The Antidote. Inside the World of New Pharma
A review of 25 years of Vertex
The Billion-Dollar Molecule. The Quest for the Perfect Drug
On the business of science, and about the Vertex pharmaceutical firm and its IPO.
How New Models Of Vaccine Development For COVID-19 Have Helped Address An Epic Public Health Crisis
This acceleration has largely been fueled by an influx of resources—both financial and human—that is likewise record-setting. Significant levels of cooperation and innovation, which enable more-efficient use of those resources, have also played a key role.
There may be additional opportunities for innovation that deserve exploration. For example, master protocols, in which multiple vaccine or drug candidates are tested against a single control arm, could further accelerate clinical trials without compromising safety. Innovations to overcome potential delivery impediments, including supply chain challenges and insufficient numbers of health care workers in some regions, would also be welcome.
If widespread COVID-19 vaccination is realized in the coming months and years, the approach undertaken to arrive at that point will offer lessons for how to optimize the development and accessibility of vaccines against other pathogens, under both outbreak and non-outbreak scenarios. Our experiences with COVID-19 may also offer knowledge spillovers to other areas of medicine and public health.
More details in this Health Affairs issue.
Government, Big Pharma, and The People. A Century of Dis-Ease
A book to read, with this Table of Contents:
White Market Drugs. BIG PHARMA AND THE HIDDEN HISTORY OF ADDICTION IN AMERICA
A book to understand the contribution to addiction over a century.
By showing how the twenty-first-century opioid crisis is only the most recent in a long history of similar crises of addiction to pharmaceuticals, Herzberg forces us to rethink our most basic ideas about drug policy and addiction itself—ideas that have been failing us catastrophically for over a century.
This is the outline:
IntroductionComplicated legacies: The human genome at 20
On genome and precision medicine:
Debates about precision medicine (PM), which uses genetic information to target interventions, commonly focus on whether we can “afford” PM (17), but focusing only on affordability, not also value, risks rejecting technologies that might make health care more efficient. Affordability is a question of whether we can pay for an intervention given its impact on budgets, whereas value can be measured by the health outcomes achieved per dollar spent for an intervention. Ideally, a PM intervention both saves money and improves outcomes; however, most health care interventions produce better outcomes at higher cost, and PM is no exception. By better distinguishing affordability and value, and by considering how we can address both, we can further the agenda of achieving affordable and valuable PM.
The literature has generally not shown that PM is unaffordable or of low value; however, it has also not shown that PM is a panacea for reducing health care expenditures or always results in high-value care (17). Understanding PM affordability and value requires evidence on total costs and outcomes as well as potential cost offsets, but these data are difficult to capture because costs often occur up front while beneficial outcomes accrue over time (18). Also, PM could result in substantial downstream implications because of follow-up interventions, not only for patients but also for family members who may have inherited the same genetic condition. Emerging PM tests could be used for screening large populations and could include genome sequencing of all newborns, liquid biopsy testing to screen for cancers in routine primary care visits, and predictive testing for Alzheimer's disease in adults. These interventions may provide large benefits, but they are likely to require large up-front expenditures.
Now that Jeff Bezos anounces that he is to step aside as CEO, a summary in one figure:
The history, in one book:
Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women
Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.
However,
We found strong evidence of an association with breast cancer risk (Bayesian false-discovery probability, <0.05) for protein-truncating variants in 9 genes, with a P value of less than 0.0001 for 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) and a P value of less than 0.05 for the other 4 genes (BARD1, RAD51C, RAD51D, and TP53).
None of the other 25 genes in the panel had a Bayesian false-discovery probability of less than 0.10. Of note, 19 genes had an upper limit of the 95% confidence interval of the odds ratio of less than 2.0, with 2.0 representing a proposed threshold for “pathogenic, moderate risk alleles”9; we therefore conclude that these genes are not informative for the prediction of breast cancer risk. We confirmed that missense variants in BRCA1, BRCA2, and TP53 that would be classified as pathogenic according to clinical guidelines are indeed associated with clinically significant risks. We also found that rare missense variants in CHEK2 overall, as well as variants in specific domains in ATM, are associated with moderate risk.
The summary:
Variants in 8 genes — BRCA1, BRCA2, PALB2, BARD1, RAD51C, RAD51D, ATM, and CHEK2 — had a significant association with breast cancer risk.
Biotechnology in the Time of COVID-19
Our journey is far from over. In my mind, it is our responsibility as an industry, as a company, and as global citizens to help ensure a pandemic of this magnitude never happens again. I’ve worked in infectious diseases for my entire career—and I’ve been exposed to the disruption, the health crises, and the economic fallout they create. It is up to all of us to bring forward solutions. I hope you will join the many companies, worldwide health agencies, and nongovernmental organizations that are answering the call. Together, we can all use our skills to help serve people in this remarkably urgent time of need.
Great words by Stephane Bancel, CEO of Moderna
Recent evolutions of machine learning applications in clinical laboratory medicine
You'll find an interesting review about laboratory medicina and machine learning in this article, with applicatons to chemical chemistry, hematology and microbiology.
There has been a recent rise in various ML applications in the field of clinical laboratory medicine. Despite the potential of ML to ameliorate the efficiency of laboratory processes and optimize diagnostic workflows, translation into routine practice is still slow-going. There is a need to raise more awareness about the vast ML landscape among laboratory professionals. Educational programs dealing with theoretical ML concepts as well as their associated challenges and opportunities could stimulate wider acceptance and exploitation in the clinical laboratory. It is important to realize that ML will not immediately function as a surrogate of the laboratory professional’s neural networks, but will rather act as a valuable supportive tool with the capability of increasing the odds on optimal outcomes for patients accessing health care.
Margaret Huntington Boehner