In this study we show that glycosylation is relevant for immune recognition of therapeutic antibodies, and that defined glycan structures can modulate immunogenicity. Concerns regarding immunogenicity arise from the high heterogeneity in glycosylation that is difficult to control and can deviate from human glycosylation if produced in non-human cell lines. While non-human glycosylation is thought to cause hypersensitivity reactions and immunogenicity, less is known about effects of Fc-associated glycan structures on immune cell responses. We postulated that glycosylation influences antigen recognition and subsequently humoral responses to therapeutic antibodies by modulating 1) recognition and uptake by dendritic cells (DCs), and 2) antigen routing, processing and presentation. Here, we compared different glycosylation variants of the antibody rituximab (RTX) in in vitro assays using human DCs and T cells as well as in in vivo studies.We found that human DCs bind and internalize unmodified RTX stronger compared to its aglycosylated form suggesting that glycosylation mediates uptake after recognition by glycan-specific receptors. Furthermore, we show that DC-uptake of RTX increases or decreases if glycosylation is selectively modified to recognize activating (by mannosylation) or inhibitory lectin receptors (by sialylation). Moreover, glycosylation seems to influence antigen presentation by DCs because specific glycovariants tend to induce either stronger or weaker T cell activation. Finally, we demonstrate that antibody glycosylation impacts anti-drug antibody (ADA) responses to RTX in vivo. Hence, defined glycan structures can modulate immune recognition and alter ADA responses. Glyco-engineering may help to

Background More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. Objective This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. Methods The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies’ ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. Results Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. Conclusions This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. International Registered Report Identifier (IRRID) DERR1-10.2196/35442

High-grade serous ovarian cancers (HGSOC) represent the most common subtype of ovarian malignancies. Due to the frequency of late-stage diagnosis and high rates of recurrence following standard of care treatments, novel therapies are needed to promote durable responses. We investigated the anti-tumor activity of CD3 T cell engaging bispecific antibodies (TCBs) directed against the PAX8 lineage-driven HGSOC tumor antigen LYPD1 and demonstrated that anti-LYPD1 TCBs induce T cell activation and promote in vivo tumor growth inhibition in LYPD1-expressing HGSOC. To selectively target LYPD1-expressing tumor cells with high expression while sparing cells with low expression, we coupled bivalent low-affinity anti-LYPD1 antigen-binding fragments (Fabs) with the anti-CD3 scFv. In contrast to the monovalent anti-LYPD1 high-affinity TCB (VHP354), the bivalent low-affinity anti-LYPD1 TCB (QZC131) demonstrated antigen density-dependent selectivity and showed tolerability in cynomolgus monkeys at the maximum dose tested of 3 mg/kg. Collectively, these data demonstrate that bivalent TCBs directed against LYPD1 have compelling efficacy and safety profiles to support its use as a treatment for high-grade serous ovarian cancers.

High-grade serous ovarian cancers (HGSOC) represent the most common of the ovarian malignancies. Due to the frequency of late-stage diagnosis and high rates of recurrence following standard of care treatments, novel therapies are needed to promote durable responses. We investigated the anti-tumor activity of CD3 T cell-engaging bispecific antibodies (TCBs) directed against the PAX8 lineage-driven HGSOC tumor antigen LYPD1 and demonstrated that anti-LYPD1 TCBs induce T cell activation and promote in vivo tumor growth inhibition in LYPD1-expressing HGSOC. To selectively target LYPD1-expressing tumor cells with high expression while sparing cells with low expression, we coupled bivalent low-affinity anti-LYPD1 Fabs with the anti-CD3 SP34 scFv. In contrast to the monovalent anti-LYPD1 high-affinity TCB (VHP354), the bivalent low-affinity anti-LYPD1 TCB (QZC131) demonstrated antigen density-dependent selectivity and showed tolerability in cynomolgus monkeys at the maximum dose tested of 3 mpk. Collectively, these data demonstrate that bivalent TCBs directed against LYPD1 have compelling efficacy and safety profiles supportive of consideration for treatment of high-grade serous ovarian cancers.

BackgroundThe rate of failed drug trials in Alzheimer’s disease (AD) remains high. Many conventional endpoints currently used to demonstrate success of clinical trials lack sensitivity to drug treatment effects and perform disparately across disease stages. These endpoints tend to be burdensome “single time‐point” assessments that are vulnerable to subjectivity and rater errors.Novel technologies are rapidly emerging at the same time as our understanding of how to optimally measure drug treatment effects is evolving. Rather than relying on reductionist paper‐pencil assessments, a multimodal approach incorporating more frequent and/or more direct physiological assessments, may result in better detection of true treatment effects. However, will such an approach add too much burden to clinical trials? Are elderly participants in AD trials willing and able to operate new technologies? It is clear that any endpoint that is not well‐accepted by sites or trial participants is unlikely to be successfully adopted for large clinical drug trials.MethodThe MEDIA study was a single‐site study evaluating 10 digital in‐clinic assessments in 38 early AD participants and 12 cognitively healthy controls. The assessments included computerized and augmented reality assessments as well as wearable gait and EEG monitoring. This study additionally included conventional cognitive assessments augmented with unobtrusive digital sensors; such as eye tracking via a tablet camera, speech analytics using voice recordings and physiological assessments using a tablet or pen with built‐in sensors. All participants completed a feedback survey on each of the digital assessments. This feedback survey asked seven questions about ease of use, burden of the assessment and clinical meaningfulness. Responses were recorded on a scale of 0 = strongly disagree to 5 = strongly agree.ResultThe results revealed overall good acceptance of the digital technologies. Although some of the assessments were considered mentally demanding, the majority of participants felt the technologies were easy to use, clinically meaningful and enjoyable.ConclusionThere is great anticipation for more sensitive clinical endpoints in AD. However, a question remains on the operational feasibility and how acceptable digital endpoints are to trial participants. This presentation discusses early AD participant (from presymptomatic to mild dementia) acceptance of different digital assessments.