Entering the Blogosphere

This is the post excerpt.

Introduction

Happy New Year and welcome to my first blog posting! Perhaps the initial question to address in one’s inaugural blog posting is: why create a blog? For me the answer lies in my efforts to make sense of the rapidly changing terrain in science and medicine, and its impact on the field of pathology.

douglas-clark

My perspective

In this first blog posting it might be useful to provide you with my professional background so you can see what experiences shape my opinions. Most of my professional life has been spent at academic medical centers on the East coast of the US. During part of that time I was also the Scientific Founder of a small biotechnology company. My research interests have ranged from basic cell biology to translational molecular biology, particularly in the areas of oncology and molecular biomarkers. I am also a practicing diagnostic Anatomic pathologist, primarily in the area of Cytopathology. Four years ago I left the East coast to become the chair of the Pathology Department at the University of New Mexico.

Disruption

One way to examine the changes taking place in pathology is through the lens of disruption. The dictionary defines disrupt as: “to break apart or throw into disorder.” However, it may also mean:  “to interrupt the normal course.”   There are several disrupters that will have large impacts on the normal course of pathology that will likely become the topics of my future blog posts.

Molecular technologies and big data

We’re rapidly approaching the point in a research setting where we can identify virtually every gene, mRNA and protein in a population of cells. In fact, we’re getting closer to be able to deeply characterize every single cell in a population of cells. Our clinical challenge is to identify which of these has clinical validity and to generate assays that are analytically valid. To separate the signals from the noise in these data will require robust bioinformatics tools and expertise.
Another source of big data lies in the information we generate every day in the clinical labs. It is likely that there are valuable clinical data buried within the trends and patterns of individual laboratory data points that can be identified and better utilized for proactive health interventions. This too will require expertise in informatics, computer science, and even mathematics.

Computational pathology

Computational Pathology encompasses several different areas, including digital pathology, image analysis, machine learning and deep learning. Digitizing Pathology images will be the foundation for development of sophisticated image analysis tools and even deep learning assist devices to aid in location and interpretation of pathological entities.

Reimbursement

We must acknowledge that declining reimbursement trends will stress traditional pathology labs (particularly those not functioning at peak efficiency). While we must strive for fair reimbursement, we must simultaneously ensure that we are key players in areas where reimbursement will be focused in the future, including overall clinical quality, safety, value and outcomes.

Optimism

Although these disrupters will create some growing pains, and will require an infusion of new skills into our profession, I see tremendous opportunities to transform pathology into a vibrant and critical profession in the precision medicine of the future.  Hopefully my future blogs will encourage a dialog that will inspire us on this path. While I will strive to make my posts evidence-based, they will be filled with my opinions and are not intended to be comprehensive reviews of the topics I discuss.
Until next time!

 

One thought on “Entering the Blogosphere”

  1. Dr. Clark, I agree with your statement that clinical lab data is a data-rich source of information. That is true and always will be true. The challenge is how to interrogate it to provide meaningful and clinically-actionable insights. There is so much more inside of that than we can see, interpret, and understand. Pathology needs more data scientists who can team up with clinical scientists to work together to find the answer we all seek. There is much to be done.

    Like

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s