The point of this blog and Data & Donuts isn't to bash pharma or offend an entire category of stakeholder in the healthcare evolution and debate. I share information and ideas. I try not to portray answers but I do want to raise questions--and question answers. A recent blog post about the role of marketing interests in CME resulted in a weird mix of accusations and disengagement. I would suggest it would be more useful to debate the data not the person reporting the information.
When I worked in medical advertising or education I only knew one viewpoint. The customer was the pharmaceutical company. I confess that when I began working directly on behalf of patient advocacy groups, physicians, and non-industry stakeholders the dialogue changed. I listened to their concerns, attended their meetings, and discovered another perspective. I am going to say the real answers are at the cross-section of all of the information. The narrative was unfamiliar but insightful. I decided to share what I heard, read, or discussed with end-users of clinical education, medical information, evidence-based medicine and yes, marketing.
I have been asked what I think about the PBS NOVA presentation "Can Alzheimer's Be Stopped." I am sure it plays differently to viewers not familiar with the research history and debates but it primarily focused on the history from the monotherapeutic search for a cure and even included a plea for clinical trial participation-- "Enroll trials faster we can get there sooner--only answer is research."
Drug makers continue their race to find preventative or curative treatments although less than 1% of drugs developed thus far have been approved--and only show minimal effectiveness in slowing progression. I certainly hope they are successful. But I think there is a lot of evidence emerging that should indicate--or at least in a Bayesian construct-- how low the probability is likely to be. Think of a Bayesian prior probability distribution or a prior--these can be the result of prior clinical experiments. In this case, many experiments have yielded less than promising results. The Bayesian theorem estimates the conditional distribution of an uncertain quantity by calculating the product of the prior and the likelihood function. How likely is an event to occur when considering prior evidence. I know, I know. It is oversimplified--but you get the main idea.
The research of Remback et al. identified Beta2M as the most frequently connected biomarker across all marker sets and clinical groups in the clinical study, Bayesian Graphical Network Analyses Reveal Complex Biological Interactions Specific to Alzheimer’s Disease. I have always wanted to see this approach applied to potential targets for research in AD.
The David H. Koch Fund for Science is a major funder of NOVA. He has been a member of the Board of Trustees of WGBH in Boston, NOVA’s presenting station and top PBS producer, since 1997 and has been a supporter of the station since 1982. According to a report last year in Current, the public broadcasting news organization, he has donated $18.6 million to the station, more than half of which has gone to NOVA. Koch is a graduate of MIT with a longtime interest in science and engineering and he and his brother, Charles, are among the country’s leading philanthropists.
As NOVA’s Apsell* states above, there is no consultation with or by Koch on NOVA choices and programs, and there is no evidence, at least that I have knowledge of, that he has sought to interfere or influence coverage. PBS and the station also argue that it is important to have a diverse spectrum of “pursuits and viewpoints” on their boards, as in their viewership, which seems reasonable.--PBS Ombudsman Michael Getler
*NOVA’s Senior Executive Producer, Paula Apsell
I don't recall where I found this little image. I consider it a homunculus of possibilites and will continue to explore the evolving research in all areas and context.
Follow along here or at @alzheimersbrand