Implementation of a High-Level Isolation Unit Readiness Checklist in the Irish Setting.

A high-level isolation unit (HLIU) is a specially designed biocontainment unit for suspected or confirmed high-consequence infectious diseases. For most HLIUs, maintaining readiness during times of inactivity is a challenge. In this case study, we describe a checklist approach to assess HLIU readiness to rapidly operate upon activation. This checklist includes readiness criteria in several domains, such as infrastructure, human resources, and material supplies, that are required to safely activate the unit at any time. The checklist audit tool was derived from a novel activation readiness checklist published by the biocontainment unit at The Johns Hopkins Hospital in Baltimore, Maryland. It was then adapted for the Irish healthcare setting and implemented at the Mater Misericordiae University Hospital, Ireland's current isolation facility. Results from the audit were also used to inform recommendations for the construction of a new HLIU to open in 2025. The audit tool is user friendly, practical, and focuses on the essential elements of readiness to ensure a successful rapid operation.

Mechanistic modeling of empty-full separation in recombinant adeno-associated virus production using anion-exchange membrane chromatography.

Recombinant adeno-associated viral vectors (rAAVs) have become an industry-standard technology in the field of gene therapy, but there are still challenges to be addressed in their biomanufacturing. One of the biggest challenges is the removal of capsid species other than that which contains the gene of interest. In this work, we develop a mechanistic model for the removal of empty capsids-those that contain no genetic material-and enrichment of full rAAV using anion-exchange membrane chromatography. The mechanistic model was calibrated using linear gradient experiments, resulting in good agreement with the experimental data. The model was then applied to optimize the purification process through maximization of yield studying the impact of mobile phase salt concentration and pH, isocratic wash and elution length, flow rate, percent full (purity) requirement, loading density (challenge), and the use of single-step or two-step elution modes. A solution from the optimization with purity of 90% and recovery yield of 84% was selected and successfully validated, as the model could predict the recovery yield with remarkable fidelity and was able to find process conditions that led to significant enrichment. This is, to the best of our knowledge, the first case study of the application of de novo mechanistic modeling for the enrichment of full capsids in rAAV manufacturing, and it serves as demonstration of the potential of mechanistic modeling in rAAV process development.

Tumor-wide RNA splicing aberrations generate immunogenic public neoantigens.

T-cell-mediated immunotherapies are limited by the extent to which cancer-specific antigens are homogenously expressed throughout a tumor. We reasoned that recurrent splicing aberrations in cancer represent a potential source of tumor-wide and public neoantigens, and to test this possibility, we developed a novel pipeline for identifying neojunctions expressed uniformly within a tumor across diverse cancer types. Our analyses revealed multiple neojunctions that recur across patients and either exhibited intratumor heterogeneity or, in some cases, were tumor-wide. We identified CD8+ T-cell clones specific for neoantigens derived from tumor-wide and conserved neojunctions in GNAS and RPL22 , respectively. TCR-engineered CD8 + T-cells targeting these mutations conferred neoantigen-specific tumor cell eradication. Furthermore, we revealed that cancer-specific dysregulation in splicing factor expression leads to recurrent neojunction expression. Together, these data reveal that a subset of neojunctions are both intratumorally conserved and public, providing the molecular basis for novel T-cell-based immunotherapies that address intratumoral heterogeneity.

HepCare Plus: Enhancing Primary Care Identification and Treatment of Hepatitis C Virus in High-Risk Individuals.

Hepatitis C Virus (HCV) disproportionately affects people who inject drugs, migrants, prisoners and the homeless. An integrated, peer-led model of care involving primary and secondary care is required to enhance the identification and treatment of HCV in these marginalised groups. HepCare Plus builds on the network and achievements of HepCare Europe (a co-funded Third Health Programme of the European Union/Health Service Executive project). It further identifies those not accessing care and facilitates prompt assessment and treatment of those diagnosed with HCV, with the aid of a peer support worker (PSW) and a community HCV nurse specialist. Of 109 individuals identified and assessed for HCV treatment, 100 commenced HCV treatment. Despite interruptions to treatment (COVID-19 pandemic and national health service cyberattack) there was a high-level of treatment completion with PSW engagement (98%, n = 98). Eighty (73%) individuals were previously aware of a positive HCV status, highlighting the ongoing need to address barriers preventing marginalised groups from engaging with care. HepCare Plus reiterates the defining role of peer-led community interventions in HCV treatment engagement and the need for continuous open-ended HCV care. It provides a sustainable framework to meaningfully combat HCV and achieve the United Nations Sustainable Development Goal of HCV elimination by 2030.

Safety and efficacy of low dose naltrexone in a long covid cohort; an interventional pre-post study.

Background: Up to 37.7% of patients experience symptoms beyond 12 weeks after infection with SARS-CoV-2. To date care for people with long covid has centred around multidisciplinary rehabilitation, self care and self pacing. No pharmacotherapy has been shown to be beneficial. Methods: In this single centre interventional pre post study, the safety of Low Dose Naltrexone (LDN) was explored in patients with Post COVID-19 Syndrome (PCS), defined by NICE as patients with ongoing symptoms 12 or more weeks after initial infections with SARS-CoV-2 where alternative explanation for symptoms cannot be found. Patients were recruited through a Post COVID clinic, had a baseline quality of life questionnaire in symmetrical Likert format, were prescribed 2 months (1 mg month one, 2 mg month two) of LDN and repeated the same questionnaire at the end of the second month. Patients were monitored to adverse events. Findings: In total 52 patients participated of whom 40(76.9%) were female. The median age was 43.5 years(IQR 33.2-49). Healthcare workers represented the largest occupational cohort n = 16(34.8%). The median time from diagnosis of COVID-19 until enrolment was 333 days (IQR 171-396.5). Thirty-eight participants (73.1%) were known to commence LDN, two of whom (5.3%) stopped taking LDN post commencement due to new onset diarrhoea and also described fatigue. In total 36(69.2%) participants completed the questionnaire at the end of the two-month period. Improvement was seen in 6 of 7 parameters measured; recovery from COVID-19, limitation in activities of daily living, energy levels, pain levels, levels of concentration and sleep disturbance (p ≤ 0.001), improvement in mood approached but was not significant (p = 0.054). Conclusions: LDN is safe in patients with PCS and may improve well-being and reduce symptomatology in this cohort. Randomised control trials are needed to further explore this.

Assessing the impact of COVID-19 at 1-year using the SF-12 questionnaire: Data from the Anticipate longitudinal cohort study.

BACKGROUND: Few studies to date have explored the health-related quality of life (HRQoL) in patients with long COVID. METHODS: The Anticipate Study is a prospective single-centre observational cohort study. Hospitalised and nonhospitalised patients were seen at a dedicated post-COVID clinic at a 2-4 month (Timepoint 1) and 7-14 month follow-up (Timepoint 2). The main objectives of this study are to assess the longitudinal impact of COVID-19 in patients using the 12-item Short Form Survey (SF-12) score, a health-related quality of life tool, and to identify predictors of developing post-COVID-19 syndrome (PoCS). In addition, we aimed to describe symptomatology and identify predictors of PoCS at 1-year. RESULTS: A total of 155 patients were enrolled, 105 (68%) were female aged 43.3 (31-52) years. In total 149 (96%) and 94 (61%) patients completed follow-up at median 96 (76-118) days and 364 (303-398) days. The overall cohort had significantly reduced physical composite score (PCS) of the SF-12 (45.39 [10.58] vs 50 [10], p = 0.02). Participants with PoCS had significantly lower scores than those without symptoms at 1-year follow-up (37.2 [10.4] v 46.1 [10.9] p <0.001), and scores for these patients did not improve over the 2 Timepoints (PCS 34.95 [10.5] - 37.2 [10.4], p = 0.22). Fatigue was the most common symptom. Those with 5 or more symptoms at initial diagnosis had lower PCS and mental composite score (MCS) at 1-year. Predictors of PoCS at 1-year were lower PCS and higher baseline heart rate (HR) at clinic review median 3 months after COVID-19. CONCLUSION: Patients with PoCS have lower PCS scores during follow-up, which did not significantly improve up to a 1-year follow-up. Lower PCS scores and higher HR at rest can be used in the weeks after COVID-19 can help predict those at risk of PoCS at 1 year.

Taking the Hinge off: An Approach to Effector-Less Monoclonal Antibodies.

A variety of Fc domain engineering approaches for abrogating the effector functions of mAbs exists. To address some of the limitations of the current Fc domain silencing approaches, we are exploring a less commonly considered option which relies on the deletion of the hinge. Removal of the hinge domain in humanized IgG1 and IgG4 mAbs obliterates their ability to bind to activating human Fc gamma receptors I and IIIA, while leaving their ability to engage their target antigen intact. Deletion of the hinge also reduces binding to the Fc neonatal receptor, although Fc engineering allows partial recovery of affinity. Engineering of the CH3 domain, stabilizes hinge deleted IgG4s and prevents Fab arm exchange. The faster clearing properties together with the pacified Fc make modality of the hinge deleted mAb an appealing solution for therapeutic and diagnostic applications.

Rational design of peptide affinity ligands for the purification of therapeutic enzymes.

Non-mAb biologics represent a growing class of therapeutics under clinical development. Although affinity chromatography is a potentially attractive approach for purification, the development of platform technologies, such as Protein A for mAbs, has been challenging due to the inherent chemical and structural diversity of these molecules. Here, we present our studies on the rapid development of peptide affinity ligands for the purification of biologics using a prototypical enzyme therapeutic in clinical use. Employing a suite of de novo rational and combinatorial design strategies we designed and screened a library of peptides on microarray platforms for their ability to bind to the target with high affinity and selectivity in cell culture fluid. Lead peptides were evaluated on resin in batch conditions and compared with a commercially available resin to evaluate their efficacy. Two lead candidates identified from microarray studies provided high binding capacity to the target while demonstrating high selectivity against culture contaminants and product variants compared to a commercial resin system. These findings provide a proof-of-concept for developing affinity peptide-based bioseparations processes for a target biologic. Peptide affinity ligand design and screening approaches presented in this work can also be easily translated to other biologics of interest. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:987-998, 2018.

QSAR models for prediction of chromatographic behavior of homologous Fab variants.

While quantitative structure activity relationship (QSAR) models have been employed successfully for the prediction of small model protein chromatographic behavior, there have been few reports to date on the use of this methodology for larger, more complex proteins. Recently our group generated focused libraries of antibody Fab fragment variants with different combinations of surface hydrophobicities and electrostatic potentials, and demonstrated that the unique selectivities of multimodal resins can be exploited to separate these Fab variants. In this work, results from linear salt gradient experiments with these Fabs were employed to develop QSAR models for six chromatographic systems, including multimodal (Capto MMC, Nuvia cPrime, and two novel ligand prototypes), hydrophobic interaction chromatography (HIC; Capto Phenyl), and cation exchange (CEX; CM Sepharose FF) resins. The models utilized newly developed "local descriptors" to quantify changes around point mutations in the Fab libraries as well as novel cluster descriptors recently introduced by our group. Subsequent rounds of feature selection and linearized machine learning algorithms were used to generate robust, well-validated models with high training set correlations (R2 > 0.70) that were well suited for predicting elution salt concentrations in the various systems. The developed models then were used to predict the retention of a deamidated Fab and isotype variants, with varying success. The results represent the first successful utilization of QSAR for the prediction of chromatographic behavior of complex proteins such as Fab fragments in multimodal chromatographic systems. The framework presented here can be employed to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives. Biotechnol. Bioeng. 2017;114: 1231-1240. © 2016 Wiley Periodicals, Inc.