The Proteomic Bubble Wrap Suit

The Proteomic Bubble Wrap Suit

Face it. Despite our best intentions, bad stuff happens on occasion, as seen in the medical field. In hopes of a positive outcome, a patient undergoes treatment, but has a negative reaction. In the pursuit of “first do no harm,” more safeguards are put into place to minimize the chances of a negative outcome. As technology improves, however, we may soon have an equivalent to the bubble wrap suit, particularly in the development of new medical treatments.

The Food and Drug Administration (FDA) – the federal gatekeeper for new drugs – has established numerous criteria that drug candidates must meet before being sold in the U.S. marketplace (FDA, 2017a). After testing the drug candidate in animals, the clinical evaluation begins. The first phase involves looking at how the drug candidate is processed in a few healthy people and figuring out common side effects. If things look good and the drug is considered to be not too toxic, the investigation focuses on both the safety and the effectiveness of the drug candidate for treating the disease/condition in a large number of people. If all goes well with the testing and review, the FDA decides whether to approve the drug. Further monitoring of drug safety still happens after the approval, but success depends on medical professionals and insurance companies (FDA, 2017b; FDA, 2018).

Who foots the bill for all the testing done during the clinical phases? Well, usually the company or other parties who wishes to have the drug approved. You can imagine that this process is not cheap. It is the worst nightmare imaginable when something goes horribly wrong, particularly in later stages. Despite all the safety precautions taken, this nightmare becomes reality more often than anyone would like to see.

The unfathomable sadly materialized in the clinical testing of Pfizer’s drug candidate torcetrapib, designed to treat high cholesterol (Berenson, 2006). The safety barriers put in place failed. The initial biomarkers selected to monitor the drug recipients did not work to alert doctors that something was about to go horrifically wrong. Pfizer lost about a billion dollars in the development of the drug, and sons and daughters lost their lives (Williams et al., 2018).

In a retrospective study, researchers applied a new proteomic technology (SOMAscan platform) to blood samples collected from participants of the failed study (Williams et al., 2018). The data from this proteomic investigation illuminated unknown deep physiological effects of the experimental drug that were also quite pervasive, and which probably would not have been picked up by technologies available at the time the clinical trial was conducted. The effects were especially prevalent in the bodily functions of immunity and inflammation. The insights provided by the SOMAscan proteomic analysis offered probable explanations for the deaths attributed to taking the experimental drug.

Although the SOMAscan technology was not available at that time, the odds are very good that the problems with torcetrapib would have surfaced early enough to make a difference. It is important to note that during the clinical trials, clinicians used instead the best available measurement, the Framingham risk score (a score to assess the likelihood of having heart problems), to monitor the patients, and observed a decreased risk of heart problems for the experimental drug users (Williams et al., 2018). In the retrospective SOMAscan study, the proteomic data showed the opposite result; the experimental drug users were actually at an elevated risk (Williams et al., 2018). This is not the first-time proteomics beat the Framingham risk score, a gold standard for assessing cardiovascular event risks. In an earlier and separate retrospective study, the proteomic assessment using the SOMAscan platform outperformed the Framingham risk score in determining the patients most likely to suffer a heart attack (Ganz et al., 2016).

While it is too late to help those who suffered from the unexpected effects of torcetrapib, we now have an opportunity to spare others from unintended harm. Applying the proteomic bubble wrap during clinical trials may indeed prevent unnecessary deaths. Also, the SOMAscan platform may better identify patients who would benefit the most from the experimental drug or who should avoid it all costs. Already, we know that the inclusion of biomarkers in the stratification of patients to receive experimental treatment can improve the success rate for FDA approval (Wong, Siah, & Lo, 2018). However, we need to use every tool at our disposal to monitor the right things at the right time, to avoid the kind of outcomes seen with the torcetrapib trial.



Berenson, A. (2006, December 4). End of Drug Trial Is a Big Loss for Pfizer. The New York Times. Retrieved from

Food and Drug Administration. (2017a, November 24). The FDA’s Drug Review Process: Ensuring Drugs Are Safe and Effective. Retrieved on March 20, 2018 at

Food and Drug Administration. (2017b, November 17). FDA’s Sentinel Initiative – Background. Retreived on March 20, 2018 at

Food and Drug Administration. (2018, February 21). Questions and Answers on FDA’s Adverse Event Reporting System (FAERS). Retrieved on March 20, 2018 at

Ganz, P., Heidecker, B., Hveem, K., Jonasson, C., Kato, S., Segal, M. R., . . . Williams, S. A. (2016). Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease. JAMA, 315(23), 2532-2541. doi:10.1001/jama.2016.5951

Williams, S. A., Murthy, A. C., DeLisle, R. K., Hyde, C., Malarstig, A., Ostroff, R., . . . Ganz, P. (2018). Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib. Circulation, 137(10), 999-1010. doi:10.1161/CIRCULATIONAHA.117.028213

Wong, C. H., Siah, K. W., & Lo, A. W. (2018). Estimation of clinical trial success rates and related parameters. Biostatistics. doi:10.1093/biostatistics/kxx069


Melody Harris, J.D., appointed Chief Legal Officer of SomaLogic

April 2, 2018 – Boulder, CO – SomaLogic announced today that Melody Harris has joined SomaLogic as the company’s Chief Legal Officer. Ms. Harris comes to SomaLogic from Qualcomm Life, a digital health subsidiary of Qualcomm, where she led the legal, global privacy, and Quality, Regulatory & Compliance groups as Vice President & Chief Counsel.

“I am delighted that Melody has chosen to take on this central role at SomaLogic at this critical time of company growth,” said Al Reynolds, Chief Executive Officer of SomaLogic. “She brings with
her a wealth of experience in healthcare technology and data-centric business models that we need to help us accelerate the delivery of SomaLogic’s breakthrough precision health insights into multiple markets around the world.”

SomaLogic was founded to transform healthcare by accurately measuring the changing state of an individual’s health over time, as revealed by changes in the proteins that make up the human body. Regularly monitoring thousands of proteins, unlike genome sequencing, can reveal not only real-time health status but also what interventions (e.g., diet, prescription and/or lifestyle changes) could maximize that status.

“SomaLogic is bringing together a unique technology and business plan to entirely change how people world-wide manage their personal health,” said Ms. Harris. “This rare opportunity to make a real difference in people’s lives is exciting, and I am eager to join the SomaLogic team to help make that vision a reality.”

Ms. Harris joined Qualcomm Life with the acquisition of HealthyCircles, where she served as General Counsel. At HealthyCircles, Ms. Harris built the company’s legal and compliance functions and advised on early-stage product development related to data and privacy by design. Prior to HealthyCircles, Ms. Harris held a variety of senior leadership roles, including President & General Counsel of an international IP management firm, Executive Vice President and General Counsel of an international software development and consulting firm, and Senior IP counsel to U S WEST/Qwest. She received her J.D., cum laude, from the Harvard Law School and her B.A., cum laude, in political science from the University of Denver.


SomaLogic Contact
Laura S. Mizoue, Ph.D.
Communications Specialist
T: 720-417-7509

About SomaLogic
SomaLogic delivers health management insights in real-time that empower individuals to take action to improve their personal health and wellness. These essential insights, provided through a global network of partners and users, are derived from precise, proprietary, and personalized measurement of critical changes in an individual’s protein makeup throughout life. For more information, visit


SomaLogic launches new version of SOMAscan® assay

Expanded SOMAscan content measures approximately 5000 proteins simultaneously in a small blood sample

SomaLogic has launched a new version of their proprietary SOMAscan® assay. This new version measures approximately 5,000 unique human protein analytes, almost four times more than its predecessor. The optimized assay format also uses new robotic instrumentation, removing as many manual interventions as possible.

Unlike genes which remain largely the same throughout an individual’s lifetime, the proteins in the body are constantly changing in response to both internal and external factors, such as pathogens, diet, exercise and medications. The SOMAscan assay is the only technology capable of measuring thousands of proteins simultaneously, over a wide concentration range in a small sample of blood, which is critical for delivering personalized health information in real time.

The new version of the SOMAscan assay will be run in SomaLogic’s CLIA-certified laboratory, with a capacity of approximately 2,000 samples per week. On April 2, SomaLogic will start running samples from various studies on the new platform, to begin building precision health insights around metabolic and cardiovascular disease risk.

Proteomics Providing Alternatives to X-rays

Proteomics Providing Alternatives to X-rays

It is simple. It is non-invasive. Yet, it is not without risk. I am referring to imaging technologies, such as X-rays and computed tomography (CT) scans, that expose bodies to radiation to “see” under the skin.

What’s the risk with radiation? Well, the radiation can alter/damage DNA. Unfortunately, damaged DNA does not lead to one developing super powers despite what the comics might say. But damaged DNA can lead to cancer (ACS, 2015). And the risk only increases with repeated rounds of radiation exposure.

It’s true that the amount of radiation exposure from a simple X-ray of an extremity (e.g., an arm) is equivalent to about 3 hours of environmental radiation exposure for the typical adult (Radiological Society of North America, 2018). However, if you are subjected to many X-rays or other imaging procedures that use way more radiation over the course of your lifetime, the added radiation exposure quickly adds up. As you might expect, this extra exposure increases your cancer risk but not your Spidey senses.

What can be done to mitigate the risk? Cutting down on the number of X-rays would help. One superhero may swoop in to do just that: Researchers are pioneering the use of a simple blood sample to figure out if bones are healing.

Current monitoring of broken bones uses highly variable metrics and lacks universal standards. Researchers from Boston University set out to determine if a standardized lab test built on blood analysis could take the place of all these other approaches (Hussein et al., 2017). Using a mouse model, the researchers collected many samples and searched for different types of biomarkers. They noted that hundreds of proteins changed dramatically during the course of the bone-healing process. Optimistically, they noted that protein measurement-based blood tests may prove especially promising in monitoring human bone repair.

In a serendipitous and almost concurrent moment, an international group of researchers led by scientists from the Shriners Hospitals for Children and the Oregon Health and Science University in Portland happened upon related findings (Coghlan et al., 2017). These researchers set out to bring order to the field of monitoring how quickly children grow, which currently yields variable results, particularly in very young children. In their search, the researchers identified that the circulating levels of the protein “noncollagenous 1 domain of type X collagen” (CXM) tracked well with growth rate (specifically, the rate of bone growth). For young patients suffering from growth disorders, having a more precise way of monitoring growth rates proves crucial to gauge appropriate response to medical treatment. As for the moment of serendipity, the researchers also noted that the levels of CXM rise during the healing of broken bones.

We will likely never be able to eliminate imaging based on X-rays: It is just too useful. We may, however, be able to reduce our need for them with improved diagnostic technologies for particular uses, like monitoring bone healing. Not only will new approaches like blood analysis inevitably reduce the amount of radiation exposure, but it could be easier on the pocket book too: Just think of how many superhero comic books could be purchased for the cost of a CT scan or a standard X-ray!



American Cancer Society (ACS) medical and editorial content team. (2015, February 24). Do x-rays and gamma rays cause cancer? Retrieved from

Coghlan, R. F., Oberdorf, J. A., Sienko, S., Aiona, M. D., Boston, B. A., Connelly, K. J., . . . Horton, W. A. (2017). A degradation fragment of type X collagen is a real-time marker for bone growth velocity. Sci Transl Med, 9(419). doi:10.1126/scitranslmed.aan4669

Hussein, A. I., Mancini, C., Lybrand, K. E., Cooke, M. E., Matheny, H. E., Hogue, B. L., . . . Gerstenfeld, L. C. (2017). Serum proteomic assessment of the progression of fracture healing. J Orthop Res. doi:10.1002/jor.23754

Radiological Society of North America, Inc. (accessed February 8, 2018) Radiation Dose in X-Ray and CT Exams. Retrieved from


Using Proteomics to Defend Tiny Warriors

Using Proteomics to Defend Tiny Warriors

Tiny toes. Tiny fingers. Tiny diapers. The word “tiny” almost perfectly describes infants born very prematurely. Yet, it fails to properly describe the battle for survival these tiny warriors endure. And the more premature the baby, the harder the fight. Can recent advances in medicine help boost the odds in the warriors’ favor?

Upon entering the world, preemies struggle to breathe with underdeveloped lungs. Medical intervention in the form of oxygen therapy or mechanical ventilation can help, but many babies receiving such treatments often develop bronchopulmonary dysplasia (BPD) (Baker, Abman, & Mourani, 2014). This disease is characterized by problems with the development of the veins and arteries that feed into and out of lungs and air sacs. Not too surprisingly, BPD can give rise to more conditions, such as pulmonary vascular disease (PVD) or pulmonary hypertension, which in turn significantly increase infant mortality. Diagnosing these conditions can be difficult, but a better understanding of their molecular underpinnings may help identify the tiny warriors at greatest risk early enough to intervene successfully.

Researchers are answering the call to battle. Using an arsenal of scientific methodologies (including the proteomic analysis of blood samples from premature infants), one group found that current medical interventions can cause a decrease in levels of a critical protein called “platelet-derived growth factor receptor a” (PDGF-Ra) (Oak et al., 2017). Decreasing the amount of PDGF-Ra experimentally in animal models leads to the manifestation of traits similar to those seen in BPD-afflicted infants. The same researchers also found that adding back PDGF-Ra could rescue the observed consequences of the simulated medical intervention, suggesting a new way to attack the diseases that arise from standard treatments.

In another answer to the call-of-action, a different group used proteomics to better understand how PVD arises (Wagner et al., 2018). In the results, it was not too surprising to see proteins associated with the PDGF signalling network on the list of potential biomarkers. Surprisingly, some of the other biomarker candidates suggest new signaling pathways may be involved in the onset of PVD. Although exciting, future work is needed not only to confirm, but also expand upon these early suggestive findings.

With each answer to the call to battle, we are moving ever closer to improving the odds for the tiny warriors. The day may soon come when these tiny ones no longer struggle for breath or suffer the unintended consequences of the medical community’s life-saving interventions. When it does come, it will truly be a happy victory.



Baker, C. D., Abman, S. H., & Mourani, P. M. (2014). Pulmonary Hypertension in Preterm Infants with Bronchopulmonary Dysplasia. Pediatr Allergy Immunol Pulmonol, 27(1), 8-16. doi:10.1089/ped.2013.0323

Oak, P., Pritzke, T., Thiel, I., Koschlig, M., Mous, D. S., Windhorst, A., . . . Hilgendorff, A. (2017). Attenuated PDGF signaling drives alveolar and microvascular defects in neonatal chronic lung disease. EMBO Mol Med, 9(11), 1504-1520. doi:10.15252/emmm.201607308

Wagner, B. D., Babinec, A. E., Carpenter, C., Gonzalez, S., O’Brien, G., Rollock, K., . . . Abman, S. H. (2018). Proteomic Profiles Associated with Early Echocardiogram Evidence of Pulmonary Vascular Disease in Preterm Infants. Am J Respir Crit Care Med, 197(3), 394-397. doi:10.1164/rccm.201703-0654LE


Precision Medicine, Space Vomit, and Meaning

Precision Medicine, Space Vomit, and Meaning

“Space vomit” is a truly scientific idiom. At least, it was in the lab. We used this queasy term to describe rendered 3D images of nucleic acids that resembled more the product of an astronaut’s upset stomach than the structure of a molecule. The data were just too noisy and, ultimately, useless for extracting any meaningful insight.

Worse, even when we knew that we had space vomit on our hands, we were still tempted to try and make sense of it. Maybe, one more tweak to the algorithm or input file would suddenly transform the mess into something meaningful? Having given into the temptation too many times, I know first-hand that this kind of salvage moment VERY RARELY happens. And, I think, this is a lesson that many precision medicine disciples could benefit from learning as well.

Okay, what does space vomit have to do with precision medicine? Precision medicine typically conjures the image of using genetic testing to indicate the best medical treatment or lifestyle choices for people (Marcon, Bieber, & Caulfield, 2018). But we have to be honest: in the majority of cases, deducing a medical or lifestyle choice from a genome sequence is akin to trying to make spatial sense of space vomit: It is just too messy.

Indeed, our genomes are incredibly noisy and contain too much “stuff” for us to effectively make sense of it, at least at the moment. Only ~1% of our DNA codes for proteins (the molecules responsible for almost every function in our bodies) (Zhao, 2012). The rest holds not only the instructions for building the protein, but also the instructions for when to use the protein and the instructions for controlling the protein’s activity. In addition to carrying relevant information, the genome can also include DNA from random sources, such as viruses, transposons, bacteria, etc.  (Crisp, Boschetti, Perry, Tunnacliffe, & Micklem, 2015; Soucy, Huang, & Gogarten, 2015). And these are just a few of the numerous complicated variations that our genomes carry.

The noise/complexity problem only gets worse beyond the sequence itself. A person’s DNA gets replicated over and over during the course of a lifetime, and the machinery responsible for this task occasionally makes mistakes (Harris & Nielsen, 2014), which may get passed to the next generation. Some of these mistakes, or mutations, may be expected to give rise to some horrible disease, but even having a “bad” mutation is not a guarantee that the bearer will show clinical symptoms of the disease (Chen et al., 2016)!

Despite the uncertainty, many researchers (and even a growing number of companies) are deeply invested in linking genomic mistakes to various traits and medical problems. But trying to associate complex traits to changes in the genetic code is difficult at best. Recently, a call-to-action has been raised for changing how this is being done (Boyle, Li, & Pritchard, 2017).

Aside from trying to extract insights from the genome, another problem exists: the actual readout of the genetic material. Different entities, such as business and research institutions, usually have different protocols for generating data and algorithms for figuring out the DNA sequence from the data. Now, it may seem that no matter what, the same sequence should be generated. Right? Recently, a JAMA Oncology article described yet another instance of discrepancies when it comes to DNA sequencing (Torga & Pienta, 2017). In this article, researchers sent samples from the same set of patients to two different companies with Clinical Laboratory Improvement Amendments (CLIA) certified labs (i.e., a way of vetting companies that sell diagnostic tests) and got back different sequences for the majority of the patients. So which company provided the “correct” DNA sequence? This is a great question; especially when the choice of medical care made by providers presumably hinges on having a “correct” sequence.

And this brings us back to space vomit: There are instances when knowing the correct DNA sequence can be beneficial in the treatment of cancer, such as melanoma and some types of lung cancer (Harris, 2018). But these occurrences may be the exception rather than the rule, though they might be what cause people to give into the temptation of continuing to hammer away at noisy, complex, and potentially incorrect data to find the magical answer for medical treatments or lifestyle choices. It is reassuring to know that awareness is growing about the limitations of the DNA sequence for determining better medical intervention (Harris, 2018). Perhaps the precision medicine field will now turn their attention to other, less space vomit-like data types that may more readily and easily lead to better medical or lifestyle choices.


Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017). An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell, 169(7), 1177-1186. doi:10.1016/j.cell.2017.05.038

Chen, R., Shi, L., Hakenberg, J., Naughton, B., Sklar, P., Zhang, J., . . . Friend, S. H. (2016). Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases. Nat Biotechnol, 34(5), 531-538. doi:10.1038/nbt.3514

Crisp, A., Boschetti, C., Perry, M., Tunnacliffe, A., & Micklem, G. (2015). Expression of multiple horizontally acquired genes is a hallmark of both vertebrate and invertebrate genomes. Genome Biol, 16, 50. doi:10.1186/s13059-015-0607-3

Harris, K., & Nielsen, R. (2014). Error-prone polymerase activity causes multinucleotide mutations in humans. Genome Res, 24(9), 1445-1454. doi:10.1101/gr.170696.113

Harris, R. (2018, January 15). For Now, Sequencing Cancer Tumors Holds More Promise Than Proof. NPR. Retrieved from

Marcon, A. R., Bieber, M., & Caulfield, T. (2018). Representing a “revolution”: how the popular press has portrayed personalized medicine. Genet Med. doi:10.1038/gim.2017.217

Soucy, S. M., Huang, J., & Gogarten, J. P. (2015). Horizontal gene transfer: building the web of life. Nat Rev Genet, 16(8), 472-482. doi:10.1038/nrg3962

Torga, G., & Pienta, K. J. (2017). Patient-Paired Sample Congruence Between 2 Commercial Liquid Biopsy Tests. JAMA Oncol. doi:10.1001/jamaoncol.2017.4027

Zhao, R. (2012, November 8). ENCODE: Deciphering Function in the Human Genome. Retrieved from


SomaLogic teams with Leeds Centre for Personalised Medicine and Health to deliver SOMAscan® platform in clinical healthcare

Personalized health insights derived from SomaLogic’s proprietary protein measurement technology will be tested in clinical healthcare settings in the UK

February 6, 2018 – Boulder, CO – SomaLogic announced today the establishment of a framework “Partnership for Personalized Health” with the Leeds Centre for Personalised Medicine and Health (CPMH), to be based in Leeds, UK. This collaboration – the first of its kind – aims to help individuals and professionals enhance health decisions by providing:

  • accurate assessment of the current state and future disease risks;
  • deeper understanding of causal and actionable factors that may drive these risks;
  • reliable monitoring of individuals to understand the effectiveness of interventions.

These activities will rely on personalized insights gained from SomaLogic’s unique ability to easily measure thousands of protein changes associated with a wide variety of diseases and conditions.

Leeds CPMH is a collaboration based at the University of Leeds involving general practitioners, the National Health Service, academics and the city council. By working closely with SomaLogic within this unique partnership, Leeds patients will also gain preferential access to additional health management insights provided exclusively through SomaLogic’s SOMAscan® protein-measurement platform.

“We are excited to be working with SomaLogic, a global leader in personalised medicine,” said Dr. Mike Messenger, head of the Leeds CPMH. “This partnership has the potential to deliver huge benefits for the people of Leeds, in terms of better health outcomes and more efficient use of health and care resources.”

Initially, the two organizations will develop a “test bed”multiple clinical areas, in both primary and secondary settings throughout the greater Leeds region. The Leeds CPMH and its strong network of healthcare providers and health leaders will provide the infrastructure and expertise to use insights derived from SomaLogic’s innovative technology to enhance clinical decision making and influence positive patient behavior change. Ultimately, the partners hope to dramatically lower the cost and increase the quality of personalized health screening and care delivery in Leeds and beyond.

“Leeds CPMH is at the forefront of integrating academia, industry, healthcare providers, and individual citizens to go beyond the ‘one size fits all’ approach to healthcare,” said Steve Williams, SomaLogic’s Chief Medical Officer. “We are thrilled that Leeds CPMH is the first of what we trust will be many test-bed partners around the world.”

For further details, please see the Leeds CPMH news article.


SomaLogic Contact
Laura S. Mizoue, Ph.D.
Communications Specialist
T: 720-417-7509

About SomaLogic
SomaLogic delivers meaningful and actionable health-management insights that empower individuals worldwide to continuously optimize their personal health and wellness throughout their lives.

These essential insights, which are provided through a global network of partners and users, are derived from precise, proprietary, and personalized measurement of critical changes in an individual’s proteins over time. For more information, visit


Understanding How Our Greatest Ally Can Also Be Our Greatest Foe

Understanding How Our Greatest Ally Can Also Be Our Greatest Foe

Achoo…sniffle sniffle…cough…hack…These sounds echoing throughout the office herald the arrival of yet another cold/flu season. Yay! But before you convince yourself to work from behind the barricades of your home, remember that we do have a wonderful defense: our immune system. When it works properly, everything is right with the world. However, it can also go very wrong.

The scientific literature is peppered with examples of how our immune system defender can turn on us, such as in the case of rheumatoid arthritis. In your joints, the synovium provides critical lubrication, akin to the oil needed to keep the engine parts running smoothly in cars (Mayo Clinic, 2017a). In rheumatoid arthritis, the immune system starts attacking this tissue, causing unnecessary inflammation where it does not belong. Without treatment, the inflammation persists, the pain worsens and the joints become disfigured and even inoperable.

New research is highlighting many additional, even surprising instances in which our immune system ally can seem to turn on us. Trisomy 21, the inclusion of an additional chromosome 21, leads to Down Syndrome (DS) and its wide spectrum of complications (Mayo Clinic, 2017b). To understand how an extra chromosome can lead to such a diverse set of complications, researchers measured changes in blood proteins to try to understand what is happening at a deeper level. From their findings, they learned that the extra 21st chromosome can lead to “profound” protein changes in the immune system (Sullivan et al., 2017). Interestingly, they saw dramatic increases in DS individuals of the inflammatory TNF-a signaling pathway (a target for some rheumatoid arthritis medications) (Rau, 2002; Sullivan et al., 2017), in addition to many other immune system-related proteins. More work is needed to pinpoint how these protein changes can affect various DS complications. However, it is tantalizing to think that medications aimed at treating rheumatoid arthritis may also potentially benefit DS individuals in some way.

Another surprising instance of our friend the immune system causing chaos may be premature labor. Researchers noted that a mother-to-be’s immune system changes during pregnancy to allow the fetus to grow without being attacked (Aghaeepour et al., 2017). When they investigated blood samples from pregnant women, they mapped out a clear-cut timeline of changes to the immune system. If the strict schedule is not followed, the researchers hypothesize it could be the prelude to premature labor. If this hypothesis plays out, it could yield beneficial diagnostics that could warn doctors and the mom-to-be ahead of time and result in an increase in happier birth stories.

It really does seem that a legitimate way to describe our immune system is to call it our greatest frenemy. (Hopefully, this does not bring back any painful middle school memories.) With continuing advances in diagnostics and therapeutics, we might be able to determine when the relationship turns adversarial, and take the necessary steps to mend that break. Hopefully, the friendship is mended before we need our ally the most. Goodness…I just heard another cough!



Aghaeepour, N., Ganio, E. A., McIlwain, D., Tsai, A. S., Tingle, M., Van Gassen, S., . . . Gaudilliere, B. (2017). An immune clock of human pregnancy. Sci Immunol, 2(15). doi:10.1126/sciimmunol.aan2946

Mayo Clinic. (2017a). Rheumatoid arthritis – Symptoms and causes. Retrieved on December 8, 2017 at

Mayo Clinic. (2017b). Down syndrome – Symptoms and causes. Retrieved on December 8, 2017 at

Rau, R. (2002). Adalimumab (a fully human anti-tumour necrosis factor alpha monoclonal antibody) in the treatment of active rheumatoid arthritis: the initial results of five trials. Ann Rheum Dis, 61 Suppl 2, ii70-73.

Sullivan, K. D., Evans, D., Pandey, A., Hraha, T. H., Smith, K. P., Markham, N., . . . Blumenthal, T. (2017). Trisomy 21 causes changes in the circulating proteome indicative of chronic autoinflammation. Sci Rep, 7(1), 14818. doi:10.1038/s41598-017-13858-3


Precision Medicine and Rube Goldberg

Precision Medicine and Rube Goldberg

The American cartoonist and inventor Rube Goldberg was best known for his series of cartoons featuring absurdly intricate contraptions designed to perform mundane tasks. The humor comes from the apparent simplicity of the task: Why not just take the egg into one’s own hands and crack it open? However, Rube Goldberg was onto something: We humans are living Rube Goldberg machines. That simple act of cracking open an egg requires an inordinately complex sequence of events to occur within our bodies.

We know that such a simple act requires exquisite coordination between body and brain. However, this interaction is just the surface. If we probe deeper (to the molecular level), we can see an orchestra of DNA, RNA, and proteins working in harmony to carry out the egg-breaking. When everything works in a harmonious balance, we are fine. When discord arises, disease often results. By probing the different players of the molecular biology trilogy, unique understandings about the disease can be gleaned and harnessed for the implementation of precision medicine.

Yet, we must be cautious about which molecules we monitor for precision medicine because the realization of our own inherent complexity holds especially true in the doctor’s office. Take cancer treatment as an example. Not only are cancer genomes highly variable (Tomasetti, Vogelstein, & Parmigiani, 2013; Vogelstein et al., 2013), but cancers can be affected by numerous molecular pathways (Loeb & Loeb, 2000). As a result, successful treatments for one type of cancer do not always work efficiently for other cancers — or even other tumors of the same type of cancer!! — even though they share the same mutations (Kobayashi & Mitsudomi, 2016; Kopetz et al., 2010; Prahallad et al., 2012).

To develop medicines with greater precision, we certainly should tap into the data geyser born from the omics revolution. Before tapping in, however, we need to determine just what information we really need and how to put it together. This knowledge makes the path clearer for harnessing the wealth of data to make the vision of precision medicine a reality.

Historically, research fixated on specific pathways or individual proteins, but this approach has nearly maxed out the potential benefits regarding our understanding or providing new treatments for cancer (Sapiezynski, Taratula, Rodriguez-Rodriguez, & Minko, 2016). For the next generation of medicines/treatments, we will need to look at how numerous pathways influence one another and how they may differ among individuals. Already, this realization has birthed yet another omics, known as interactomics.

What in the world is interactomics? In essence, it’s about looking at how all the proteins interact with one another and how the interactions change in real-time in response to cues from the environment, etc. (Fessenden, 2017). It’s akin to playing the “Six Degrees of Kevin Bacon” game, but with proteins. For many researchers, interactomics could be a powerful tool for precisely understanding how a faulty protein can cause problems in other molecular pathways, which can give rise to diseases (Fessenden, 2017).

Looking at the protein version of the Kevin Bacon game is another reminder of our biological Rube Goldberg machines’ complexity. It is also a wonderful step to a deeper and sounder understanding of the body’s mechanical workings, which could be a boon for precision medicine. To properly tackle the ginormous challenge of generating a sounder understanding, however, will take a massively coordinated effort of the pharmaceutical industry, research community, and medical community.



Fessenden, M. (2017). Protein maps chart the causes of disease. Nature, 549(7671), 293-295. doi:10.1038/549293a

Kobayashi, Y., & Mitsudomi, T. (2016). Not all epidermal growth factor receptor mutations in lung cancer are created equal: Perspectives for individualized treatment strategy. Cancer Sci, 107(9), 1179-1186. doi:10.1111/cas.12996

Kopetz, S., Desai, J., Chan, E., Hecht, J. R., O’Dwyer, P. J., Lee, R. J., . . . Saltz, L. (2010). PLX4032 in metastatic colorectal cancer patients with mutant BRAF tumors. Journal of Clinical Oncology, 28(15_suppl), 3534-3534. doi:10.1200/jco.2010.28.15_suppl.3534

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SomaLogic closes $200M financing round

Nan Fung Life Sciences and Madryn Asset Management join iCarbonX in investing to accelerate SomaLogic’s unique precision health insights delivery business

January 3, 2018 – Boulder, CO – SomaLogic announced today that it has capped its $200 million funding round, anchored by iCarbonX with substantial investments from Nan Fung Life Sciences and Madryn Asset Management. The successful round will accelerate SomaLogic’s goal of becoming the world’s leading provider of precision digital health insights.

SomaLogic uniquely and precisely measures thousands of human proteins rather than genes, and turns those measurements into insights that empower people to purposefully and meaningfully manage their individual health and wellness. SomaLogic’s “SOMAscan®” technology, which currently measures 5,000 proteins in a single sample, has successfully analyzed over 150,000 samples across more than 50 diseases or conditions, with plans for an additional 1 million more samples by the end of 2020. The continuously growing power of the SOMAscan technology, the massive proprietary data sets being accumulated and analyzed, and the strategy for turning those assets into a successful health insight company have together caught the attention of leading investors in emerging digital health markets.

“We are delighted to expand our relationship with SomaLogic and continue to support the company’s growth,” said Avinash Amin, Managing Partner at Madryn Asset Management. “We believe SomaLogic’s proteomics technology provides the basis for unique and differentiated insights into human health and disease, with broad implications for diagnosis and treatment.”

Understanding the changes over time in bodily proteins is being increasingly recognized by the medical community as essential to the effective personalized maintenance of health and management of disease. Unlike genes, proteins respond dynamically to changes in the body and the environment, offering meaningful and actionable health information in real-time.

“These new investments by Nan Fung and Madryn, two elite, global healthcare investors, are yet another huge vote of confidence in our strategic direction and the deep intrinsic value of our technology,” said Al Reynolds, SomaLogic’s CEO. “We are delighted that they recognize the huge potential of our technology to radically transform healthcare, and are joining us as valued partners to accelerate that goal.”

Specific financial details were not disclosed.

SomaLogic Contact
Laura S. Mizoue, Ph.D.
Communications Specialist
T: 720-417-7509

About SomaLogic:
SomaLogic delivers meaningful and actionable health-management insights that empower individuals worldwide to continuously optimize their personal health and wellness throughout their lives.
These essential insights, provided through a global network of partners and users, are derived from precise, proprietary, and personalized measurement of critical changes in an individual’s proteins throughout life. For more information, visit

About Nan Fung Group:
Founded in 1954, Nan Fung Group is a conglomerate based in Hong Kong with global interests in real estate development and investment, financial investment, hotels and shipping. The Group continues to diversify its business and growth globally with interests in a diverse range of business partnerships, including life sciences.

About Nan Fung Life Sciences:
Nan Fung Life Sciences, part of Nan Fung Group, is a global life science investment platform with a significant presence in the US and Greater China.
Leveraging on the Group’s strong capital position, it has a long-term commitment to life sciences through direct investments and fund investments covering the full spectrum of the industry (including therapeutics, medical devices and diagnostics) and across different development stages.

About Madryn Asset Management, LP:
Madryn Asset Management, LP is a leading alternative asset management firm that invests in innovative healthcare companies specializing in unique and transformative products, technologies, and services. The firm draws on its extensive and diverse experience spanning the investment management and healthcare industries, and employs an independent research process based on original insights to target attractive economic opportunities that deliver strong risk-adjusted and absolute returns for its limited partners while creating long-term value in support of its portfolio companies. For additional information, please visit