Mapping Biopharmaceutical Innovation and Diffusion: How the Second Translational Block (T2) Shapes Drug Diffusion

Joshua Cohen*, Laura Faden, Kenneth Getz
Tufts Center for the Study of Drug Development (CSDD), 75 Kneeland Street, Suite 1100, Boston, Massachusetts 02111, USA.

© 2008 Cohen et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Tufts Center for the Study of Drug Development (CSDD), 75 Kneeland Street, Suite 1100, Boston, Massachusetts 02111, USA; Tel: 617-636-3412; Fax: 617-636-2425; E-mail:


In the US, there is a vigorous public debate on the merits of biopharmaceutical innovations and their diffusion. There is virtual unanimity about the importance of maintaining a steady stream of biopharmaceutical innovations, to which patients should have timely access. However, the debate’s participants are cognizant that the effects of innovation and diffusion on health outcomes, health care spending, and incentives for future innovation, must be weighed against one another.

First, we performed a Medline literature review to map the innovation diffusion process, combining the search terms “innovation,” “diffusion,” and “pharmaceutical.” Second, we conducted a survey of 190 physicians to examine their valuation of the innovativeness and rate of diffusion of 20 new molecular entities (NMEs). Third, we collected data from the Centers for Medicare and Medicaid Services (CMS) Formulary Finder to assess payers’ valuation of the innovativeness of the 20 NMEs in question.

Based on our literature review, we identified the key stakeholders involved in the innovation diffusion process. Furthermore, we highlighted the changing landscape of translational movers and shakers, tracing the emergence of T2 barriers, emanating largely from third party payer formulary management. Our empirical analysis suggests payers are exerting influence on physicians’ prescribing decisions, while the role of patients and pharmaceutical firms has diminished somewhat. Payers directly affect prescribing decisions through the use of formularies, and indirectly by funding evidence-based continuing medical education.

On average, across the 20 drugs we sampled, the time from approval to first prescription was 33 months, which indicates a slow diffusion process. Our data analysis shows a gap in perception of innovativeness between physicians and payers, with physicians ranking drugs as more innovative on average than payers. And, our findings suggest the more innovative a drug is perceived by physicians and payers the higher market share it has.

Striking an appropriate balance on access to and cost of biopharmaceuticals will require policy adjustments on the part of payers. In cases in which there is a large degree of uncertainty or the fiscal impact is particularly high, coverage could be made subject to a policy of coverage with evidence development (CED). Here, coverage would be conditional on development and capture of outcome data. A CED policy could be combined with a risk-sharing arrangement in which financial risk is shared between payers and the biopharmaceutical industry.