Associate Director, Value Analytics

Job Description As a leading pharmaceutical company, AbbVie is constantly striving to discover and deliver innovative medicines and solutions that address complex health issues and enhance people's lives.
Bringing a new drug to patients is a complex process that involves not only scientific research and development but also navigating regulatory hurdles, Access and reimbursement decisions as well as Pricing negotiations.
In today's healthcare landscape, decision-makers are increasingly focused on demonstrating the value of new treatments, and AbbVie recognizes the importance of providing robust evidence to support its products.
To address this need, AbbVie is establishing a new function:  Value Analytics Center  within Global Value and Evidence (V&E).
This team will be responsible for building and leading an evidence synthesis, economic modeling, and HTA and value assessment analytics capability.
By bringing together experts in these areas, AbbVie will be able to develop a comprehensive understanding of the value of its products, from a clinical, humanistic, and economic perspective.
With this new function a new way of working will be introduced with modelling evidence teams led by the V alue Analytics Center  bringing together cross functional partners in global, us and international functions and business units to co-create robust modeling evidence for internal and external stakeholders.
  The Value Analytics Center  will play a critical role in informing internal Access strategies, pricing, and reimbursement decisions, as well as HTA and value assessment submissions.
By providing robust evidence to support these decisions, AbbVie will be well-positioned to secure positive recommendations and listings, negotiate with payers and secure/maintain access to its treatments for patients.
In addition, the  Value Analytics Center  team will help AbbVie stay industry leading by developing in-house expertise and creativity to demonstrate the value of its products to Access stakeholders and the overall Health care system ensuring patient access to AbbVie's innovative medicines.
Overall, the  Value Analytics Center  capability is essential to AbbVie's long-term success in the rapidly evolving healthcare landscape.
Role is responsible for leading evidence modelling teams to design and execute evidence-synthesis, health economic models.
Position applies methodological and analytical expertise to predict the value of AbbVie products and develop strategies on how best to demonstrate this to external payer decision makers.
Role will strategically and effectively communicate, and tailor generated evidence to multiple stakeholder audiences.
Responsibilities Develop core global Systematic Literature Reviews (SLR), Indirect Treatment Comparison (ITC) and Health Economic Models (HEM) for HTA, payer and other Access stakeholder assessments, submissions, and negotiations.
Support publications associated with these to meet business objectives.
Providing strategic, methodological, and analytical support to affiliates with adaptation of the Global Models (ITC, HEM) for local HTA submissions and support the local assessment of HTA strategy.
Coordinate data requirements across biostatistics and evidence generations functions (Clinical Development; HEOR and Medical Affairs) to support Pricing & Reimbursement Lead evidence modelling teams (cross-functional and multi countries) to source affiliate and other stakeholder needs, develop strategic options and co-create solutions.
Tracking progress, motivating, and leading peers in a matrix team.
Core member of VAT when leading modelling teams contributing to development of integrated access strategy and attend other cross-functional teams as required.
Identify need for preliminary ITCs and HEMs to inform value proposition, development, pricing and commercial strategic forecast and decisions.
Lead and facilitate the sharing of best practices and key learnings across affiliates and cross-functional partners.
Use analytical techniques leveraging available clinical data and published information to inform pricing and market access strategy.
Collaborate with the Data and Statistical Sciences (DSS) team for trial analyses, HTA challenges, and statistical analyses of clinical trial data.
Act as a Strategic Partner for key partners from V&E (HEOR Strategy, RWE Analytics) and iMAP (HTA Strategy, Pricing) to ensure alignment to brand and commercial, access and evidence strategy.
Ensure optimal utilization of modelling evidence through partnership with teams generating payer & promotional materials, generating regulatory dossiers and publications.
Provide mentoring and coaching support to junior members of evidence modelling teams and across function.
Qualifications Advanced degree MS/MSc/Mphil/MPH (required) or PhD (preferred) in Health Economics, Epidemiology, Statistics, Biostatistics, Public Health, Econometrics, or other related field.
At least 8 years relevant experience in consultancy or pharmaceutical industry in Evidence-synthesis, Health Economics, Health Technology Assessment, or related area Excellent oral and written communication skills, and strong interpersonal and leadership skills Expert knowledge of both health economics and evidence-synthesis disciplines as relevant to HTA, pricing, reimbursement, and value assessment Ability to leverage deep expertise to design custom solutions for diverse stakeholder groups.
Demonstrated leadership in a global matrix environment with multiple stakeholders.
Proven experience interacting with and/or delivering submissions to HTA agencies, or other payer or decision-making bodies.
Skills and experience within one of the following core capabilities of the Value Analytics Center Health economics economic modelling and budget impact analysis Working hands-on knowledge of EXCEL for the development of economic models and/or BIMs including VBA Evidence-synthesis Designing SLR search strategies, conducting feasibility analysis for Indirect comparisons Critically appraise reporting of SLRs and ITC/NMAs Statistics HTA-relevant statistical methodologies, for example indirect treatment comparisons, survival analysis, or utility estimation.
Working knowledge of statistical and data processing software (R preferred) Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ? ? The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range.
This range may be modified in the future.? We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.? This job is eligible to participate in our short-term incentive programs. ? This job is eligible to participate in our long-term incentive programs? ? Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. ? AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion.  It is AbbVie's policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.
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