Introduction No published literature systematically explores the dry age-related macular degeneration (AMD) patient experience. To inform the development of patient-reported outcome measures (PROMs), the important and relevant signs, symptoms, and impacts for patients with dry AMD were identified. Methods A holistic approach was used to capture, define, and organize the signs, symptoms, and impacts that are important to patients with dry AMD. Qualitative evidence was identified through a targeted literature review and clinician ( N = 5) and patient ( N = 20) interviews. The targeted review was expanded to include patients with AMD, as few studies specific to dry AMD were identified. The qualitative evidence was incorporated into a conceptual model that included the signs, symptoms, and impacts of dry AMD affecting the patient experience. Results Twenty-nine articles (dry AMD, N = 5; general AMD, N = 24) exploring health-related quality-of-life evidence in patients with AMD were identified. Concepts identified and included in the preliminary, literature-based model included signs and symptoms related to general vision loss and general impacts (e.g., dependency on others, poor spatial perception/mobility, difficulty reading, emotional affects). No concepts unique to dry AMD were identified. Interviewed clinicians refined the literature-based model. Across all visual acuity severities, ≥ 80% of patients reported difficulty driving, reading, and completing activities of daily living, along with frustration and dependency on others; all patients reported blurred vision. The final model included 35 signs, symptoms, and impacts, with 19 considered salient. Conclusions To better understand the patient experience, we captured, defined, and organized signs, symptoms, and impacts into a dry AMD conceptual model. This model can aid in the development of PROMs reflecting the experience of patients with dry AMD. Supplementary Information The online version contains supplementary material available at 10.1007/s40123-020-00325-y.

Global progress against malaria has stagnated and novel medical interventions to prevent malaria are needed to fill gaps in existing tools and improve protection against infection and disease. Candidate selection for next-generation interventions should be supported by the best available evidence. Target product profiles and preferred product characteristics play a key role in setting selection criteria requirements and early endorsement by health authorities. While clinical evidence and expert opinion often inform product development decisions, integrating modelling evidence early and iteratively into this process provides an opportunity to link product characteristics with expected public health outcomes. Population models of malaria transmission can provide a better understanding of which, and at what magnitude, key intervention characteristics drive public health impact, and provide quantitative evidence to support selection of use-cases, transmission settings, and deployment strategies. We describe how modelling evidence can guide and accelerate development of new malaria vaccines, monoclonal antibodies, and chemoprevention.

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