Personalized Diagnostics

What can we learn from previous pandemics to apply to the current situation?

What do we actually know to be true about the novel coronavirus?

Jeffrey Taubenberger, MD, PhD, a physician-scientist and investigator at the National Institutes of Health, joins us to discuss his landmark work in sequencing the 1918 Spanish flu virus and to provide insights into the current novel coronavirus global pandemic.

Change can be slow - particularly in #healthcare.

Establishing clinical validity and clinical utility can be slow.

Getting regulatory approvals can be slow.

Gaining payor acceptance can be slow.

Where are we in this megatrend of precision #medicine?

Since the human genome has been sequenced, it has become clear that the technology to sequence has far outstripped our capabilities to accurately classify and interpret genetic variants.

It turns out that genetic variants are much more common than we ever suspected and many - in some cases most - variants are of uncertain significance.

But is the attempt to accurately classify Variants of Uncertain Significance (VUS) a losing strategy?

We have seen tremendous advances in sequencing technology. And the cost to sequence is going to zero, according to Moore's Law. More and more genes and gene sets are being correlated with clinical outcome and response to therapy.

Is bioinformatics intelligence the missing link to realizing the promise of precision medicine?

Will a company emerge as the Google or Amazon of cancer informatics?

Our guest is Bruno Larvol, of the eponymous healthcare data company, Larvol.

"We have to evolve."

Establishing a "gold standard" for real world evidence will allow us to move beyond what we can learn from the 4% of patients enrolled in clinical trials and allow #innovation to flourish.

Fewer than 4% of oncology patients ever make it onto a clinical trial. And these 4% may not even reflect the real-world patient experience.

How can we use real world data in a rigorous and thoughtful way to come up with new standards of evidence to help move innovation forward?

There’s no question that we are awash in promising new technologies with the potential to advance precision medicine.

But is the existing infrastructure adequate to bring innovation into patient care?

It's generally recognized that the highest levels of evidence are generated via the prospective randomized trial. These trials, however, are extremely costly and time-consuming and generate only a limited number of conclusions from a small subset of patients which may not be truly reflective of the real-world patient experience.

Will we be able to evolve and find new ways to generate high levels of evidence to move precision medicine forward?

There’s no question that we are awash in promising new technologies with the potential to advance precision medicine.

But is the existing infrastructure adequate to bring innovation into patient care?

It's generally recognized that the highest levels of evidence are generated via the prospective randomized trial. These trials, however, are extremely costly and time-consuming and generate only limited conclusions from a small subset of patients which may not be truly reflective of the real-world patient experience.

Will we be able to evolve and find new ways to generate high levels of evidence to move precision medicine forward?

Dane Dixon, MD, of Taproot Health joins us in one of our most important episodes to date.

The diagnostics #industry is very fragmented, in terms of testing laboratories, test developers, and testing methodologies used.

Companion diagnostics testing for targeted therapies is still done by a variety of methodologies, including immunohistochemistry, FISH, RT-PCR, RNA expression analysis as well as next-generation sequencing, and others.

The advent of next-generation #sequencing, as many predicted, has not - as of yet - led to a more unified approach to testing. Why is this?