Michael Ringel

Does size matter in R&D productivity? If not, what does?

This analysis of factors that affect the likelihood of success in drug research and development (R&D) indicates that scientific acumen and good judgment — particularly with regard to the early termination of less viable drug candidates — are crucial.

What matters most in commercial success: first-in-class or best-in-class?

It is common for several companies to be simultaneously pursuing promising new targets, and this analysis investigates the relative importance of market entry order and therapeutic impact on commercial success for drugs in the same class.

Racing to define pharmaceutical R&D external innovation models.

The pharmaceutical industry continues to face fundamental challenges because of issues with research and development (R&D) productivity and rising customer expectations. To lower R&D costs, move beyond me-too therapies, and create more transformative portfolios, pharmaceutical companies are actively capitalizing on external innovation through precompetitive collaboration with academia, cultivation of biotech start-ups, and proactive licensing and acquisitions. Here, we review the varying innovation strategies used by pharmaceutical companies, compare and contrast these models, and identify the trends in external innovation. We also discuss factors that influence these external innovation models and propose a preliminary set of metrics that could be used as leading indicators of success.

Quantifying Geographic Variation in Health Care Outcomes in the United States before and after Risk-Adjustment

Background Despite numerous studies of geographic variation in healthcare cost and utilization at the local, regional, and state levels across the U.S., a comprehensive characterization of geographic variation in outcomes has not been published. Our objective was to quantify variation in US health outcomes in an all-payer population before and after risk-adjustment. Methods and Findings We used information from 16 independent data sources, including 22 million all-payer inpatient admissions from the Healthcare Cost and Utilization Project (which covers regions where 50% of the U.S. population lives) to analyze 24 inpatient mortality, inpatient safety, and prevention outcomes. We compared outcome variation at state, hospital referral region, hospital service area, county, and hospital levels. Risk-adjusted outcomes were calculated after adjusting for population factors, co-morbidities, and health system factors. Even after risk-adjustment, there exists large geographical variation in outcomes. The variation in healthcare outcomes exceeds the well publicized variation in US healthcare costs. On average, we observed a 2.1-fold difference in risk-adjusted mortality outcomes between top- and bottom-decile hospitals. For example, we observed a 2.3-fold difference for risk-adjusted acute myocardial infarction inpatient mortality. On average a 10.2-fold difference in risk-adjusted patient safety outcomes exists between top and bottom-decile hospitals, including an 18.3-fold difference for risk-adjusted Central Venous Catheter Bloodstream Infection rates. A 3.0-fold difference in prevention outcomes exists between top- and bottom-decile counties on average; including a 2.2-fold difference for risk-adjusted congestive heart failure admission rates. The population, co-morbidity, and health system factors accounted for a range of R2 between 18–64% of variability in mortality outcomes, 3–39% of variability in patient safety outcomes, and 22–70% of variability in prevention outcomes. Conclusion The amount of variability in health outcomes in the U.S. is large even after accounting for differences in population, co-morbidities, and health system factors. These findings suggest that: 1) additional examination of regional and local variation in risk-adjusted outcomes should be a priority; 2) assumptions of uniform hospital quality that underpin rationale for policy choices (such as narrow insurance networks or antitrust enforcement) should be challenged; and 3) there exists substantial opportunity for outcomes improvement in the US healthcare system.

Occlusion in the Flow of New Drugs for Cardiovascular Disease

There is a large misalignment between unmet need and both private and public investment activity in cardiovascular disease. In this paper, we quantify the magnitude of the gap, analyze a range of potential root causes in two main categories (issues of feasibility and valuation), and propose steps toward solutions to close the gap.

Market watch: 2017 FDA drug approvals: number rebounds but average value slips

In line with our outlook last year (Nat Rev. Drug Discov. 16, 78; 2017), there was a rebound in the number of new drugs approved by the FDA in 2017 compared with 2016 (Nat. Rev. Drug Discov. 17, 81–85; 2018). Here, we analyse the 2017 crop of new therapeutic drugs (NTDs), defined as new molecular entities approved by the FDA’s Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER), adding combination products with at least one new molecular entity as an active ingredient but subtracting diagnostic imaging agents. As described previously (Nat. Rev. Drug Discov. 13, 331–332; 2014), we use projected peak annual sales of these NTDs as a proxy for value. In 2017, the FDA approved 52 NTDs with combined projected peak annual sales of US

What drives site performance in clinical trials

47 billion, substantially higher than the

What is the right amount to spend on biopharma R&D?

32 billion in 2016 and somewhat above the longer-term mean of

Do large mergers increase or decrease the productivity of pharmaceutical R&D?

40 billion (FIG. 1). Nevertheless, the average forecasted value per approval was lower in 2017 compared with 2016; average value slipped to

What drives operational performance in clinical R&D?

0.9 billion in 2017 from