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Welcome to the Personalized Diagnostics Podcast.
We are going to be talking to some of the greatest minds and personalities in the diagnostics space – the engine which is driving personalized medicine forward.
We will be exploring the unmet need for better diagnostics across the patient journey - from screening to treatment to treatment monitoring, new assay development, technologies such as next generation sequencing and artificial intelligence plus we’ll be tackling issues in reimbursement and health economics- how we’re going to pay for all this and how diagnostics can provide value to the health care system.
Thanks for listening.
We are going to be talking to some of the greatest minds and personalities in the diagnostics space – the engine which is driving personalized medicine forward.
We will be exploring the unmet need for better diagnostics across the patient journey - from screening to treatment to treatment monitoring, new assay development, technologies such as next generation sequencing and artificial intelligence plus we’ll be tackling issues in reimbursement and health economics- how we’re going to pay for all this and how diagnostics can provide value to the health care system.
Thanks for listening.
79 Episodes
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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?
With the advent of next generation sequencing, we've gained the ability to test for nearly any and all genomic alterations – many or most of which are benign or of uncertain significance.
And, believe it or not, we encounter many benign or uncertain alterations in tumor related genes.
Targeted therapies have historically been developed with a relatively small number of alterations in mind. For example, KRAS testing focused originally only on codon 12 and 13 mutations. While, 90% of deleterious EGFR alterations in lung #cancer are either chromosome 19 deletion or the L858R mutation.
Are we in danger of watering down the size of the effect in clinical trials for targeted therapies by trying to incorporate too many genomic alterations in their #design?
Will this be a golden #era for #diagnostics?
Are we moving away from a model based on high-value #therapeutics and towards one based more on high-value diagnostics?
September 25, 1998 - trastuzumab, one of the first targeted therapies with a companion diagnostic, received #FDA approval in breast #cancer.
The commercially available IHC and FISH companion #diagnostics were not incorporated into the pivotal clinical trial. They had to be subsequently "developed" and validated by way of concordance studies (which were not stellar).
Does this still happen today? Have we begun to appreciate the importance of embedding companion diagnostics directly into clinical trials?
Over the past 20 years we've seen the development of approximately 40 indications for targeted therapies with a companion diagnostic. How can we continue to build on these successes and develop even more effective strategies for developing targeted therapies with companion diagnostics and incorporating diagnostics into clinical trials?
Our guest is Tracy George, MD, Professor of Pathology at the University of Utah and the Executive Director of clinical trials and pharma DX at ARUP Laboratories.
We’ve all heard the term “epigenetics.” But what does it actually mean?
#Epigenetics is the study of changes in organisms caused by modification of gene expression rather than alteration of the genetic code itself.
It is somewhat of a catch-all term and does not apply to any one type of change or any one methodology for measuring these changes.
There appears to be a clear association between age and underlying chronic conditions such as #diabetes and #hypertension and the severity of a #covid19 illness.
Can epigenetics inform us of our risk of acquiring acute or infectious illnesses such as Covid-19 and their severity?
How do we age?
We've all heard the term biological age. But what does it mean exactly? How is it measured? And is it possible to "turn back the hands of time?"
Does the key to health, wellness and longevity lie in epigenetics?
We are joined by Dr. Tom Stubbs, Co- founder and CEO of Chronomics
Slow down - testing for SARS-CoV-2 is not as simple as it may seem.
“What I really want to know is: if this test result is positive, what are the chances that my patient actually has the condition.
“Sensitivity and specificity really have no utility in a practical everyday clinical setting.
“You really want to know the positive predictive value and the negative predictive value.”
Slow down - testing for SARS-CoV-2 is complicated.
Jill Hagenkord, MD, FCAP is co-founder and CMO of MDisrupt, as well as previously serving as CMO at Invitae, Complete Genomics Inc., Color, and 23andMe.
She joins us for this first installment of "Hagenkord's Korner."
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