Assessing rare disease understanding: a novel disease readiness level framework

Drug development for rare diseases has hurdles against setting high priority because of the size of the market. Although many countries have incentive policies for the development of orphan drugs (drugs used against rare diseases), evaluation methods for determining the rare diseases warranting resource support have not yet been established. To promote research and development (R&D) of rare diseases and drug development, methods measuring the level of understanding of rare diseases and its comparison with that of other diseases are warranted. This study proposes a grading system for measuring simultaneously the level of understanding of rare diseases and progress in product development.

Using the Technology Readiness Levels (TRL) framework developed by the National Aeronautics and Space Administration, we proposed a Disease Readiness Level (DRL) to assess the understanding of rare diseases by comparing the characteristics of existing TRL derivatives in the medical field, adding a clinical guideline in the middle stage and extending the assessment period to earlier stages than product development. Case studies with the developed framework were conducted for four rare diseases.

The DRL comprehensively described the four selected rare diseases, muscular dystrophy, progressive fibrodysplasia ossificans, Tangier disease, and idiopathic peripheral pulmonary artery stenosis from their disease origin in the pre-product development phase to the launch of therapeutic strategies over a longer period than previous TRL derivatives.

This study developed a comprehensive framework for rare diseases that focuses on the disease rather than the product for assessment and covers information spanning disease discovery to drug development. The results of case studies using the framework suggest that DRL can analyze both the level of understanding of rare diseases and the progress of the product research and development (R&D), and can be used as a potential indicator for the allocation of R&D resources.