Market access for expensive therapies (or how to overcome prices)

 Managed Entry Agreements and Funding for Expensive Therapies

Key reference to understand what's going on in this topic. Recommended.

Contents:

1. Introduction to Managed Entry Agreements

2. Definition and Classification of MEAs

3. From Coverage with Evidence Development to Individual Performance-Based Agreements in Italy

4. Coverage with Evidence Development for Multiple Sclerosis Drugs in the UK: A "Costly Failure"?

5. Country Comparison of the Implementation of Managed Entry Agreements

6. Novel Funding Models for Expensive Therapies

7. Managed Entry Agreement for Cell and Gene Therapies

The decline of pharma R&D productivity (how much are we willing to pay for failure (95%) or success (5%)?)

Global Trends in R&D . Overview through 2021 

The productivity of the clinical development process can be considered as a measure of trial outputs (drugs, innovation, trial success, etc.), compared to a measure of trial inputs or resources dedicated to obtaining those outputs (e.g., aspects of trial complexity, duration, monetary investments, etc.). Such measures of success, complexity and trial duration were selected for inclusion in the productivity index as described above. Increases in success will increase productivity overall as will decreases in complexity or duration. Conversely, decreases in success will drive down the productivity index, as do increases in complexity and duration.

Clinical development productivity — a composite metric of success rates, clinical trial complexity and trial duration — declined in 2021, continuing an overarching 10-year trend. Despite a second year of decreasing trial complexity, the ongoing decline in success rates has resulted in reduced average trial productivity. Trial success rates fell to their lowest in more than 10 years to an average 5% likelihood of progressing successfully through all phases.

Health systems design

 Building a High- Value Health System

Countries and institutions worldwide face the challenge of planning and paying for health care that effectively meets the needs of citizens and employees. While there are many criticisms of existing healthcare models, current literature offers little guidance for individuals who want to carry out the work of redesigning and improving their health system.

Pharma, big pharma (15)

Sick Money. The Truth About the Global Pharmaceutical Industry 

Pharmaceutical innovation and value extraction

 Pharmaceutical innovation sourcing

Figure below shows that 23% of new medicines came from public bodies and private-private collaboration and they didn't apply for any marketing authorisation.

Managing the decline in Pharma R&D

Global Trends in R&D. OVERVIEW THROUGH 2021

A decade ago I posted this: Gestionar el declivi. John Kay said in 2011:

"When an industry model is broken, the best business strategy may be to manage its decline"

Now a new report confirms that the process continues after a decade.

From IQVIA report:

The composite success rate across all development phases and therapy areas declined to 5.0% in 2021, which can be attributed to an appetite for increased scientific risk in clinical development programs as the bar for efficacy and safety rises, as well as increased pauses in product development due to the pandemic.

Across disease areas, probability of success varies considerably, and 2021’s composite success rate fell below the 10-year trend in all areas except for vaccines and cardiovascular.

 That's all folks.

Human genomics vs. clinical genomics

 Today my suggestion is to read the post by Eric Topol with the same title. 

It begins with this statement:

We’re now well over 20 years since the first human genome was sequenced, but with few exceptions the massive amount of data that has been generated has not been transformed to routine patient care.

So, why?

Setting priorities explicitly (or not) (2)

 REASONABLE RATIONING. International Experience of Priority Setting in Health Care

COVID and patents

Unprecedented. The Rapid Innovation Response to COVID-19 and the Role of Intellectual Property 

Political determinants of health

 The Political Determinants of Health

In this book, Daniel E. Dawes argues that political determinants of health create the social drivers—including poor environmental conditions, inadequate transportation, unsafe neighborhoods, and lack of healthy food options—that affect all other dynamics of health. By understanding these determinants, their origins, and their impact on the equitable distribution of opportunities and resources, we will be better equipped to develop and implement actionable solutions to close the health gap.

Value-based pricing: a controversial narrative

 Rethinking value in health innovation: from mystifications towards prescriptions

From the abstract:

Debates over value in health innovation in the U.S. and Europe have
become increasingly dominated by “value-based pricing”. We examine
this prevailing narrative and its weaknesses and then present an
alternative framework for rethinking value in health. Drawing on
scholarship from the political economy of innovation, we argue that
value in health must be considered in terms of both value creation
as a collective process amongst public and private actors, as well as
value extraction that occurs due to financialization. In building this
alternative framework, we pose three questions that present areas
for further research and public policy change

Precision medicine (2)

 Advancing Healthcare Through Personalized Medicine

AI everywhere (16)

 The Doctor and the Algorithm. Promise, Peril, and the Future of Health AI

AI is a clear and present danger to health, safety, and equity. AI also has the potential to improve clinical care profoundly. Both of these statements are true, and both are false by dint of their incompleteness. This kind of indeterminacy is a common problem in medicine. Famously, pharmakon (the Ancient Greek word at the root of pharmacy) means “drug” but can connote either cure or poison. The Paracelsian maxim that “the dose makes the poison” is likewise a common, albeit misleading, trope of introductory pharmacology. In many ways, AI is a pharmakon. It can be both cure and poison. The indeterminacy of a pharmakon is inarguably a challenge for medicine, but it does not bring healthcare to a halt. Rather, doctors, researchers, and regulators have slowly built up, over the centuries, systems of checks and balances that ideally lead toward more pharmakon-qua-cure than pharmakon-qua-poison. Please do not misunderstand me. This has certainly not been some sort of steady progression toward a better world. I am not trying to sell a story about the inevitability of scientific progress.

Health reform zombies (3)

 Health Reform Without Side Effects: Making Markets Work for Individual Health Insurance