【Alexion Japan】Manager / Associate Manager, Patient Business Model & Insights

Role Purpose The Manager / Associate Manager, Patient Business Model & Insights is responsible for designing a patient-level commercial model for rare diseases and for generating patient insights from real-world data (RWD) and other data sources. As the core role of Patient Ladder Harmonization, this position aligns the Patient Ladders, KPIs, and patient-data practices that currently differ by disease, brand, and business unit into a common framework, so that the patient journey and business progress can be described with the same definitions and the same measures across all diseases. The role holds design and insight as one accountability. It designs patient-journey stages, KPIs, data models, and disease-archetype strategies in a form that can be measured with data. At the same time, it designs analyses of RWD, internal data, and public information according to those definitions, and validates and interprets the results executed by data scientists and external analytics partners to generate insights — such as the number of patients at each stage, stage-to-stage conversion rates, lead time to diagnosis and treatment initiation, and persistence — and connects them to decisions on brand planning, CRM strategy, marketing initiatives, and resource allocation. The role operates on the premise of a highly regulated environment and of diseases with extremely small patient populations. It builds into the design, as preconditions, the permitted scope of use according to how patient data was obtained and whether consent exists, the risk of re-identifying individuals, data licensing and permitted-use terms, and the regulations governing direct engagement with patients. Working with legal, compliance, medical, and privacy functions, it operates the model and its insights within appropriate governance and human decision-making frameworks. Key Responsibilities Business Model Design The role defines common patient-journey stages (such as suspicion, diagnosis, treatment selection, treatment initiation, persistence, and switching), maps them against the existing Patient Ladder of each disease and business unit, and builds a stage framework that can be used in common across all diseases. The role designs common definitions and calculation methods for KPIs such as "new patient," "treatment initiation," "persistence," "discontinuation," and "switch," so that stage-to-stage conversion rates, lead times, and persistence can be calculated in the same way. Where definitions differ between business units, the role makes the differences visible and leads alignment. The role contributes to the design of a data model that classifies patient data by how it was obtained and whether consent exists, and that specifies, for each class, the permitted purposes, level of granularity, storage method, authorized viewers, and representation in CRM. It builds the elements required for governance — consent metadata, audit logs, and upper limits on the granularity of de-identified data — into the design from the outset. For identifiable data obtained with patients' own consent, the role is responsible only for designing how the data is held, its consent metadata, and access rights; the role itself does not view individual patient records. The role defines disease archetypes according to disease characteristics (for example, diseases with many competitors where persistence and switching matter most, ultra-rare diseases with a single therapy where finding each patient matters most, and diseases with a large undiagnosed population where the path from diagnosis to treatment selection matters most), and designs CRM strategies and marketing models that, on top of the common framework, vary the priority stages, tracked indicators, and initiatives by archetype. The role designs the mechanisms that turn CRM signals into initiatives for healthcare professionals, institutions, and patients (limited to what regulations permit) — including next-best-action design, omnichannel orchestration, and modular messaging — together with the methods for measuring their effect, including how control groups are set. The role runs pilots of the designed model in selected diseases, measures and evaluates the results, and feeds them into roll-out to other diseases and business units and into revisions of the standard. Patient Insight Generation from RWD and Other Data The role starts from brand and business questions — not from available data or tools — and designs analytical themes after determining which questions each data source can and cannot answer. The role designs analyses that combine commercial claims databases, public statistics and open data, internal data (such as CRM, patient profiles, and patient support programs), and published literature and guidelines to generate patient insights such as the number of patients at each stage, stage-to-stage conversion rates, lead time to diagnosis and treatment initiation, persistence and discontinuation, referral pathways, and healthcare delivery structures. Data extraction and aggregation are performed by data scientists and external analytics partners; the role itself does not hold direct access rights to internal or purchased data. The role assesses the limitations of each data source — including coverage, representativeness, accuracy of diagnosis and prescription records, follow-up period, and biases arising from how persistence is measured — and triangulates results across multiple data sources to show the range and confidence of estimates. For diseases with extremely small patient populations, the role determines the granularity and presentation of results in light of estimation uncertainty and re-identification risk. The role works with data scientists and external analytics partners to specify analyses (definitions of target populations, metric definitions, analytical logic, assumptions, and limitations), reviews deliverables, and validates the soundness of the logic. The role translates findings and their limitations in a way that non-specialist stakeholders understand without misinterpretation, makes data provenance, coverage, and confidence explicit, and supports decision-making while preventing over-interpretation. The role defines how KPIs are measured during pilots and after roll-out, and, based on the measured results, analyzes gaps between model assumptions and actual results, and reflects them in revisions of the business model. Driving Harmonization and Governance The role works with stakeholders across marketing, sales, m