detail.51 The LNP morphology,lipid packing, and microenvironment of the encapsulated mRNA are thusplausibly connected to the delivery efficiency, emphasizing the centralsignificance of higher-order structure associated with both the mRNAand LNP.Due to their size,polyanionic nature, and hydrophilicity, theintracellular delivery of mRNA molecules cannot generally rely onpassive diffusion across cell membranes. Furthermore, nucleic acidsare rapidly degraded by endogenous nucleases in physiological fluids.To overcome these challenges, LNPs incorporating ionizable lipidshave been developed as delivery vehicles for siRNA and mRNA, servingboth to protect the delicate cargo from degradation in vivo and toenable delivery into the cell. LNPs for mRNA delivery generally comprisea zwitterionic phospholipid, cholesterol, a polyethylene glycol (PEG)lipid, and an ionizable lipid.52 theircGMP scale-up for clinical/commercial use employs finely controllablerapid-mixing platforms involving multiple processing steps.54 In contrast, the large-scale production of many biologic drugs canbe based on relatively simple thaw–filter–fill drugproduct production processes. On the other hand, the operational simplicityof the drug product is offset by the complexity of biologic drug substanceproduction processes, which are based on microbial fermentation ormammalian cell culture. mRNA is produced synthetically at large scaleusing the in vitro transcriptase reaction.55The challenges of LNP preparative scale-up and large-scaleprocessingrepresent another interesting point of distinction between mRNA-vaccinesand biologic drugs. While LNPs may be prepared at bench-scale usingpipets and simple manual mixing,58 The literatureindicates there are many processing and compositional factors thatcan influence the outcome of the nanoprecipitation reaction, and itis also apparent that the chemical nature of the component lipidscan affect the LNP morphology,48 even tothe extent of producing distinctive faceted particle geometries.50 The siRNA-LNP literature reflects a fairly concordantdescription of the LNP assembly supported by biophysical studies.Presumably, due to their small size (≈20 nucleotides) and doublestranded character, the siRNA molecules can be more readily accommodatedwithin a structural arrangement directed predominantly by preferencesof the lipids. The much larger mRNA molecules evidently require adifferent accommodation. A direct comparison of LNP formation usingsiRNA versus mRNA under the same LNP preparative scheme showed thatmRNA formed LNPs with very large bleb features, whereas the siRNA-LNPcounterpart were devoid of these.56 Whenone recognizes that cryo-EM mass density in the blebs can be assignedto mRNA, it follows that the nature of the encapsulated RNA moleculeitself can influence LNP morphology and the degree of lipid association.Clearly, the encapsulation of large mRNA molecules is more complexthan common representations of the LNP as a sphere with RNA lipid-boundin the core.59 On the basis of our recentstudy pinpointing the location of mRNA within the LNP,1 we suggest that LNPs may be better represented as a continuumof states corresponding to varying degrees of mRNA-lipid associationas shown in Although cryo-EM images of mRNA-LNPs reported in the literatureoften appear as relatively featureless gray circles, we were intriguedby the diversity of mRNA-LNP morphologies in some published imageswhere spherical and nonspherical morphologies are apparent, includingblebs (cavernous protrusions) of varying size, sometimes showing resolvedstriations indicative of annular arrangements.12 Structural effects of the encapsulation itselfon the mRNA 3-dimensional fold may also conceivably influence stabilityby exposing or burying labile regions. The mRNA molecule within theLNP is thus expected to possess a distinct stability profile relativeto naked RNA. It is worth emphasizing at this point that the term“stability” is often used in different scientific contextsacross the pharmaceutical sciences and biological sciences fields.It has been described basically as the potential of a pattern to surviveover time,60 and in the context of a biological-basedmedicinal product, the relevant pattern may be categorized broadlyas either conformational or compositional. Denaturation, unfolding,self-association, and aggregation relate to the former, whereas processescreating new chemical entities such as cleavage, enzymatic degradation,oxidation, and covalent adducts12 are examplesof the latter. The preservation of correct higher-order structures,specifically secondary, tertiary, and quaternary structures, representsa central focus of biologic product development and characterization61 for which the close connection between conformationalstability and chemical stability is well recognized.62 Interfacial stresses associated with large-scale production,filling, shipping, storage, handling, and administration create formidablechallenges to preserving these delicate higher-order structures necessaryfor biological activity.63 Signatures ofthermal unfolding can thus provide some basis for understanding howpharmaceutical conditions impact the intrinsic structural stabilitywith a view to identify solution conditions robust to large-scaleprocessing and pharmaceutical stresses while also enabling a convenientcomparison of sequence variants in discovery phases of drug development.64 A prediction of the shelf life of proteins fromaccelerated data remains largely aspirational, nevertheless, gainingpredictive insights into the overall pharmaceutical stability of formulateddrug products by screening thermal unfolding signatures featured prominentlyin protein developability workflows within the biotechnology industry.67 Similarly, there is evidence that the secondary structure affectsthe chemical stability of RNA.68 We wereinterested in exploring the impact of encapsulation on the thermalfolded stability of the mRNA molecule with a view to understand itspotential relevance to pharmaceutical stability.The lipidic environmentof encapsulated mRNA involves several chemicalcomponents, creating the possibility that each pharmaceutical rawmaterial may adversely affect the mRNA stability profile.69 These approaches utilize optical or calorimetricreadouts to detect conformational change as the molecule unfolds.Much historical impetus for this work has come from the goal of understandingbiologically relevant conformational transitions, as these occur viabreakage and formation of base pairing interactions. The thermal stabilityof secondary structural elements in mRNA has received additional attentionrecently due to emerging evidence that this attribute relates to actualfunction (protein expression).70 We applied differentialscanning calorimetry (DSC)66 to a freemRNA to produce the thermogram shown in Thermal melting techniques for RNA are well-developed and havebeen applied extensively to studying nucleic acid folding and stability.71A complex thermogram requiring multiple Gaussian componentstoproduce an adequate fit indicative of a complex thermal unfoldingpathway is evident. As an illustrative comparator, we also recordedthe DSC of bovine serum albumin (BSA), a “model globular protein”4C. BSA e72 CD spectra of nucleicacids are mostly dependent on the sequence and stacking geometry ofthe bases, and in the case of short RNA sequences, it is possibleto distinguish A-form, B-form, and Z-form helices.73 The CD spectrum of mRNA at 25 °C, shown in 75 CD spectraof this mRNA recorded at 5 °C temperature increments from 25to 95 °C are also shown in 76To further evaluate the DSC results using a different biophysicaltechnique, we applied circular dichroism (CD) spectroscopy, whichcan be applied to the characterization of the conformation of nucleicacids in solution.The effect of encapsulation on the thermal melting of mRNA wasalso characterized using the CD signal. The CD spectrum of encapsulatedmRNA recorded at 5 °C increments is shown in 77 The determinationof the protein structure from the CD spectra is possible because thefar-UV CD arises from the intrinsic CD of the protein backbone. Incontrast, much of the nucleic acid CD originates from the stackinggeometry and sequence-dependent base pair content, making the relationshipbetween the nucleic acid secondary structure and CD spectral shapemore convoluted than is the case for proteins, especially in the caseof a large single-stranded mRNA. With this caveat, we offer some interpretationsof the spectral features present in 79 Studies on DNA have found that a particularly large spectral effectoriginates from guanine–guanine stacking, which makes an importantcontribution to the formation of helix duplexes, leading to the strongpositive band at 265 nm.80 In general,a positive band in the 260–280 nm region suggests the formationof a right-handed helix.72 A dominant positiveband at 260 nm and a sharp negative band at 210 nm characterize theCD spectra of A-form helix RNA.81 The weakband observed at 295 nm has been identified as the result of the nearest-neighborinteractions.78 In thermal melting experiments,CD changes are primarily caused by base destacking, leading to theloss of interaction between neighboring bases, which manifests asa decreased magnitude of CD bands. In the free mRNA spectrum of 82 The Hill coefficient valuesobtained from the curves of For proteins,the assignment of CD bands to specific secondarystructural elements has been well-established on the basis of thefar-UV CD of the peptide bond.67 Here, we show that some degree of analogy exists regardingLNP encapsulation conferring enhanced conformational stability tothe mRNA molecule. The achievement of the overall pharmaceutical stabilityof lipid nanoparticles will also require consideration of colloidalstability. This raises some further interesting analogies and contraststo proteins as net attractive or repulsive forces between moleculesor particles can influence pharmaceutical stability. With the adventof monoclonal antibodies (mAbs) as a prominent class of therapeuticsand the frequent need to deliver them at high dose and high concentration,favorable colloidal properties have become increasingly critical toachieve overall pharmaceutical stability and deliverability.83 It is not uncommon to formulate mAbs at >100mg/mL under which condition the distance between van der Waals surfacesof the molecules is on the same order of magnitude as the size ofthe molecules themselves.84 Consequently,solubility, stability, and viscosity become strongly influenced byintermolecular networks that form in solution.85 These networks have a complicated dependence on the subtletiesof surface morphology, dipole character, and patchiness of the electrostaticand hydrophobic surfaces. Although monoclonal antibodies are largemolecules with hydrodynamic diameters in the vicinity of ≈5–7nm, this size is considerably smaller than the ≈100 nm sizeof the lipid nanoparticles used to deliver RNA. Consequently, colloidalaspects can be expected to play a key role in their formulation. WhileLNPs may be cartoonishly represented as uniform spheres, the imagesin 86A comparison of events occurring in free versus encapsulatedmRNAleads to the conclusion that mRNA becomes thermally more stable inits encapsulated form, more effectively preserving its basic CD signatureduring heating. This observation parallels a pharmaceutical stabilizationstrategy used for proteins whereby enhanced folded stability may beconferred by favorable formulation conditions.87 and “Unstable ribonucleic acid...”.88 While these descriptions were certainly notmade with pharmaceutical applications in mind, they were an indicatorof the unique stability profile relative to other biopolymers. BecausemRNA science has not evolved with a central emphasis on biomedicalapplications, the interrelationships among primary sequence, higher-orderstructure, biological activity (protein expression), and pharmaceuticalstability have only relatively recently become the focus of intenseresearch. The accelerated thermal degradation of proteins has beenstudied extensively throughout biopharmaceutical history89 as a means of connecting fundamental thermodynamicmeasurables to the ultimate practical resilience of the intended therapeuticproduct. While there is clearly a unique set of challenges associatedwith stabilizing mRNA vaccines, the observation that encapsulationwithin LNPs significantly enhances the folded stability of mRNA strikesa familiar and optimistic note.Early descriptions of mRNA emphasized its instability. Titles ofthe landmark publications announcing its discovery referred to themolecule as “An unstable intermediate...”