04 de març 2019

Pharma landscape

The Global Use of Medicine in 2019 and Outlook to 2023

The summary of IQVIA report:

  • Global spending on medicines reached $1.2 trillion in 2018 and is set to exceed $1.5 trillion by 2023.
  • Invoice spending in the United States is expected to grow at 4– 7% to $625–655 billion across all channels, but net manufacturer revenue is expected to be 35% below invoice and have growth of 3-6% as price growth slows on both an invoice and net basis.
  • Net drug prices in the United States increased at an estimated 1.5% in 2018 and are expected to rise at 0–3% over the next five years.
  • China reached $137 billion in medicine spending in 2018, but will see growth slow to 3-6% in the next five years as central government reforms to expand insurance access to both rural and urban residents, as well as expansions and modernizations of the hospital system and primary care services have been largely achieved and efforts shift to cost optimization and addressing corruption.
  • Medicine spending in Japan totaled $86 billion in 2018, however spending on medicines is expected to decline from -3 to 0% through 2023, due to the effect of exchange rates and continued uptake of generics and offset by the uptake of new products.
  • The number of new products launched is expected to increase from an average of 46 in the past five years to 54 through 2023, and the average spending in developed markets on new brands is expected to rise slightly to $45.8 billion in the next five years, but represent a smaller share of brand spending



01 de març 2019

Rescuing citizens from the "rule of rescue"

People feel a need to rescue identifiable individuals facing avoidable death or harm. This is a well known fact  explained in 1968 by the Nobel laureate Thomas Schelling from an economic perspective  and by Jonsen  in the bioethics context in 1986.
"A single death is a tragedy; a million deaths is a statistic." This quote reflects exactly what we are talking about. However, the issue is: Do you accept the rescue at any price with public money?
These previous posts of this blog: (1) and (2) explain the details. I'll not insist on what I've already said. I suggest you have a look at them.
Today you can asess these three facts:
1. A country spends 38m € in drugs for 249 patients in 2018. A lifetime treatment.
2. A country has a waiting list of 132.025 patients for surgery, 123.249 patients for diagnostic tests, and 424.715 patients waiting for a visit to the specialist. Total people waiting: 679.989 patients in a country with 7.543.825 inhabitants. 9% of the population is in the waiting list for a health service. However, 25% have voluntary duplicate insurance and could jump the list. Therefore the exact figure is 12% of inhabitants waiting.
3. A country knows that spending 10m € in addition every year can increase cardiac surgery by 600 interventions. This means 600 critical patients less in the waiting list. With 38m €, the number of cardiac interventions would be 2.280.
 Ask yourself what to do about it, what would you prefer to do with 38m€ every year ? Just apply them to 249 patients or to 2.280 (you are not on the waiting list, and we'll assume the same adjusted quality of life years for both cases). Anyway, it's too late to have your answer, the government has already decided for you, and maybe you don't agree with it, as I don't agree. The government prefers the rescue of 249 citizens.
Just to finish, check this final fact:
This country spends 1.192 € per capita of public budget on health. Another country under the same mandatory tax system is able to spend 1.635 €, 40% more !!!
More money allows to avoid such dilemmas for this country. Ask yourself if you want to stay in the former tax system that is damaging your health. Once you have the answer, you'll understand why this country wants to leave this unfair tax system as soon as possible.



23 de febrer 2019

Pharma returns

Measuring the return from pharmaceutical innovation 2018

Key findings for top 12 biopharma companies in the Deloitte study.
  • R&D returns have declined to 1.9 per cent, down from 10.1 per cent in 2010 - the lowest level in nine years
  • Returns have been impacted by the growing cost of bringing a drug to market which now stands at $2,168 million – almost double the $1,188 million recorded in 2010
  • Forecast peak sales have declined from last year to $407 million – less than half the 2010 value of $816 million
The growing cost of new drugs includes buying companies for their research (outsourcing research) instead of "producing" R&D within the company. The report will not tell you this minor observation.
Last February I said :
In drug industry the probability of R&D failure is 90.4%. We all know that in the drug costs we are paying also for failures, but we easily forget the figure.
You'll not find any reference to this minor issue. Is there any profitable industry with such a failure rate?


Caro Emerald

22 de febrer 2019

The bioethics of machine clinical decision making

Artificial intelligence (AI) in healthcare and research
Regulation of predictive analytics in medicine

This is what a brief note from Nuffield Council of Bioethics says about artificial intelligence in healthcare:
The use of AI raises ethical issues, including:
  • the potential for AI to make erroneous decisions; 
  • the question of who is responsible when AI is used to support decision-making; 
  • difficulties in validating the outputs of AI systems; inherent biases in the data used to train AI systems; 
  • ensuring the protection of potentially sensitive data; 
  • securing public trust in the development and use of AI; 
  • effects on people’s sense of dignity and social isolation in care situations; 
  • effects on the roles and skill-requirements of healthcare professionals; 
  • and the potential for AI to be used for malicious purposes.
A key challenge will be ensuring that AI is developed and used in a way that is transparent and compatible with the public interest, whilst stimulating and driving innovation in the sector.
This statement is naive.(From m-w, naive:  marked by unaffected simplicity : INGENUOUS). Up to now, have you seen any transparent algorithm available for imaging, triage or any medical app? For sure not. Therefore, the real key challenge is to stop introducing such algorithms -to ban apps- unless there is a regulatory body that takes into account the quality assurance or effectiveness side (sensitivity and specificity) and the required transparency for citizens.
Until now Nuffield has released only a brief. Let's wait for the report.
If you want a quick answer, check Science this week:
To unlock the potential of advanced analytics while protecting patient safety, regulatory and professional bodies should ensure that advanced algorithms meet accepted standards of clinical benefit, just as they do for clinical therapeutics and predictive biomarkers. External validation and prospective testing of advanced algorithms are clearly needed
 They explain the five standards and give rules and criteria for regulation. It is really welcome.



21 de febrer 2019

Pharm niche busters

The Information Pharms Race and Competitive Dynamics of Precision Medicine: Insights from Game Theory
Economic Dimensions of Personalized and Precision Medicine
Precision medicines inherently fragment treatment populations, generating small-population markets, creating high-priced “niche busters” rather than broadly prescribed “blockbusters”. It is plausible to expect that small markets will attract limited entry in which a small number of interdependent differentiated product oligopolists will compete, each possessing market power.
A chapter in a new book on  Precision Medicine explains the new approaches to a oligopolistic market structure where the size of the market may be determined by biomarkers with a cut-off value suggested by pharmaceutical firms themselves. The dynamics of this market is described according to game theory. Sounds fishy at least.
I already have pending chapters to read of this book. A must read for physicians and economists.



16 de febrer 2019

Defining roles and skills for digital health

The Topol Review
Preparing the healthcare workforce to deliver the digital future.

The NHS asked Dr. Eric Topol about the new health workforce and how digital health will change the current landscape. A must read:
This is an exciting time for the NHS to benefit and apitalise on technological advances. However, we must learn from previous change projects. Successful mplementation will require investment in people as well s technology. To engage and support the healthcare workforce in a rapidly changing and highly technological orkplace, NHS organisations will need to develop a learning environment in which the workforce is given very encouragement to learn continuously. We must better understand the enablers of change and create culture of innovation, prioritising people, developing an agile and empowered workforce, as well as digitally capable leadership, and effective governance processes
to facilitate the introduction of the new technologies, supported by long-term investment.

15 de febrer 2019

Who is worse off?

Health, priority to the worse off, and time

The prioritisation of resource allocation towards the worse off is a well known rule. What does this mean exactly?
 There are many dimensions in which someone can be worse off (e.g., in terms of wellbeing, health, opportunities, resources), and there are many ways to give priority to someone (e.g., by giving extra weight to their claims, lexical priority to their claims, or by earmarking a fixed amount of resources for their claims). Furthermore, there are many different reasons why one might want to give priority to benefits to the worse off: is it because it is good to promote equality for its own sake, good to promote equality for other reasons, because benefits to the worse off matter more, because the worse off typically fall under some sufficiency threshold, or for many of these (and maybe other) reasons
The precise argument is described in a recent article that combines the complete lives approach with the forward looking approach, and says:
 I believe that the focus on complete lives has been beneficial in that it is a step away from a complete focus on current distributions of health. However, I think that the arguments presented in this paper give us reason to adopt a more nuanced approach to how to rank individuals in terms of who is worse off with the purpose of giving priority to certain benefits in light of unequal distributions of health over time. Such an approach accepts that both the complete lives view and the forward looking view that only takes into account current and future health states, matter. This leads to the complicated question of how to combine these views. Some work that addresses how to combine  concerns for simultaneous segment inequality and complete lives inequality has appeared recently, but the question needs further attention.
Therefore, it is still a work in progress.