HOW CAN HEALTH ECONOMIC ASSESSMENT METHODS HELP DECISION MAKING IN PORTFOLIO DEVELOPMENT

Author(s)

Akpo H;Popa C*, Saka Ö Deloitte, Diegem, Belgium

Objectives: The R&D costs of a new drug approximate $1.3billion and are increasing due partly to regulatory hurdles and development costs. There is a need for smarter investments, which consider the requirements of regulatory bodies, increasing the chances of securing market access and high return on investment. We describe how health economic methods could support capital investment decisions in funding, valuing and bringing new pharmaceuticals to market. Methods: A literature review was performed on health economic and capital investment methods.  The different analyses were mapped to the commercial roadmap and R&D pipeline of a biopharmaceutical company. An approach based on real options valuation model was proposed to support investment and market decisions and to predict the potential net present value (NPV) of a drug. The conceptual structure of the model was face-validated by health economic and valuation experts. Results: A decision-tree based valuation method, populated partially by information from health economic tools, was adopted to analyse and clearly communicate R&D investment opportunities, to capture management flexibility and to improve strategic thinking.  A feedback loop can be built into the model to analyse resiliency to assumption changes. In early phases, headroom and multi-criteria decision analyses indicate the likelihood of an investment being cost-effective. Phase I and II trials provide early evidence on drug efficacy and tolerability and initial cost estimates. Based on value of information, cost-effectiveness and budget impact models, only drugs deemed to meet authority requirements would be selected. Market intelligence and uncertainties and clinical success probability further enable identification of the optimal portfolio containing drug candidates that maximize NPV for given risk levels. Conclusions: Health economic methods are commonly applied during late stage development, but if implemented alongside capital investment tools from earliest R&D stages they could increase the likelihood of selecting the right products to compose an effective investment portfolio.

Conference/Value in Health Info

2013-11, ISPOR Europe 2013, The Convention Centre Dublin

Value in Health, Vol. 16, No. 7 (November 2013)

Code

PRM236

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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