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About admin

DeeAnn Visk, a medical writer and editor science writer, writes a variety of content: scientific peer-reviewed papers, white papers, abstracts, presentations, posters, and web content. She lives in Poway, CA with her husband, two kids, and one very spoiled hen. For more information, view her LinkedIn profile at: www.linkedin.com/in/deeannv/

how everyone sees SEO differently

Search Engine Optimization for Medical Writers

Demystifying Search Engine Optimization for Medical Writers

Mystery surrounds search engine optimization (SEO).  What is the best way to accomplish SEO?  Pay for Google ads?  Find a shady, off-shore company to click on your site 100,000 times?  Use a consultant?  Plunge into the SEO world on your own? This article will assist content generators to better understand and assist clients with SEO.  As communicators of information, medical writers need to be aware of what works and what does not in writing for the purpose of search engine optimization (SEO).

Having good solid information for readers in the best SEO.

Google considers pages that have “an impact on your current or future well being [sic]” Your Money or Your Life (YMYL) pages.  YMYL pages contain content deemed by Google to have a big impact on your life—obviously medical information falls into this category.  YMYL pages are scrutinized more than non-YMYL pages.

To understand SEO, it is necessary to understand how a Google search works.  Google keeps its computer program, or algorithm for searching the web, a deep, dark secret.   That’s fine; I am not qualified to dissect lines of code—let’s go with broader concepts.  Google web crawls, or looks through the content of web pages.  Web crawling is done automatically, any time of the day or night.  The website needs to be available at all times (no down servers), to keep the web crawlers (called spiders) happy.

how everyone sees search engine optimization differently

SEO humor:  how everyone sees it differently

White Hat vs. Black Hat Methods

As with many things, there are “white hat” and “black hat” methods.  White methods are good, upfront means to build SEO.  Black hat methods are seen as devious and underhanded.   The preferable way to optimize your ranking in a search engine is to develop good, useful content. This is white hat SEO, versus trying to fool the search engines, the black hat approach.

Black Hat Methods to Avoid

Some of the black hat techniques that have been tried in the past include key word stuffing:  simply adding keywords about 200 times to the bottom of a webpage. This worked until Google nixed it.   Then there were hidden key words, adding hundreds of keywords on a webpage in white on a white background—you can’t see it, but Google’s spiders can.  This worked until Google nixed it.  Next there were link farms, websites set up just to link to your page. This worked until Google nixed it.  (See a pattern developing here?)

Having all kinds of slick tricks may work for a while, until Google realizes what you are up to, which will then lead to your ranking sinking like a rock.  Google can and will penalize your site in the rankings if you violate their best practices guidelines.  Or they could even remove you from their indexing service. 

illustration of white hat and black hat

Different methods of SEO

Black hat methods are eventually figured out by Google.  Once Google finds out what you are up to, not only will the ruses fail to work, you will be punished.  Try to stick to the white hat method of SEO—develop good content that is useful to readers.

Details on White Hat Methods for Search Engine Optimization

1.  Select appropriate key words. This can be trickier than it sounds.  Brainstorming with the client is a good place to begin.  If you are working on a project, be sure to visit Google Ad Words. I believe you can still set up an account without having to purchase anything.  Use the tools to search various words that your target audience may use to find your client.  Google will give you data on how often these words are searched on Google’s search engine.

2.  Find a good online text editor with SEO optimization tools. Online webpage text editors such as Word Press offer free SEO plug-ins like SEO powered by Yoast. Or if you are writing a scientific paper, ensure that keywords are in the title, abstract, and throughout the article; a simple keyword search in your favorite text editor will suffice.

3.  Make your file names keyword rich. Include keywords in all file names, whether for text, images, or other media.  Title display in search engines is limited to first 70 characters, so keep your headlines brief and keyword rich.  Your URL (Uniform Resource Locator or website address) also needs to have keywords.  Don’t go overboard with keywords—limit yourself to 5 to 7—or Google will move you down in the rankings.

4.  Ensure a minimum of 300 words per page. If there are more than 700 words, reader frequently stop reading because it takes too long. Google gets bored with long pages, too.  Longer posts should be broken up into several pages.  Rather than present readers with a wall of text, remember to use quotation pull out, subheadings, and graphics.  [Side bar:  This article is longer than 1000 words, but since it is targeting medical writers, for whom plowing through several 5000-word papers are all in day’s work, that is fine.]

5.  Link to other sites with excellent content. I am thrilled that the Mayo Clinic webpages have such a high ranking in the Google search engine.  They are a known, trusted name in medical matters, so be sure to look for content on their site (to which you can link) that may also be of interest to your readers.  When reading on the Mayo Clinic website, I never find myself thinking “this was going along swimmingly, but now the writer is on Planet Crazy.”

 

 

Several of the words used in this article: Google, content, keyword, medical writer, search engine optimization

Word Cloud based on this article.

6.  Write with the end goal in mind: Are you publicizing your group, promoting your personal brand, or working for a client to sell products? Information is key. Be sure to inform your readers about good information they need.  Normally, medical writer generate informational web content for a general audience, like those visiting websites.  Use simpler sentence construction and terminology.

7.  Add images and other media. Good pictures, graphics, charts, cartoons, and even videos added to your pages will improve search engines rankings.  While you want the images to display with enough resolution to avoid pixelation, do not make them huge—300 by 300 pixels is a good ballpark for image size.  Smaller or larger sizes may work, too.  Remember to use keywords in the meta-information for your pictures and other media.  Get permission to use images or pay licensing fees for stock images.

8.  Content is king. Write content well, with useful information for your audience. Produce high quality content and remove any low-quality content.  Encourage sharing and commenting on your content.

9.  Maintain your website. Regularly check for broken links and either fix or remove them. Google is serious: they threatened to de-list a non-profit website for not fixing a hacking that took advantage of their excellent SEO.  Keep in mind a major redesign of a website may drastically change your search ranking.

10.  Are your SEO efforts paying off? Check your rankings once a month to show concrete measures of how well your SEO efforts are paying off.

DeeAnn Visk, PhD, is a freelance medical writer and editor. Pharmacogenetics, high throughput screening, cell culture, molecular biology, and in vitro diagnostics are her areas of expertise. DeeAnn lives in the San Diego area with her husband, kids, and two spoiled hens. You are welcome to contact her at deeannlwv@gmail.com.

© 2018 DeeAnn Visk. All rights reserved

 

Metabolomics integrates the effects of the environment with the effects of genetics

Metabolomics and Precision Medicine

Advancing Precision Medicine: Genomics, Metabolomics, and Clinical Trials

Monday, October 12 was the evening of an interesting talk at BIOCOM. Teresa Gallagher, founder of the San Diego Clinical Research Network (SDCRN) introduced the moderator of the event, Arnold Gelb, MD, Senior Medical Director at Halozyme. Rather than attempt to summarize all of the topics examined, the goal of this blog is to give a sampling of some of the areas discussed during the event.

Deterministic versus probabilistic genetics

The first speaker of the evening was Amalio Telenti, MD, PhD, Head of Genomics at Human Longevity, Inc. His talk touched on the ever-present nature vs. nurture debate. Do our genes determine a particular characteristic or merely influence the probability of developing that characteristic? In the world of whole genome sequencing, this can be described as deterministic versus probabilistic genetics.

In general, a deterministic trait would be something like Tay-Sachs Disease: if you have two copies of the gene for this condition, you have a better than 99% chance of developing the disease. A probabilistic trait is one with many genes that influence it, like height. Outside factors like disease and diet also affect how tall an individual grows. Hence, height is a probabilistic trait.

Telenti predicted that genomics will not revolutionize all aspects of medicine; but some medicine will be revolutionized profoundly; clinical trials will benefit the most. Genomics will be employed to stratify patient populations both before studies are commenced and after all the data is collected. Ideally genomics will be utilized to both determine who benefits from a drug and who should not take the drug.

Metabolomics combines genetics and environment

Steve Watkins, PhD, Chief Technology Officer of Metabolon spoke next.  Metabolon specializes in metabolomics, offering comprehensive measurements of small molecules such as glucose, cholesterol, cortisol, and amino acids in a CLIA-certified lab.

Metabolites reflect the integration of genetic and environmental influences on an individual.  Diseases can be prevented and diagnosed by checking on an individual’s metabolites. Response to disease treatment can be monitored by testing metabolites. Metabolomics is emerging as an effective tool in precision medicine.

Metabolomics integrates the effects of the environment with the effects of genetics

A person’s genome and environment affect their metabolome. Used with permission from Metabolon.

Watkins shared that Proceedings of the National Academy of Sciences recently published a study led by Baylor University’s Tom Caskey, MD. Caskey comprehensively tested the metbolites of many patients with no frank disease.  Metabolon’s platform spotted underlying health issues not previously noticed in the patients’ genetic data.

For example, Patient 3905 had very high levels of sorbitol and fructose, but no clinically significant mutation was reported in their genome.  Looking back at the genomic data for that individual, a mutation in the fructose pathway indicating “fructose intolerance” was discovered. This mutation had been overlooked previously. When discussing these results with the patient, the patient simply stated that fruit bothered him, so he refrained from eating it.

In the same study, Patient 3923 carried a gene for Xanthinuria type 1.  He showed no symptoms of the disease such as kidney stones, suggesting the gene was not penetrant (or not expressed), leaving the patient symptom-free.

In conclusion, Watkins stated that metabolomics can be used in a number of ways:

1)  By identifying pathways of interest for genetic assessment

2)  By revealing non-penetrance of genes suspected of being deleterious

3)  By enabling monitoring and understanding of metabolic conditions

Which drugs to use in cancer treatment?

The final speaker for the evening was Nicholas Schork, PhD Professor and Director of Human Biology at the J. Craig Venter Institute. He focused on emerging themes of design for precision medicine trials.

Schork presented several novel ideas. One was the idea of vetting algorithms for the treatment of cancers based on the mutations the cancers carry. Some hospitals already use this method, begging the question of who has the best algorithm for cancer treatment. As Schork points out, this has led to some interesting conversations with the FDA. He envisions clinical trials in the future for the evaluation of algorithms for cancer treatment with existing drugs, in direct contrast to the conventional clinical trial, usually designed to assess the effectiveness of a new drug.

In all, this was an exciting presentation of cutting-edge research and future directions in precision medicine.

Yes, these are lipids. But there are so many more inside your body; and they do more than store fat!

Annual Lipids Meeting in La Jolla California

The 2015 meeting on Lipids—focusing on their impact in cancer, metabolic, and inflammatory diseases—took place on Tuesday and Wednesday, May 12 and 13 at the Scripps Seaside Forum at UCSD’s Scripps Institute of Oceanography (SIO). With a beautiful venue and superb facilities, what more can you ask for? How about some really interesting science.

Lipids are generally thought of as fats. But in a biological system, they are much more. They include chemokines and other signaling molecules involved in signal transduction to and from the cell membrane. Metabolically, lipids also play an important role. Innovation in technology allow the study all the lipids in an organism (yeast, bacteria, or animal), leading to a new field of study: lipidomics. Once again, UCSD is on the cutting edge, with an established program and website in the field.

ocean, palm trees, La Jolla pennisula, green lawn with white chairs; breakfast view for lipids conference

View from the Scripps Seaside Forum at UCSD’s Scripps Institution of Oceanography.

Michael Snyder, the keynote speaker, has subjected himself to a battery of “omic” studies including his personal genome, exosome, microbiome, epigenome, proteome, metabolome, transcriptome, auto-antibody-ome, as well as cytokines. Data from these samples comprise the “Snyerdome”. All this was done in the interest of personalized medicine. These studies were done not only at one time point, but over a range of times, making it longitudinal.

Mike sees the data providing insights into how to managing healthcare in healthy individuals to predict risk, diagnose, monitor, and treat the patient, in this case, himself.

“He has also combined different state-of–the-art “omics” technologies to perform the first longitudinal detailed integrative personal omics profile (iPOP) of person and used this to assess disease risk and monitor disease states for personalized medicine” (from lab website).

in the future, Mike sees genomes being sequenced before birth and all this information being channeled through your smart phone. Patients will also bear more responsibility for maintaining their health with all the information they have; they will need to learn to maintain a balanced life.

The next speaker, David Wishart, discussed how to link lipidomics to laboratory medicine. He noted that in the rationalization of translating basic research to something of value in the clinic, researcher often cite the possibility of developing a new:          

  • surgical technique
  • invent a new medical device
  • drug
  • drug target
  • medically important gene
  • biomarker

All these are good outcomes; some are more likely than others. Practitioners of lipidomics are most likely to have the best luck in developing new biomarkers; not many are surgeon and drug development has about a 0.001% success rate from basic science to the prescription bottle.

lipids, lipids, lipids

Slide from David Wishart’s talk listing the number of FDA approved clinical tests from omic data

Discovery of new biomarkers is a realm where omics, specifically lipidomics, will meet a great chance of success. For this comparison, David recommends using the statistical ROC test, which is routinely used to evaluate medical test. This test gives a good sense of a medical test’s specificity and sensitivity by plotting the true positive rate over the false positive rate.

Example of ROC curve with an assessment of the area under the curve. The PSA referred to here is the amount of Prostate-Specific Antigen test; phi refers to a different, more specific calculation with less false positives than the PSA test alone.

 

ROC curve used to show predictive value of a test for prostate cancer using two different methods.

ROC curve used to show predictive value of a test for prostate cancer using two different methods.

Or you can just know that an ROC of 0.5 is worthless, while 1.0 is perfect.

Thus, from the graph above, using the PSA test alone to determine the risk of prostate cancer is poor. A better method is to use the phi method.

Work done looking at 3 to 5 biomarkers can have great ROC results. For example, predicting congenital heart defects by looking at the level of 3 carotenes, yields a ROC of 0.98. Other areas of success with high ROC scores include endometrial cancer, prostate cancer, and chronic fatigue syndrome.

David urged participants to become more quantitative to move their research into the clinic; using the website www.roccet.ca to generate ROC curves for your data is a great place to begin.

The numerous other speakers all gave fantastic talks.

In this smaller conference, I was able to browse through the all posters, read all the titles and talk to the presenters. Large conventions tend to lack the sense of intimacy and fraternity found in this lipidomics meeting. Kudos to the organizers for a successful event. A convivial group, I would highly recommend this meeting.

 

Optimizing 2D Assay Kits for Use on 3D Cultures

Assay Optimization for 3D Cultures

No, not this 3D culture

3D Movie Culture

The culture of 3D movie goers.

But this kind

3D Cultures in a tissue culture context

Tissue culture cells growing in three dimensions.

Traditionally, mammalian cell culture means living cells grown outside the body on specially treated tissue culture plates in specialized incubators. Millions (dare I say billions?) of experiments utilizing this technique leading to huge advances in research and medicine.

To improve on this convention, innovators develop cultures that grow, not just in two dimensions (2D), but three dimensions (3D). General consensus in the field now is that these 3D cultures are more physiologically relevant—closer to native whole organisms—than conventional 2D cultures.

With more use of 3D cultures in business and research, a new challenge to testing larger volumes of cells arises. Almost all previous assays used to test qualities of cells in culture have only been tested and optimized for traditional 2D models. What hurdles face scientist who want to test (assay) their cultures in 3D rather than 2D?

Terry Riss, a Promega scientist, presented his company’s findings in a talk at the Society of Toxicologist meeting on Monday, March 23, 2015 at the San Diego Convention Center. Promega’s work has been primarily conducted with spheroids generated with a hanging drop method from a company aptly named In Sphero

In thinking about differences between 2D and 3D cultures, one huge differences is the ability of reagents to diffuse longer distances into cells. Two dimensional cells tend to grow flat and spread out on the dish surface, allowing great accessibility to the innards of the cells, which scientist are obsessively interested in.

Promega offers various “Glo” assays for cell viability. Generally they are better than the usual MTT or resazurin tests in that they are less toxic to the cells and permit the same cells to be used again after the assays for even more assays (there we go again, us scientist and our obsession with assays).

In general, Riss advocates optimizing any off-the-shelf assays developed for 2D cell culture with your own particular cell line and application (basic good lab practice in my book!).

Try increasing these three parameters:

  • Detergent concentration to lysis the cells
  • Physical disruption used to dissociate the cells
  • Time of incubation

As always, remember to  include controls, both positive and negative, and optimize the experiment to your particular assay needs.

As the drug development moves towards more 3D cell culture models, the need for assays of these cultures will grow.  Promega is adding to their repertoire of kits to meet this need.

revolutionizing cancer treatment

Treating Cancer in the Genomic Era

Revolutionizing Cancer Treatment

by DeeAnn Visk

We have all had “ah-ha” moments.  I had one on October 15, 2013 listening to Dr. Razelle Kurzrock illustrate a new way of thinking about cancer and cancer drug development.  Historically, cancers are categorized by the organ in which they originate.  With the advent of genomic sequencing, cancers can now be grouped by the mutations they contain.  Thinking about cancer in this way will revolutionize how this disease is treated therapeutically, researched in academia, targeted by drug companies, and conceptualized in clinical trial design.

This epiphany occurred at the recent meeting of the Southern California Chapter of Women In Bio at Janssen Labs, while listening to Dr. Kurzrock, one of three excellent speakers at the meeting.

Director of Clinical Trials, Moores Cancer Research Center

Dr. Razelle Kurzrock, Director, Center for Personalized Cancer Therapy

Dr. Kurzrock pointed out that, while the light microscope was invented in 1590, it is still used today to diagnose cancer. While current cancer therapies are not quite as ancient, treatment for many cancers has not changed for up to 20 years.  This is shocking, given the enormous strides in technology that have occurred in the last two decades.  Most importantly, we need to change the paradigm of thinking of cancer as an organ-centric disease. Molecular abnormalities in cancer are not associated with the cancer’s organ of origin. Hence, we should treat cancers based on their molecular profile, not on where they originated in the body.

Now that the genomic era is upon us…

we can analyze the molecular signature of each cancer.  Clinical trials need to be redesigned to be mutation-centric, not drug-centric.  Multiple genetic markers should be employed to diagnose and classify cancers.

Generally, clinicians are entrenched in their way of thinking, which presents an obstacle to this kind of fundamental change.  To paraphrase Max Planck, science progresses one funeral at a time.  Regrettably, medicine also seems to progress this way.  Previous ways of thinking about cancer have become so ingrained that many are not even aware of their underlying assumptions.

The concept of classifying cancer by mutational profile will also impact cancer research.  How many times have you heard of a laboratory studying breast cancer, or prostate cancer, or liver cancer?  Several more times than you hear about a laboratory studying a particular mutation in a cancer biomarker like the epidermal growth factor receptor (EGFR), I’ll bet.

Further areas of inertia include applications for new drugs submitted to the Food and Drug Administration (FDA).  No application for an investigational new drug study (IND) has ever been filed based on a treatment targeted at a mutation in a cancer (of any kind), rather than treatment of a cancer in a specific organ. This situation persists despite the fact that the FDA has indicated it would be open to INDs using this approach.

Need a new paradigm for treating cancers.

Hope for new cancer treatments–turning in a new direction.

I hope the idea of classifying cancers by the mutations that drive them, not the organ in which they originate, changes how cancers are treated.  Dr. Kurzrock did an excellent job of articulating and advocating for these changes.  Employing old-school approaches to cancer is so engrained that we are often unaware of these underlying assumptions.  Rethinking cancer biology certainly has changed how I would respond to a loved one being diagnosed with cancer. I would seek out a forward-thinking doctor, willing to utilize this new paradigm from the onset, not waiting for last-ditch efforts once the cancer re-occurs.

Challenging the current methods for treatment, research, and drug development will not be easy, given with the institutional barriers that remain. Financial interests of the institutions involved will need to be realigned with this new paradigm.  Either that or we need AIDS-activist-like protests to spur on this change in thinking. In the end, as with AIDS, it may be patient advocacy groups that can best bring about this change in thinking in the medical, pharmaceutical, research, and regulatory communities.

The views expressed here are solely those of DeeAnn Visk are not necessarily those of Women in Bio, AWIS-SD, Janssen Labs, NPR, or your local NPR station. A special thanks to Nurith Amitai for her especially helpful editing.

This article was previously published in the January/February 2014 edition of the Association for Women in Science San Diego Chapter Newsletter.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net

Clinical Trials Improved by Leveraging Technology

On November 25, 2013, the San Diego Clinical Research Network held a meeting at the Sanford Consortium for Regenerative Medicine, with a reception at Bella Vista Cafe.  Three speakers talked about innovations in clinical trials.  J. Summer Rogers, Chief Executive Officer of nPruv, Inc., a company which acts like a “match.com” to match up patients and clinical trials, moderated the event.

The first speaker, Marcos Milla, Ph.D., Scientific Director and Fellow at Janssen, spoke from the pre-clinical research perspective about the search for drugs and patients by phenotypes.  New thinking about entire systems within a cell versus a specific target, allows complex cellular systems as a whole to be targeted.  Given the intricacies of problems with the immune system, this way of thinking will simplify a complex milieu.

Executing these experiments is the simple part.  A more difficult question is interpreting them.  One approach employs phenotypic read outs:  proliferation, migration, contact, differentiation, and activation.  These phenotypes can be read with automated systems, enabling high throughput screens.  Next, gross readouts of cell behaviors must be correlated with molecular readouts to permit determination of structural activity relationships.  To accomplish this, functional readouts need to be deconvoluted to concrete “hits”.  Harnessing knowledge of the human interactome will facilitate this goal.

human interactome

Clinical trials can target complex pathways in the human interactome.

An example of this workcan be found in the eicosanoid biosynthetic pathway.  High throughput and high-sensitivity liquid chromatography mass spectroscopy is utilized to acquire data from three different phenotypically-normal, healthy patients exposed to prostaglandin inhibitors.   All three displayed remarkably different profiles.   Differences in these profiles suggest different drugs would be most effective for each patient.

One method to optimize these interactions is to bring together the wide variety of “-omics” (genomics, metabolomics, proteomics, etc.) to build a drug profile for each individual patient.  This information could then be used to optimize individual treatments for specific patients.

The next speaker, Andreas Koester, M.D., Ph.D., VP Clinical Trial Innovation & External Alliances, Janssen, spoke about clinical trial innovations spawned by collaborations between large pharmaceutical companies, and a patient-centric approach to designing trials. As a leader in clinical trial operations, he offered a different perspective.

As a potential drug journeys through the research and development process, out of 10,000 compounds, 1 new drug will be approved by the FDA.  Presently this process costs about 2 billion dollars and takes 10 years.  How can we better spend our time and money?

word collage

A collage of words from Andreas Koester’s talk on improving clinical trials.

We need to change how we design clinical studies.  Patients should be first in mind in designing trials.  Collaboration between drug companies will streamline this process.  TransCelerate BioPharma, Inc., a non-profit organization established by leading pharmaceutical companies to advance innovation and tackle inefficiencies in R&D, is an example of this.  TransCelerate has developed guidelines for risk-based monitoring to reduce the cost of clinical trials, and established criteria for the qualifications and training of clinical research sites.

A Blue Button™ Initiative begun by the Veterans Administration to allow patients the opportunity to access and download their health records is being extended to clinical trials.  Pfizer is piloting the use of Blue Button™ technology to enable participants in Pfizer trials to download their own electronic clinical data collected in the trial.  Patients sign up after the study to get data results through a third party.  Normally  patients  receive no information about the results of a clinical trial in which they participate.  By allowing patients access to this information, patients are more engaged with the process.

Novartis is partnering with Walgreens to bring clinical trials to the patient.  Ninety percent of all Americans live within three miles of a Walgreens pharmacy.  No longer must patients interested in participating in clinical trials travel scores of miles to participate.  Novartis is currently doing a novel trial, allowing study participants to have their follow-up visits at Walgreens rather than hospitals, in an attempt to run the trial more efficiently and scale more widely.

Recently, the FDA allowed a trial for a investigational new drug (IND) with a clinical trial protocol developed using crowdsourcing.  The open innovation drug developer, Transparency Life Sciences, gained FDA clearance to proceed with a phase II trial of the antihypertensive drug lisinopril as adjunctive therapy in multiple sclerosis.  This groundbreaking, crowdsourced protocol also eliminated most study visits by using telemonitoring to assess outcomes.

The final speaker of the evening, Steven Steinhubl, M.D., Director of Digital Medicine at Scripps Clinic and Scripps Translational Science Institute, spoke about using mobile health technologies (mHealth) to conduct patient-centered clinical trials.  The change he advocates in clinical trials is to “move the mountain,” by bringing clinical trials to patients.  Presently healthcare is designed around the physician and not the patient.  Clinical trials are also designed around physician investigators.

The biggest driver of cost for clinical trials is Phase III testing.  Ninety percent of the cost is associated with this step.  Mobile health technologies can allow us to do studies more efficiently, and reduce costs.  However, there are cultural and regulatory barriers to implementing mobile health technologies into clinical trials.

translational medicine uses clinical trials to move ideas

Translational medicine employs clinical trials to move ideas from research to the bedside.

Another area needing change is the average lag time between a definitive clinical trial and changing the majority of clinical practice.  Currently it is 17 years.  Although 17 years is unacceptable, from a historical standpoint we are improving rather dramatically.  For example, it took 264 years for vitamin C use (via citrus fruits) on ships to prevent scurvy to become common practice after a definitive study.

During discussion, the panel agreed that the device and pharma industry need to be integrated from invention through clinical trials.  Perverse financial incentives for reimbursement on devices encourages the creation of a new device to accompany every new test.  This needs to be fixed.  Ironically, medicine is the only industry where more technology increases costs.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net

The human microbiome: a new approach to treating non-infectious diseases

The fault lies not in our genes, but in our microbiome

Conceptualizing humans as an organism, the microbes living within and on our bodies are often neglected.  A recent trend in academia has been the research into the wide variety of micro-organisms living within and upon humans.  Overlooked until recently, differences in the human microbiome are implicated in many disease states from auto-immune disorders to obesity.  Some day is may be possible to lose a few pounds just by consuming the right mix of bacteria to colonizes your gut!

plaque--bacteria in the mouth microbiome

Many different bacteria from the mouth microbiome

Given the advent of low-cost, high-throughput sequencing and the relatively smaller genomes of micro-organisms, a plethora of studies have been done comparing microbiomes of healthy and sick patients.  First academia must answer the chicken-or-the-egg-question:  do people have these diseases because of the combination of bacteria they have (or don’t have) or does having the condition lead to the combination of bacteria?  Does the microbiome of a sick patient arise from having a specific microbiome or does being sick lead to the presence of the specific microbiome?

To test this question, sickened laboratory animals have been inoculated with the microbiome of healthy animals.  Generally, the answers point to the idea that the right combination of microbes can alleviate the symptoms of a disease.  The list of non-infectious diseases (allergies, asthma, diabetes, and obesity) that have been effectively treated by reconstituting the microbiome in laboratory animals is growing. While academic research on this area is booming, what practical progress has been made on this front?

Compare the number of clinical trials using fecal transplants (46) to those using a cell therapy (29,268).  Clearly there is much room for growth in the practical application of the human biome to disease states.

Additionally, these initial clinical studies are looking only at the microbiome of the lower gut.  This leaves many areas of the human anatomy unstudied.  What about the skin, upper gastrointestinal tract, hair, eyes, nose and other mucus membranes?  While academia is well on the way to working on these issues, little has yet been seen in the way of practical application of this as evidenced by the lack of clinical trials.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net

Risk-based clinical trial monitoring

Increasing efficiency in clinical trials

While it sounds intimidating, risk based management is simply applying common sense in a systematic way.  Defining, evaluating, and managing risk is easily accomplished by using a documented approach to evaluate the risks.  Which needs closer monitoring:  a simple clinical trial in the United States at a reputable site previously used with much success or a complex trial in Zimbabwe at a location never utilized before?

Obviously, the trial with the greater unknowns is higher risk.

risk management for the FDA clinical trial

Evaluating risk to monitor clinical trials

Recently, the FDA came out with guidelines on risk-based management for clinical trials.  “The overarching goal of this guidance is to enhance human subject protection and the quality of clinical trial data by focusing sponsor oversight on the most important aspects of study conduct and reporting.”

What this means is merely commonsense in monitoring of clinical trials based on which ones have a higher risk of problems. 

 Another factor to consider beyond experience with a site and the complexity of the trial are the patient outcomes.  Will your trial involve life and death situations? 

Quantifying this can be done using a matrix of categories such as geographical location of the study, Good Clinical Practice compliance (GCP), and the relationship of the sponsor with the investigator.

 Understanding these concepts is crucial to increase efficiency and decrease costs of clinical trials.  As with any change in a regulatory environment, the industry is grappling with how to implement it. Pilot programs explore the implementation and thousands are waiting anxiously for “the answer”. The challenge is that the answer—as with everything within clinical research—is that it depends.

 Laurie Halloran’s presentation on this and other topics in clinical trials made them easy to grasp.  She presented at the San Diego Clinical Research Network meeting last week Tuesday at the Sheppard Mullin law firm.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net

My mother, the Chimera

My mother, the Chimera

During grad school, I was amazed to hear that the color of hair on your body is controlled by only one gene.  Hence, each person should only have one color of hair everywhere on their body.  I wanted to ask:  why does my mother have two colors of hair on her body (or as the slang goes, the carpeting does not match the drapes)?  But I did not, at that time, have her permission to discuss this phenomenon.  Now I have her approval.   I have always wondered what the doctor doing her annual exams thought:  hmmm, she seems to be a natural redhead, I wonder why she keeps dyeing her hair on top brown.

zygote

Human zygote at the 4 cell stage.

Later I stumbled across a paper discussing the ideas of  chimeras in humans.1   Here I first read how an individual can come to be made up of more than one type of DNA.  The classical view is that each person is made up of one individual type of DNA which should be as unique as their fingerprint.  Hypothetically, if two fertilized eggs (zygotes) fuse together while in the womb and then merged together completely, you get what appears to be a normal individual, but made up of two different DNA types.2  I estimate human chimeras are born at approximately 1 in 50 live births, the same rate as for twins.

 What is a chimera, anyway?

chimera pottery

An ancient Greek plate, showing the original legendary chimera: a lion with a bonus goat head

What image does the word chimera bring up?  A lion with a goat coming out of its back?  The term chimera originated with the Greeks, describing a monster.   Using chimera to describe a human with two different types of DNA in the same body does not imply they are monsters.  Tetragametic chimerism sounds like you have cancer–human chimera just makes you sound cool.

 

chimeric mouse

Chimeric mouse on right, with two solid colored mice on left. Note in addition to different coat coloring, the chimeric mouse also has different colored eyes.

 

 

In the last century, the term chimera has been used to describe individual engineered mice born from a zygote derived from more than one type of mouse.  Chimeric mice have two fur colors on different parts of their bodies.  This is because the DNA that controls coat color is different in different parts of the mouse.  So when people, who had not been manipulated as zygotes, began to be detected with different DNA in different parts of their bodies, the term human chimera was coined.

So how can you tell if you are a human chimera? 

chimeric dog

Two different colored eyes are well known to occur in dogs.

Tell-tale signs are two colors of hair on different parts of your body, two colors of skin on different places of your body, or two eyes each of a distinct color.  The phenomenon of two different colored eyes is called hererochromia iridum.  The definitive method to determine your status as a human-human chimera is to have tissue taken from several different areas of your body and tested to see if the DNA is all the same.  The expense and risk (anyone feel like having a piece of your liver removed?) generally is prohibitive, but given the rapidly lowering price of genetics testing, it may soon be within financial reach.

Or you may be completely unable to tell that parts of your body arose from two different zygotes.  You may only get the news if there is DNA testing of you and your children; or if you are trying to get an organ donation from relatives, to whom you are no longer a parent according to the DNA.  Yes, this really has happened.

Any twins in your family?

Jane Seymour

Given her two different colored eyes and twins running in her family, it is likely (I’ll give you 95% odds) that Jane Seymour is a human-human chimera.

Another way to determine the probability that you are a chimera is the prevalence of twins in your family.  My grandmother was the sibling of one set of twins and aunt to another.  When I brought up my mom’s chimerism at a family gathering, my aunt, wanted to know if she was a chimera.  Sure enough, her eyes are different shades of green/hazel.  So I would conclude that she is also a human-human chimera.

Let’s look at Jane Seymour.  She has two different color eyes, a sign of being a human chimera.  Her most recent children are twins.  Twins run in families.  So, as in my mom’s situation, it is likely that her mother had two eggs available for fertilization at the same time. The twin information along with her two different colored eyes leads to the conclusion that Jane Seymour is most likely a human-human chimera.

In closing…

Mike Scherzer professional baseball pitcher

Mike Scherzer, a professional baseball pitcher for the Detroit Tigers, clearly has one light blue and one brown eye.

All the examples given so far are women who are chimeras–what about men?  Questions of paternity are nothing new.  But what if a man was pretty sure he was the father, but the DNA tests said no?  There are certainly ways of testing to show that the father of a child in question is related to the uncle degree.  But what if the father has no brothers?  I leave other scientist and lawyers to explore these questions.

So now my Mom can think of herself as her own twin.  Or she can make jokes about how this explains why she has the energy of two people.  Or if she wants to stump her doctor, she can say that she suffers from tetragametic chimerism,

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1  “Embryogenesis of chimeras, twins and anterior midline asymmetries.”  CE Boklage.  Human Reproduction.  2006.

2  The following paper offers a different hypothesis to explain the formation of chimeras.  Read at your own risk. “Traces of embryogenesis are the same in monozygotic and dizygotic twins: not compatible with double ovulation.”  Human Reproduction.  2009.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net

Effective Science Writing – 10 tips


Written by me, DeeAnn Visk, this article was originally published by the Oxbridge Biotech Roundtable (OBR) Review in April 2013–the following is an excerpt from that article, based on a science writing talk sponsored by ORT given by Lynne Friedmann.

Effective Science Writing – 10 tips

1)  Use active voice

An active voice lends more simplicity, energy, and directness to prose (resume writing, anyone?). Scientists are encouraged to write in a passive voice making for clunkier, longer, and vague prose.

Examples:  Steve loves Amy (active voice)

Amy is loved by Steve (passive voice)

2)  Employ style guidesScience writing guides

Style guides shepherd writers through the nuts and bolts of writing, addressing questions such as what to capitalize, where commas should go, grammar questions, etc.  Individual journals may have their own style guides; be cognizant of the rules for the organization for which you are writing—even Wikipedia has a style guide.

Example: 12pm or 12am?  Using midnight or noon avoids confusion

Publications/blogs may or may not care; develop good habits now.  In the future, you will need to keep an editor happy; they do not want to look dumb.  Editors comparing two equivalent papers choose the one with the least editing required.

3)  Overcome “writer’s block”

Treat your writing time like an appointment until it becomes a habit. For those of you with difficulty starting, just begin. Fire your internal editor, ignore grammar, spelling, and punctuation—just get the ideas down on paper.  Stuck on the next word?  Just write “XXXXX”.  Keep the flow going.  Write down your first draft as fast as possible.

4)  Focus on the goal

Reduce why you are writing something to one sentence:  I want my manager to approve my budget.  Write it on a piece of paper and hang it where you can see it.  Refer to it while writing.  Information without context is useless—do ideas support my goal?

5)  Make writing transparent

As Mark Twain said “never use a $5 word when a 50 cent one will do.”  Deliver information that can entertain people, the story behind the research, interject patient stories, trying to solve puzzles, and mysteries.  Work in something about the process of science, one piece of information in a continuum.  Be clear: do not overload opening sentence; go from general to specific.  You want the reader to hold your hand and never let go.  Allow readers to see and feel the experience by using descriptive and specific sensory language.science writing

6)  Do not use science clichés

Describe so that writer can see how it is a break through.  As Friedmann stated tongue-in cheek, “The ‘missing link’ has been found so many times, how could any possibly still be lost?”  Other worn clichés include:  shedding light, the holy grail, the silver bullet, and paradigms shifting.  Don’t these just make your eyes glaze over? Or do you find yourself grinding your teeth in irritation instead?

7)  Write, revise, and edit in sequence

Compose your copy well ahead of the deadline.  Don’t look at it for a day or two, then come back and eliminate the first paragraph or two.  Test your copy during revision.  Print it out—difficult to proof on-screen.  Go to a different physical space; get up walk around, read it aloud.  Are you bored? Confused? After each sentence, ask yourself “so what”?  Get rid of sentences that begin with “Th” words:  the, this, they.  Each time you read a sentence remove one word, and see if the sentence still conveys the meaning. You are on the right track when “sentences shrivel like bacon in a pan”.  Proof read copy backwards to find typos.

8)  Professional organizations as valuable resources

Professional organizations offer seminars and job leads.  A good resource is the National Association of Science Writers.  Environmental journalists normally find themselves evolving into activist (not just merely reporters), issuing calls to action. If you are thinking about becoming one, look at the Society of Environmental Journalist. The American Medical Writers Association holds great conferences and workshops.  Check out their websites for hints on the craft of writing.

science writing association

9)  Where to find science writing opportunities

Consider writing for various organizations such as your school’s alumni magazine, Roundtable Review (a blog hosted by ORT), MIT Technology review.  Both academic and industry grants require excellent writing—volunteer to help.  Many websites need content/blog writers; begin by offering to write for free.

10)  Receiving feedback on your writing

Keep your inner defensive monster in the cage.  Take a deep breath and relax.  You must respond well to correction, if you want people to continue giving it to you. Feedback is a gift, assisting you to improve your writing. Thank whoever is taking time to give you feedback; try incorporating their suggestions into your writing.

DeeAnn Visk, Ph.D., is a freelance science writer, editor, and blogger. Her passions include cell culture, molecular biology, genetics, and microscopy. DeeAnn lives in the San Diego, California area with her husband, two kids, and two spoiled hens. You are welcome to contact her at deeann.v@cox.net